WO2025231478A1

WO2025231478A1 - Techniques for hearing assistance in wearable devices

Info

Publication number: WO2025231478A1
Application number: PCT/US2025/027776
Authority: WO
Inventors: Martin Kuriger; Bernhard Kuenzle; John Raymon BRODIE; Nils Thomas Fritiof Lunner; Morteza KHALEGHIMEYBODI
Original assignee: Meta Platforms Inc
Current assignee: Meta Platforms Inc
Priority date: 2024-05-03
Filing date: 2025-05-05
Publication date: 2025-11-06
Anticipated expiration: 2026-11-03

Abstract

Some individuals may have hearing impairments and/or may be in situations that include impediments to hearing. The present disclosure relates to a method (800) comprising: generating (810) an audio signal based on sound received by one or more microphones of an open-ear device; and performing (820) a hearing enhancement process in response to user input, the hearing enhancement process comprising: detecting (830) a speech component of the audio signal; applying (840) a gain function to the speech component of the audio signal based on a plurality of gain parameters to generate a modified output signal; and operating (850) one or more loudspeakers of the open-ear device to produce sound according to the modified output signal.

Description

TECHNIQUES FOR HEARING ASSISTANCE IN WEARABLE DEVICES CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims benefit of and priority to U.S. provisional patent application Ser. No. 63/642168 filed May 3, 2024.

TECHNICAL FIELD

[0002] The present disclosure is directed to hearing assistance associated with an open-ear audio device, such as but not limited to smart glasses, headphones, head mounted displays, and/or any device that may provide sound without covering or blocking the ear completely.

BACKGROUND

[0003] Some individuals may have hearing impairments and/or may be in situations that include impediments to hearing. For example, a user may suffer from hearing loss or may be in a crowded space in which there are multiple sources of loud audio. Typically, in the scenario in which a user suffers from hearing loss, the user may wear (in or on-ear) a hearing correction device, such as a behind-the-ear (BTE) hearing aids, earbuds, personal sound amplification products (PSAPs), cochlear implants (Cl), and/or the like.

SUMMARY

[0004] According to a first aspect, there is provided a method comprising: generating an audio signal based on sound received by one or more microphones of an open-ear device; and performing a hearing enhancement process in response to user input, the hearing enhancement process comprising: detecting a speech component of the audio signal; applying a gain function to the speech component of the audio signal based on a plurality of gain parameters to generate a modified output signal; and operating one or more loudspeakers of the open-ear device to produce sound according to the modified output signal. [0005] Applying the gain function may comprise applying an adaptive dynamic range optimization gain to the speech component of the audio signal.

[0006] Applying the gain function may be based on one or more of: a comfort target; a background noise estimate; and an audibility threshold.

[0007] Detecting the speech component of the audio signal may comprise providing at least part of the audio signal, or data derived therefrom, to a neural network. The neural network may be trained on a training data set comprising a plurality of speech components and associated audio signals or data derived therefrom, as appropriate.

[0008] Detecting the speech component of the audio signal may be performed prior to applying the gain function.

[0009] The open-ear device may comprise a waveguide accessory. The method may further comprise reflecting the sound produced by the one or more loudspeakers toward an ear of a user. [0010] The waveguide accessory may include a passive waveguide structure removably attachable to the open-ear device.

[0011] The user input may comprise a touch gesture applied to the open-ear device.

[0012] According to a second aspect, there is provided a method comprising: generating an audio signal based on sound received by one or more microphones of an open-ear device; and performing a hearing enhancement process comprising: detecting a speech component of the audio signal; computing a signal level of the speech component of the audio signal; applying an adaptive dynamic range optimization gain to the speech component of the audio signal based on the computed signal level and one or more parameters, thereby generating a processed signal; operating one or more loudspeakers of the open-ear device to produce sound according to the processed signal; and reflecting the sound produced by the one or more loudspeakers toward an ear of a user using a waveguide accessory of the open-ear device.

[0013] The waveguide accessory may comprise a passive waveguide structure removably attachable to the open-ear device.

[0014] The adaptive dynamic range optimization gain may be updated in real time based on continuous computation of the signal level of the speech component of the audio signal.

[0015] The adaptive dynamic range optimization gain may be selectively applied to the speech component of the audio signal while suppressing non-speech components of the audio signal.

[0016] According to a third aspect, there is provided a wearable open-ear device comprising: at least one microphone; at least one loudspeaker comprising a passive waveguide; and at least one processing unit configured to carry out the method of the first aspect or the second aspect.

[0017] The at least one microphone may be spatially located in a predetermined distance from the at least one loudspeaker.

[0018] The passive waveguide may comprise a structure configured to couple to the openear device.

BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings illustrate a number of examples and are a part of the specification. Togetherwith the following description, these drawings demonstrate and explain various principles of the present disclosure.

[0020] FIG. 1 illustrates an example head-mounted display.

[0021] FIG. 2 illustrates the head-mounted display with a hearing enhancement pipeline.

[0022] FIG. 3 illustrates a block diagram of a hearing enhancement pipeline of the digital signal processor. [0023] FIG. 4 illustrates two different perspectives of a waveguide(s) affixed to the headmounted display.

[0024] FIGS. 5A and 5B illustrate improvements in sounds pressure and outputs attributed to the example waveguide of FIG. 4.

[0025] FIG. 6 illustrates a block diagram of an example hardware/software architecture of user equipment.

[0026] FIG. 7 illustrates a machine learning and training model.

[0027] FIG. 8 is a flow diagram of an exemplary method for generating a modified output signal from an input audio signal.

[0028] FIG. 9 is an illustration of an example artificial-reality system.

[0029] FIG. 10 is an illustration of an example artificial-reality system with a handheld device. [0030] FIG. 1 1A is an illustration of example user interactions within an artificial-reality system. [0031] FIG. 1 1 B is an illustration of example user interactions within an artificial-reality system. [0032] FIG. 12A is an illustration of example user interactions within an artificial-reality system. [0033] FIG. 12B is an illustration of example user interactions within an artificial-reality system. [0034] FIG. 13 is an illustration of an example wrist-wearable device of an artificial-reality system.

[0035] FIG. 14 is an illustration of an example wearable artificial-reality system.

[0036] FIG. 15 is an illustration of an example augmented-reality system.

[0037] FIG. 16A is an illustration of an example virtual-reality system.

[0038] FIG. 16B is an illustration of another perspective of the virtual-reality systems shown in FIG. 16A.

[0039] FIG. 17 is a block diagram showing system components of example artificial- and virtual-reality systems.

[0040] Throughout the drawings, identical reference characters and descriptions indicate similar, but not necessarily identical, elements. While the examples described herein are susceptible to various modifications and alternative forms, specific examples have been shown in the drawings and will be described in detail herein. However, the examples described herein are not intended to be limited to the particular forms disclosed. Rather, the present disclosure covers all modifications, equivalents, and alternatives falling within the scope of the appended claims.

DETAILED DESCRIPTION

[0041] As noted above, some individuals (also referred to herein as users) may have hearing impairments and/or may be in situations that include impediments to hearing. Some assistive technology designed to improve hearing, such as hearing aids, may hinder the user’s ability to use other devices such as smart sunglasses or other head mounted displays (HMDs). Therefore, it may be beneficial to provide an HMD that can incorporate assistive hearing technology.

[0042] This disclosure describes a passive waveguide component, which may be employed for various audio applications beyond its primary purpose. One of the main functions of the passive waveguide component may be to minimize audio leakage between loudspeakers and microphones integrated into glasses (e.g., smart glasses) or a headset/head mounted device, particularly in hearing enhancement and conversation focus scenarios, in which the acoustic coupling (e.g., acoustic feedback) between these components (e.g., loudspeakers and microphones) may need to be minimized. However, this passive waveguide component may offer additional benefits.

[0043] For example, in situations in which the user may be listening to music or podcasts, this passive waveguide component technology may significantly reduce audio leakage that may be audible to nearby bystanders. Typically, people close to the user wearing glasses (e.g., smart glasses) or a headset/head mounted device while listening to music or podcasts may be able to hear the audio content being played, but with the implementation of this passive waveguide component, audio leakage outside of the device may be substantially decreased, reducing the extent to which bystanders hear the audio and enhancing privacy for the user. These examples demonstrate the adaptability of the passive waveguide component. Firstly, the passive waveguide component may serve the hearing enhancement application by reducing leakage between speakers and microphones. Secondly, the passive waveguide component may cater to scenarios involving music or podcast consumption by minimizing audio leakage for the benefit of bystanders, promoting privacy for the user wearing the glasses (e.g., smart glasses) or the headset/head mounted device while listening to the music or the podcasts.

[0044] In some examples, for instance, an HMD may comprise a passive acoustic waveguide comprising a first portion dimensioned to redirect sound from a speaker of augmented reality glasses, a second portion dimensioned to guide the redirected sound toward an ear of a wearer of the augmented reality glasses, and a coupling mechanism configured to couple the passive acoustic waveguide to the augmented reality glasses.

[0045] In some example aspects, an HMD may be an open-ear device such as a glasses form-factor. In some example aspects, the HMD may be used to enhance what is audible for a user and/or to compensate or correct hearing loss for the user. In some example aspects, the HMD may be adjusted, tuned, and/or otherwise modified to enable hearing enhancement and/or hearing loss correction via one or more audio signal processing techniques using one or more generalized presets or profiles. The presets may be derived from one or more studies covering a sample of test subjects and/or one or more template audiograms. In some example aspects, the HMD may capture the acoustic scene around the user using a number of acoustic and/or contact microphones embedded within the HMD. In some example aspects, the HMD may render the enhanced, amplified, and/or otherwise processed signal for the user using open-ear transducers (e.g., unilateral or bilateral) embedded within the HMD. In some example aspects, the HMD may include one or more transducers. The one or more transducers may be air-conduction loudspeakers, bone conduction transducers, cartilage conduction transducers, and/or any other transducer utilizing any transduction method.

[0046] In some example aspects, the HMD may process audio via a hearing enhancement signal processing pipeline. The processing pipeline may utilize one or more processing blocks (e.g., methods, processes, sub-pipelines, and/or the like) such as own voice detection, own voice suppression, acoustic feedback reduction, echo cancellation, output limiters, noise suppression, wide dynamic range compression (WDRC), beamforming, and/or the like. The integration of these processing blocks — whether implemented by signal processing or machine learning applications may create a robust framework for enhancing audio on HMDs. In some examples, signal processing may involve predefined applications that may be designed to perform specific tasks, such as for example filtering frequencies or identifying patterns. In some other examples, machine learning-based approaches may be utilized by example aspects of the present disclosure and the machine learning-based approaches may involve training models (e.g., neural networks) on large datasets to learn, train and/or adapt the datasets to the signal characteristics associated with audio, which may provide more nuanced and effective noise reduction and quality enhancement as the HMD learns from more data.

[0047] In some example aspects, the HMD may detect the voice of the user wearing the HMD (the user’s “own voice”) using one or more microphones of the HMD. The HMD may suppress the user’s own voice by, for example, isolating the own voice from the rest of the audio scene, canceling or otherwise reducing the own voice from the audio scene, and rendering the audio scene without the own voice, or briefly muting all audio while the user is talking.

[0048] In some example aspects, the HMD may enable acoustic beamforming and spatial noise suppression using spatial information provided by a microphone array (also referred to herein as a “mic array”) to selectively amplify or otherwise enhance sounds from a target direction (e.g., from the front direction). Acoustic beamforming may utilize techniques such as, for example, Least Mean Squares (LMS), which may adjust the microphone array response to focus on the desired sound source, which may effectively steer the pickup pattern toward the microphone array. Spatial noise suppression may detect activity in front of a user and may suppress surrounding noise based on the difference between forward-facing and rear-facing beamformers (e.g., microphones) to suppress the surrounding noise. [0049] In some example aspects, the HMD may perform adaptive acoustic feedback reduction to process audio. Adaptive acoustic feedback reduction may be based on an LMS, or normalized LMS (NLMS), or a frequency shifting decorrelation approach.

[0050] In some example aspects, microphones on the HMD (e.g., on temple arms of glasses) may be used to detect the presence of objects as they move toward and/or away from the HMD (e.g., based on changes in loudness over time).

[0051] In some example aspects, the hearing enhancement or conversation focus functionality of the HMD may be enabled/disabled using hand gestures, such as tactile gestures (e.g., taps on the HMD or smart glasses), visual gestures (e.g., hand signals), or audible gestures (e.g., the audio of taps on the HMD or smart glasses). For example, the nature of the audio feedback path may be affected and changed by bringing a hand in close proximity to the HMD or smart glasses, and doing so thus may be classified as an event intent to enable or disable the hearing enhancement or conversation focus audio processing.

[0052] In some example aspects, a processor of the HMD may use metrics derived from behavior collected via eye-tracking sensors, cameras, audio streams, and/or other sensors, to infer a user’s perceived hearing difficulty, audiogram, and/or social activity. These inferences may be used as an assessment of functional communication abilities and may be used to inform the personalization of audio enhancement.

[0053] In some example aspects, the HMD may be fitted with an open-ear battery-less component for enhancing audio quality. The open-ear battery-less component may be a passive accessory designed to enhance the hearing correction and conversation focus features of the HMD. For example, the passive accessory may be a waveguide.

[0054] In some example aspects, the waveguide may funnel or otherwise direct the sound pressure from the loudspeakers of the HMD to the ears of a user(s). The waveguide may be acoustically open (e.g., transparent) so as to minimally affect the incoming sounds (e.g., direct acoustic path for the user). Fitting the HMD with the waveguide may improve the perceived audio gain of the HMD and may improve power consumption of the HMD, as the HMD may not need to work as hard to reach a target level of perceived audio gain.

[0055] In some example aspects, the waveguide may a variety of shapes and colors, which may be the same or different for each ear.

[0056] In some example aspects, a microphone of the HMD close to the speaker of the HMD that may be used to measure the acoustic impact of the waveguide to account for the waveguide in the signal processing by the HMD may be provided. In this manner, the HMD may reduce the output power and may still provide the correct perceived gain to the user.

[0057] In some example aspects, the waveguide may be optimized to reduce the acoustic feedback from the speaker to the microphones by directing the audio output from the HMD away from one or more microphones of the HMD.

[0058] Additional advantages will be set forth in part in the description which follows or may be learned by practice. The advantages will be realized and attainted by means of the elements and combinations particularly pointed out in the appended claims. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive, as claimed.

[0059] Some examples of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all examples of the disclosure are shown. Indeed, various examples of the disclosure may be embodied in many different forms and should not be construed as limited to the examples set forth herein. Like reference numerals refer to like elements throughout.

[0060] As used herein, the terms “data,” “content,” “information” and similar terms may be used interchangeably to refer to data capable of being transmitted, received and/or stored in accordance with examples of the disclosure. Moreover, the term “exemplary”, as used herein, is not provided to convey any qualitative assessment, but instead merely to convey an illustration of an example. Thus, use of any such terms should not be taken to limit the scope of examples of the disclosure.

[0061] As defined herein a “computer-readable storage medium,” which refers to a non- transitory, physical or tangible storage medium (e.g., volatile or non-volatile memory device), may be differentiated from a “computer-readable transmission medium,” which refers to an electromagnetic signal.

[0062] As referred to herein, an “application” may refer to a computer software package that may perform specific functions for users and/or, in some cases, for another application(s). An application(s) may utilize an operating system (OS) and other supporting programs to function. In some examples, an application(s) may request one or more services from, and communicate with, other entities via an application programming interface (API).

[0063] As referred to herein, “artificial reality” may refer to a form of immersive reality that has been adjusted in some manner before presentation to a user, which may include, for example, a virtual reality, an augmented reality, a mixed reality, a hybrid reality, Metaverse reality or some combination or derivative thereof. Artificial reality content may include completely computer-generated content or computer-generated content combined with captured (e.g., real-world) content. In some instances, artificial reality may be associated with applications, products, accessories, services, or some combination thereof, that may be used to, for example, create content in an artificial reality or are otherwise used in (e.g., to perform activities in) an artificial reality.

[0064] As referred to herein, “artificial reality content” may refer to content such as video, audio, haptic feedback, or some combination thereof, any of which may be presented in a single channel or in multiple channels (such as stereo video that produces a three-dimensional (3D) effect to the viewer) to a user.

[0065] As referred to herein, a Metaverse may denote an immersive virtual/augmented reality world in which augmented reality (AR) devices may be utilized in a network (e.g., a Metaverse network) in which there may, but need not, be one or more social connections among users in the network. The Metaverse network may be associated with three-dimensional (3D) virtual worlds, online games (e.g., video games), one or more content items such as, for example, non-fungible tokens (NFTs) and in which the content items may, for example, be purchased with digital currencies (e.g., cryptocurrencies) and other suitable currencies.

[0066] It is to be understood that the methods and systems described herein are not limited to specific methods, specific components, or to particular implementations. It is also to be understood that the terminology used herein is for the purpose of describing particular examples only and is not intended to be limiting.

[0067] The subject technology may provide hearing enhancement and/or hearing correction on HMDs. The following description may referto HMDs as smart glasses, for example, but the HMDs are not limited to smart glasses. One or more microphones (e.g., an array of microphones) on the smart glasses may capture the audio in a scene (e.g., an area in which the smart glasses are present), and one or more processing pipelines developed for the smart glasses form-factor may create an enhanced, amplified version of the audio scene (e.g., audio in the scene) and may render the audio through the one or more loudspeakers of the smart glasses. The user may perceive an enhanced version of the captured audio (e.g., audio scene), which may help the user have better speech intelligibility and lower listening efforts.

[0068] The subject technology may also or instead provide hearing enhancement on HMDs with a passive accessory that may be affixed to the HMD. The passive accessory may be a low cost device that channels the audio from the HMD to the user, allowing the user to obtain more acoustic power from their HMD. The accessory may be an acoustically open (e.g., transparent) waveguide that minimally affects the incoming sounds (e.g., ambient sounds from an audio scene). The accessory may result in an increased perceived gain from the HMD, which may increase the maximum perceived gain of the HMD and/or reduce the power utilization of the device as the device may have to work less hard to produce the same or similar perceived gain. The accessory may also decrease the feedback signal to the microphones by channeling speaker output away from the microphones of the HMD.

[0069] FIG. 1 illustrates an example HMD 100 (e.g., smart glasses). The HMD 100 may be worn by a user who may view visual content and/or hear audio content generated and presented by the HMD, such as by a processing system as described in further detail with respect to FIG. 6. For example, the HMD 100 may generate and present artificial reality content, including artificial/augmented hearing content. Artificial reality (AR) may include, for example, virtual reality, augmented reality, mixed reality, hybrid reality, or some combination or derivative thereof. Artificial reality content may include completely computer-generated content or computer-generated content combined with captured (e.g., real-world) content. The artificial reality content may include video, audio, haptic feedback, or some combination thereof, any of which may be presented in a single channel or in multiple channels (such as stereo video that produces a three-dimensional (3D) effect to the viewer). Additionally, in some instances, artificial reality may be associated with applications, products, accessories, services, or some combination thereof, that may be used to, for example, create content in an artificial reality or are otherwise used in (e.g., to perform activities in) an artificial reality.

[0070] HMD 100 may include frame 102 (e.g., an eyeglasses frame), one or more cameras 104, a display 108, an output audio device 1 10 (e.g., speakers), and/or an input audio device 106 (e.g., microphone). Display 108 may generate images viewable by the user of the HMD 100 and/or by another user. For instance, the display 108 may be a display screen, a projector, a holographic display, etc. In some examples, HMD 100 may be implemented in the form of augmented reality glasses. Accordingly, display 108 may be at least partially transparent to visible light to allow the user to view a real-world environment through the display 108. In some examples, HMD 100 may be implemented in the form of smart glasses. Accordingly, display 108 may be fully transparent to most visible light, such as sunglasses or reading glasses.

[0071] HMD 100 may include one or more cameras 104 (e.g., one or more front facing cameras that face away from a user and/or one or more rear-facing cameras that face toward the user). Camera 104 may track movement (e.g., gaze) of eye of a user or line of sight associated with user. Camera 104 may capture images or videos of an area, or capture video or images associated with a surface (e.g., eyes of a user or other areas of the face) depending on the directionality and view of camera 104. In examples where camera 104 is rear-facing toward the user, camera 104 may capture images or videos associated with a surface. In examples where camera 104 is front facing away from a user, camera 104 may capture images or videos of an area or environment. HMD 100 may be designed to have both front facing and rear-facing cameras (e.g., camera 104). There may be multiple cameras 104 that may be used to detect the reflection off of a surface (e.g., eyes) or other movements (e.g., glint or any other suitable characteristic). Camera 104 may be located on frame 102 in different positions. Camera 104 may be located along a width of a section of frame 102. In some other examples, the camera 104 may be arranged on one side of frame 102 (e.g., a side of frame 102 nearest to the eye). Alternatively, in some examples, the camera 104 may be located on display 108. In some examples, camera 104 may be sensors or a combination of cameras and sensors to track eyes (e.g., surface) of a user.

[0072] The input audio devices 106 may capture audio signals from a scene around the HMD 100. The audio of the input audio devices 106 may be processed by a processing system of the HMD 100. The processing system is discussed in further detail below with respect to FIG. 6. The audio processing is discussed in further detail below with respect to FIG. 3. The input audio devices 106 may be a microphone array in an omni-direction, single-mic bilateral configuration (e.g., one microphone at the front left of the HMD 100 and one microphone at the front right of the HMD 100). The input audio devices 106 may be in a directional, two-mic bilateral configuration. The input audio devices 106 may be in a transaural N-mic (e.g., 5 mics) beamformed configuration. The output audio device 1 10 (e.g., speakers) may provide the processed audio to the user. The output audio device 1 10 may be transducers within the HMD 100 such as air-conduction loudspeakers, bone conduction transducers, cartilage conduction transducers, and/or any other open-ear audio generating component.

[0073] FIG. 2 illustrates the HMD 100 with a hearing enhancement pipeline. To improve hearing or compensate for hearing loss, the HMD 100 may capture audio from one or more of its input audio devices 106. The captured audio signals may be provided to a digital signal processor (e.g., DSP 200) (e.g., processor 32 of FIG. 6). The DSP 200 may perform one or more transformations, modulations, or other modifications on the audio signal to generate an enhanced audio signal. The audio signal may be enhanced such that targeted audio sources (e.g., speaking individuals) may be amplified and/or that non-targeted audio sources (e.g., ambient sounds) may be reduced. The enhanced audio signal may be provided to the user via an output audio device 110 (e.g., a loudspeaker), which may be located proximate to and direct (202) audio to an ear of the user (e.g., on the temple of the HMD 100). In some scenarios, for example, when the gain (e.g., volume) of the enhanced audio is above a predetermined threshold level, the enhanced audio output by the output audio device 110 may be received as acoustic feedback by the input audio device 106.

[0074] FIG. 3 illustrates a block diagram of a hearing enhancement pipeline 300, which includes the DSP 200. It is contemplated that the hearing enhancement pipeline 300 may be implemented at least in part on a chip or processor (e.g., DSP 200) designed to support audio pathways in a device, such that audio signals may be decoded, amplified, or the like by at least part of the pipeline. In the example of FIG. 3, the DSP 200 comprises any one or more of own voice detection module 304, own voice suppression module 306, audio gesture detection module 308, proximity handler module 310, spatial noise suppression module 312 and compressor module 314. Each of these modules may be implemented using any combination of hardware and software and may be provided in any suitable combination. [0075] According to some examples, when the HMD 100 is executing an augmented hearing function, one or more microphones of the HMD may capture sound of the user’s own voice and the captured sound may be amplified (e.g., by the hearing enhancement pipeline 300). This amplification may produce an amplified signal of the user’s voice at their ear, which together with the production of the user’s voice from their mouth, may sound unnatural and/or may cause discomfort to the user. Hereinafter, the sound of the user’s voice may be referred to simply as “own voice.’’

[0076] The presence of own voice (or a measure of the likelihood that own voice sound is present) may be detected or determined by calculating a level difference of sound captured from a microphone(s) close to the mouth compared to the sound captured by one or more microphones further away from the mouth. Because the own voice may be a near-field sound, microphones closer to the mouth may be expected to have a higher level of own voice input. Accordingly, the difference between the audio of the microphone closer to the mouth of the user and the audio of the other microphones further from the mouth (e.g., on the temple of the HMD 100) of the user may be the user’s own voice.

[0077] The presence of a user’s own voice may additionally, or alternatively, be determined based on the direction of the audio’s arrival to the HMD’s microphones. Sound waves, including those of the user’s voice, may have a specific direction of arrival (DOA) relative to the microphone array. By leveraging this spatial characteristic, the HMD 100 may employ cross-correlation and coherence analysis techniques to discern the user’s voice from other audio inputs. Cross-correlation may involve the comparison of signal segments captured by different microphones to determine the time lag (or phase difference) that maximizes their correlation. This time lag may be indicative of the sound’s DOA, considering the known geometry of the microphone array. Coherence analysis may extend cross-correlation by evaluating the frequency domain relationship between signals from multiple microphones, providing a measure of how much two signals are linearly related in different frequency bands, which further aids in identifying the source of the sound. When applied, cross-correlation and coherence analysis may enable the HMD 100 to detect an instance in which the captured audio signals originate from the user, as opposed to environmental noise or other speakers, by matching the calculated DOA to the expected direction of the user’s voice.

[0078] The presence of own voice may additionally, or alternatively, be determined based on hybrid approaches that combine the analysis of near-field sounds — those emanating from close proximity to the microphones — with the directional information in the sound’s DOA. By crafting a beam pattern specifically tuned to capture the sound originating from the expected location of the user’s mouth, hybrid methods may effectively focus on the user’s voice. This may be achieved by manipulating the microphone array’s sensitivity to favor inputs coming from the direction where the user’s voice is projected. Concurrently, the HMD 100 may compare the level of sound captured by this user-focused beam with that captured by other beams or microphones oriented in different directions or configured to detect sound from farther fields. This is because the user’s voice is typically louder and more direct in the beam designed to capture the user’s voice, compared to more diffuse background noises or voices captured by other beams. This hybrid approach may be based on leveraging both the intensity of the near-field sound and the spatial DOA information, which may allow for a more nuanced and accurate identification of the user’s voice.

[0079] The presence of own voice may additionally, or alternatively, be determined based on frequency analysis of the audio captured by the microphones of the HMD 100. The audio spectrum may be segmented to enhance the accuracy of voice detection. Full band detection may employ a single detector that analyzes the entire audible spectrum as a single entity, allowing for a broad but less detailed capture of sound characteristics. This approach may not, however, provide the nuanced differentiation for complex auditory environments. Voice detection may also be segmented into several bands, typically dividing the spectrum into voiced and unvoiced sounds. Voiced sounds, which may be produced by the vibration of the vocal cords, exhibit distinct spectral properties different from unvoiced sounds, which may be created without the vocal cords’ vibration. This bifurcation may allow for a more refined analysis, enabling the HMD 100 to better distinguish between the user’s own voice and background noise. Further refinement may be achieved through the analysis of many individual frequency bands, such as those defined by third-octave bands, which may divide the audio spectrum into even narrower segments. This approach may allow for a detailed analysis of the sound spectrum, enabling the detection system of the HMD to identify the user’s own voice with greater precision by analyzing the unique spectral footprint of speech across these narrowly defined frequency bands. Each band may be individually analyzed for characteristics typical of human speech, improving the system’s ability to detect the user’s voice amidst a variety of background sounds.

[0080] Irrespective of which of the above techniques are applied to detect own voice, when the user’s own voice is detected, the HMD 100 may identify the gain of one or more frequency components of the own voice, and generate a suppression gain to counteract the gain of any one or more of these components. For instance, the HMD 100 may generate a powerfrequency spectrum representing the estimated portion of the sound captured by the microphone(s) that was produced by the user’s voice. This spectrum may be subtracted from subsequent sound captured by the microphone to suppress the presence of own voice in the sound signal.

[0081] In some examples, the HMD 100 may estimate the own voice (OV) insertion gain to produce a suppression gain. Own voice insertion gain may be aimed to be around 0 decibels (dB) to maintain a balance where the user’s voice may not overpower ambient sounds without artificial amplification. The estimate of the own voice spectrum may be derived from analyzing the output power of a beamformer — for example, an application that uses the input from multiple microphones to enhance the signal from a specific direction, in this case, the user’s mouth, during episodes of speech. The detection may employ a full band approach, considering the entire spectrum as a whole, or a sub-band method, focusing on specific frequency ranges for more granularity. Once the instantaneous spectrum of the own voice is captured, it may be converted into an OV-insertion gain. The conversion may be based on predetermined frequency-dependent calibration settings, such as those established during the device’s design phase and/or dynamically estimated in real-time. The latter approach may compare the level differences between the output from the beamformer and the input from microphones positioned near the ears, enabling a more personalized adjustment based on the current environmental context and user’s voice characteristics. To help the own voice be perceived naturally, without undue amplification or suppression, a frequency-dependent gain may be calculated. This gain adjustment may aim to keep a user’s own voice insertion gain at or near 0 dB maintaining the user’s voice at normal levels relative to the ambient sound environment. This calibration may enhance the user’s comfort and may also preserve the fidelity of environmental sounds, helping maintain a balanced and immersive auditory experience. In some example implementations, the HMD 100 may calculate an instantaneous own voice to ambient noise ratio. This ratio may provide another layer of context, allowing the system to adjust the frequency-dependent gain more intelligently based on the prevailing auditory environment. By doing so, the augmented hearing system may dynamically modulate the own voice insertion gain such that the user’s voice is neither too prominent nor drowned out by background noise.

[0082] In some example aspects, to reduce the presence of the user’s own voice from the audio input, the HMD 100 may utilize a source microphone(s) and/or beam pattern for which captured audio exhibits a comparatively low own voice level to capture audio, rather than capturing audio from a microphone and/or beam pattern that has a comparatively high voice level.

[0083] To reduce false positives, sounds emitted from the HMD 100 that are captured by the microphones may first be canceled. Hearing enhancement pipeline 300 may include one or more microphones (e.g., input audio device(s) 106), one or more acoustic feedback cancelers (AFCs) (e.g., AFC 302) associated with each of the microphones, and feedforward process(es) 210. A first microphone may be in close proximity to a loudspeaker, and the other microphones may be a predetermined distance from the loudspeaker and the first microphone. The predetermined distance may be any increment of distance away such that the audio signal received at the other microphones may be different in acoustic characteristic (e.g., phase, level, and/or the like). For example, the microphones may be in different positions on a frame (e.g., frame 102). In some examples, the hearing enhancement pipeline 300 may have one AFC (e.g., AFC 302) for each of the one or more microphones.

[0084] AFC 302 may implement any suitable application, technique, or method utilized for canceling audio feedback in a variety of audio devices (e.g., those utilized in digital hearing aids), and may be implemented using any suitable combination of hardware and software. Audio feedback may be defined as the audio produced during positive feedback in which an audio path is between an audio input (e.g., one or more microphones) and an audio output (e.g., one or more speakers). In this regard, positive feedback may refer to a process in a feedback loop which may exacerbate the effects of small re-captured audio signals (e.g., acoustic feedback 204), for example, a small audio signal may be increased in magnitude in an audio system where positive feedback occurs. For example, an audio signal received by a microphone may be amplified and passed out of a speaker. The sound from the speaker may then be received by the microphone again, thus amplifying the audio signal associated with the sound from the speaker further, and then passed out through the loudspeaker again. The action of the sound from the speaker being captured again through the microphone may result in a howl or distortion of the output associated with the speaker. The resultant howl or distortion may be an unwanted sound at which a feedback management system and/or an AFC may be utilized to mitigate acoustic feedback.

[0085] The audio signal may undergo a feedforward processing, in which feedforward processing may be any audio pathway that leads to the playing of sound, via a loudspeaker, to a user, such as but not limited to amplifying, decoding, or any other suitable process.

[0086] Feedforward processing may include one or more audio signal processing methods such as own voice detection module 304, own voice suppression module 306, audio gesture detection module 308, proximity handler module 310, spatial noise suppression module 312, and/or one or more forms of compressor module 314.

[0087] At least part of the hearing enhancement pipeline 300 may also or instead include spatial noise suppression module 312. The techniques described herein may include techniques for amplifying sounds that are of interest to the user without amplifying other sounds. For example, in a noisy restaurant, it may be desirable to amplify the speech of a person sitting in front of the wearer of the smart glasses (e.g., HMD 100) without amplifying the speech of people sitting behind the wearer of the smart glasses and non-speech sounds. Traditional and machine learning based single channel noise suppression methods may be used to selectively amplify speech. However, such methods may be unable to discriminate between speech coming from different directions and may therefore amplify both desired and undesired speech sounds. Beamforming may be used to increase the amplification of sounds in a particular direction, but this may be limited by the geometry of the microphone array and the level of amplification required for augmented hearing, and as such some sounds from undesired directions may still be amplified.

[0088] Spatial noise suppression module 312 may take advantage of spatial information provided by the multi-microphone array in the HMD 100 to selectively amplify sounds from a desired direction. The combination of spatial noise suppression, beamforming, and/or single channel noise suppression may then selectively amplify speech sounds from the front of the wearer of the smart glasses.

[0089] For example, spatial noise suppression module 312 may leverage the distinct configurations of forward-facing and rear-facing beamformers to enhance the auditory experience of the user by focusing on sounds originating from the front of a user wearing the smart glasses. The forward-facing beamformer may be calibrated to be receptive to sounds coming from the user’s frontal direction, making it adept at capturing conversations or any relevant auditory signals that the wearer may be directly facing. Conversely, the rear-facing beamformer may be configured with a nullification pattern for sounds coming from the front, effectively treating these sounds as noise. This setup may enable the rear-facing beamformer to act as a baseline for ambient noise levels, thus providing a valuable contrast to the forward beam’s inputs. By analyzing the level difference between the outputs of these two beamformers, the HMD 100 may gauge the presence and intensity of sound activities occurring in front of the user. This differential may be evaluated over the full audio spectrum or within specific frequency bands, allowing for a nuanced understanding of the sound environment. Utilizing a combination of thresholding and scaling, an approximate Signal-to- Noise Ratio (SNR) may be derived for each relevant band. This SNR may form the basis for calculating or otherwise determining the Wiener Gain, which may be applied to produce a noise suppression gain per band, thereby enhancing the clarity and prominence of sounds emanating from in front of the wearer.

[0090] In some example implementations, the probability of speech presence may be determined based on the level differential, facilitating a more sophisticated SNR determination that may consider estimates of both speech and noise levels derived from the beamformer outputs. Such an approach may allow for dynamic adjustment of noise suppression parameters, helping the user to focus on important sounds without being overwhelmed by background noise.

[0091] At least part of the hearing enhancement pipeline 300 may also or instead include audio gesture detection module 308. The HMD 100 may have several features that the user may want to control while wearing the HMD 100. It may be beneficial to the user experience for the user to be able to control these features without the need to access a secondary external device such as a smartphone. However, there may be limited space in the HMD formfactor for dedicated user interface (Ul) buttons and/or sensors.

[0092] Accordingly, an existing microphone array may be used to acoustically detect gestures such as, for example, double-taps, triple-taps, and/or cupping hand around the ear/microphones. These gestures may be used to control the augmented hearing features of the HMD without the need for dedicated Ul sensors or access to an external device. The utilization of an existing microphone array for the detection of acoustical gestures integrates seamlessly into the user’s experience by converting simple gestures into meaningful commands, leveraging three primary components such as for example tap detection, gesture/sequence detection, and/or event management.

[0093] In the tap detection process, one or more microphones within the array may be designated as sensors to capture potential tap sounds. To distinguish these sounds from background noise or speech, the audio signal may first be subjected to a low-pass filter. Following this, the instantaneous power of the filtered audio may be calculated and then smoothed over time with two distinct time constants (e.g., one fast and one slow), creating a fast and a slow smoothed power profile. By comparing the level difference between these two profiles against a predefined/predetermined threshold, the HMD 100 may discern whether an impulse, indicative of a tap, has occurred. Further, by examining the level difference between the microphone’s instantaneous power and that of other microphones in the array, it may be possible to differentiate between a tap gesture and ambient environmental sounds, provided both level differences surpass their respective thresholds.

[0094] The audio gesture detection module 308 may apply a series of timing constraints to these detected taps to confirm the presence of a valid gesture. These constraints may include the minimum and maximum time allowed between taps, as well as the specific number of taps required for a gesture(s). In an instance in which a sequence of taps on a given microphone aligns with these criteria, a gesture may be registered by the HMD 100. To enhance user feedback, an audio cue, such as a chime, may be produced to signify successful gesture detection.

[0095] Event management ties gestures to specific actions, transforming physical interactions into controls for a device (e.g., HMD 100). Depending on the detected tap sequence, various commands may be executed, ranging from muting or adjusting the volume of the augmented hearing feature to toggling noise suppression on or off. Similar to gesture detection, audio feedback may be provided upon the activation of an event, offering users immediate confirmation of their selected action. [0096] At least part of the hearing enhancement pipeline 300 may also or instead include a proximity handler module 310. Smart glasses with an augmented hearing function may be susceptible to howling. Howling sounds may occur when sound from the speaker (e.g., producing amplified sound from the user’s environment) leak back to the microphones and create a feedback loop amplifying previously amplified audio. There may be a range of feedback mitigation approaches such as feedback cancelation, open loop gain control, and feedback suppression that may be used to minimize howling. However, the effectiveness of these mechanisms may degrade when hands (or other objects) are moved near the HMD or when the HMD is being handled (e.g., put on or removed). Feedback mitigation applications may make use of information about the presence proximity/handling information to further minimize the severity of howling. Examples include speeding up the feedback canceler or making feedback suppression applications more sensitive/aggressive. In the case of handling, the augmented hearing system may be temporality disabled.

[0097] Leveraging microphones positioned on the temples or arms of the HMD (e.g., HMD 100) may offer a sophisticated method for detecting the presence of objects, such as hands, as they approach or recede from the HMD. This capability is particularly relevant in environments where ambient sound is present. The principle behind this detection lies in the observation that the sound pressure level (SPL) around the smart glasses tends to increase when an object enters the nearby sound field, a phenomenon that holds true regardless of whether any augmented processing functions are activated on the smart glasses. The process of proximity handling may involve monitoring localized SPL increases, which may signify hand movement near one side of the head of a user. This may be achieved by analyzing the SPL difference between microphones positioned on different parts of the HMD 100, such as those on the left and right temples. This level difference metric may serve as a key indicator of object presence. Furthermore, comparing SPL differences between microphones on the same side of the head of a user may enhance the accuracy of this detection mechanism. To accommodate various detection scenarios, multiple level difference metrics may be employed, including comparisons between left/right microphone pairs as well as front/rear pairs, or even contrasting the maximum microphone level against the average level. To avoid skewing the measurements by the inherent characteristics of the sound field or the head shadow effect, a baseline level difference metric may be established. This baseline level difference metric may be derived from a smoothed difference between the SPL readings across the microphones, allowing the HMD 100 to focus on changes in the object’s location rather than constant environmental sound levels. This approach effectively distinguishes between the introduction or removal of objects near the smart glasses. However, challenges such as sudden changes in head orientation within a directional sound field may temporarily alter the baselined level difference, potentially leading to false detections. To mitigate this, the system may characterize the level difference across different frequencies, enabling the determination of a level-dependent threshold at the design stage. This threshold may be tailored to minimize false positives by accounting for the distinct spectral changes in level difference caused by sound diffraction around the head versus those induced by objects near the smart glasses. Such a nuanced understanding of the interplay between sound dynamics and object detection paves the way for smart glasses equipped with this technology to serve as highly responsive, interactive devices, capable of intelligently responding to the user’s environment and actions. [0098] At least part of the hearing enhancement pipeline 300 may also or instead include one or more compressor modules 314 that may apply audio compression to an audio signal received from the input audio device(s) 106 and/or from any other module in the DSP 200. Hearing aids may have independent mono compressors for each ear, which may result in reducing interaural level differences (ILD) which may negatively affect localization. By contrast, the compressor module 314 of the HMD 100 may provide stereo compression. As the HMD has access to the stereo signal, the HMD 100 may split the processing into a mono compressor that produces identical gains on both sides (preserving ILD) and a spatial compressor that handles the differences between left and right (boosting spatial cues). The mono and spatial compressors may have different settings (e.g., frequency resolution, smoothing). The input to the compressors may be the average or maximum level of left and right for the mono compressor and may simply the level difference for the spatial compressor. The HMD 100 may also provide a temple mic compressor on logo mic signal. Due to acoustic feedback issues, the temple mic signal may be avoided as input to the signal path. However, the temple mic signal may still safely be used for the signal analysis. The HMD 100 may therefore determine the compressor gains based on the temple mic signal and may apply the compressor gains on the other microphones that may be used for feedback safe inputs to the signal path. The signal path may also or instead be limited (e.g., with a limiter) to the temple mic level, which may reduce own voice and may improve spatial cues especially in high frequencies. The HMD 100 may also provide object-based compression, applying an independent gain table per “object” in a scene. Objects may be defined as active speakers, individuals in the conversation, or individuals of interest at any given time. Independent gain/compression may be applied to each object. A single gain table may be applied to combined sources at the input. Applying independent compression per source may allow for audibility to be enhanced based on the classification of objects in the scene. The HMD 100 may also provide scene-based compression, applying specific gain/compression parameters based on scene details. For example, gain/compression may become flatter and more linear if the HMD detects the user is listening to music and the gain/compression may emphasize mid-frequencies more if speech is detected in a noisy environment.

[0099] In some example aspects, background sounds may be blurred (or otherwise distorted) to emphasize the target speaker. To help the user distinguish the target from the background sounds, the HMD 100 may actively add a jamming signal that covers, masks, blurs, scrambles, or otherwise distorts the background audio sources.

[0100] In some example aspects, output power of the HMD speakers may be limited if speaker occlusion is detected. The speakers play much louder than the audio that arrives at the eardrum because a lot of energy may be lost on the way. If the user put his hand over the ear and the speaker much less energy may be lost and the sound level at the eardrum may become uncomfortably loud. This may degrade user experience in both hearing enhancement but also in instances of streaming audio. This situation may be detected using the level of the temple mic. The temple mic level (maybe with an offset) may serve as an estimate of the sound pressure level the user may experience at the eardrum. If this level becomes too big, as in the hand occlusion case, the HMD (e.g., HMD 100) may immediately reduce the gain and may keep the eardrum level comfortable.

[0101] In some example aspects, Adaptive Dynamic Range Optimization (ADRO) (or similar gain function such as adaptive linear gain) may be combined with machine learning based speech enhancement. Unlike WDRC, which may apply a fixed compression ratio across a broad range of input levels, leading to potential over-amplification of certain frequencies, ADRO may employ a more nuanced, adaptive approach to linear gain adjustment. This methodology may allow for the dynamic optimization of the audio signal’s dynamic range, amplifying speech in a manner that preserves its natural qualities and minimizes the perceptibility of any spectral distortion that may have been introduced during the enhancement process. ADRO, or similar adaptive linear gain approaches, may provide a more consistent listening experience across various sound environments. By avoiding the over-amplification of artifacts and applying gain proportional to the input signal’s characteristics, these techniques may maintain the clarity and intelligibility of speech without introducing the auditory discomfort that may result from spectral distortion.

[0102] FIG. 4 illustrates two different perspectives of a waveguide(s) 402 that may be affixed to the HMD 100. The integration of a waveguide(s) 402 as an accessory for the HMD 100 may be a cost-effective, passive solution designed to significantly amplify the sound delivered to the user’s ear canals without necessitating additional power consumption from the HMD 100. The waveguide(s) 402 may operate on two principal functions. First, the waveguide(s) 402 may efficiently channel the sound pressure generated by the loudspeakers of the HMD 100 directly toward the ear canals enhancing the clarity and volume of the audio (e.g., by approximately 8-10 dB). Second, the waveguide(s) 402 maintains acoustic openness or transparency such that the HMD 100 may not impede the natural flow of ambient sounds to the user, thereby preserving the auditory experience of the surrounding environment. This dual functionality of the waveguide(s) 402 may be beneficial for users that want a louder output from their devices, whether for general use or to support specific features such as hearing enhancement or conversation focus. Because the waveguide(s) 402 may passively provide an additional approximately 8-10 dB of volume to the HMD 100, the HMD may save the additional power that it would have taken to actively generate the approximately 8-10 dB of added volume, and thus the waveguide(s) 402 may contribute to both improved audibility and enhanced battery efficiency. This is especially valuable for users with mild to moderate hearing loss, as it may allow for a higher maximum stable gain (MSG), improving the user’s ability to engage with both the digital and physical worlds around the users. To facilitate the waveguide(s)’s practicality and aesthetic appeal, the waveguide(s)’s design may incorporate fashionable elements, offering variations in transparency, shapes, and colors to satisfy user preferences. Moreover, the inclusion of a microphone in close proximity to a speaker within the HMD 100 may facilitate real-time monitoring of the acoustic impact of the waveguide(s) 402. This feature allows for precise adjustments in the output power of the HMD 100, such that the correct insertion gain is consistently provided to the user, thereby improving the auditory experience.

[0103] The waveguides 402 (e.g., one for each ear) may be designed as substantially flat attachments that serve to direct and amplify sound output toward the user’s ear(s). The waveguides 402 may include loops, magnets, or other fasteners that allow the waveguides 402 to be fitted to the HMD 100, for example, on the temples of the HMD over a speaker and ear of the user. Given their integration with fashion-sensitive products like smart glasses, waveguides may be crafted in a variety of shapes to complement the aesthetics of the smart glasses while maintaining their functional purpose. Shapes such as curved lines that follow the contour of the arms of smart glasses, geometric patterns that add a decorative element, or minimalistic designs that blend seamlessly with the frame are possible in the example aspects of the present disclosure. The materials used to construct the waveguides 402 may include advanced polymers, such as acrylonitrile butadiene styrene (ABS) or polycarbonate, which are lightweight and offer flexibility in terms of shaping and coloring. These materials may also possess the rigidity to efficiently channel sound waves without significant loss of energy. Additionally, bio-compatible materials may be considered for users with sensitive skin or allergies ensuring comfort during prolonged use. For the acoustic transparency features, materials that may reflect sound toward the ear while allowing ambient noise to pass through — like certain porous or mesh-like structures may be employed. Such materials may enable the waveguides 402 to enhance the audio output of the HMD 100 without isolating the user from the user’s environment.

[0104] In some example aspects, an optimized version of the waveguide(s) 402 may be developed to reduce acoustic feedback from a speaker (e.g., output audio device 110) back to the microphones (e.g., input audio device 106). For example, the waveguide(s) 402 may be angled relative to the HMD 100 such that audio output from a speaker on a side of the HMD 100 may be directed to the rear of the HMD 100, and thus may reduce the audio output that arrives at microphones located at a front of the HMD 100. This may minimize the likelihood of feedback loops, enhancing the overall sound quality and clarity of a device (e.g., HMD 100). [0105] FIGS. 5A and 5B illustrate improvements in sounds pressure and outputs attributed to the example waveguide of FIG. 4.

[0106] FIG. 5A illustrates an acoustic improvement achieved with a passive (e.g., unpowered, battery-less) waveguide accessory. The dashed line 508 may represent the loudspeaker frequency response at an ear of a user without a waveguide. The y-axis may represent sound pressure level at the eardrum reference position (DRP) of the user, and the solid lines 502, 504, 506 on the graph 500 may show the sound pressure level (SPL) generated at each frequency for a fixed sinusoidal input level. The x-axis may represent the frequency of sinewave input to a system (e.g., an HMD). The solid lines 502, 504, 506 may represent the frequency response of the system (e.g., the HMD) with the passive waveguide installed on the system (e.g., the HMD). In FIG. 5A, the passive waveguide may increase the SPL at DRP by 5-10 dB over most of the audio frequency range in relation to the baseline (without the passive waveguide) (e.g., dashed line 508).

[0107] FIG. 5B illustrates a comparison of SPLs measured at the eardrum reference position across different passive waveguide scenarios. For example, the y-axis may represent improvements in output measured in dBs. The x-axis may represent the frequency of sinewave input to a system (e.g., an HMD). The solid lines 502, 504, 506 may depict the enhancement in auditory output experienced by the user when a passive waveguide is utilized by the system, for example in an instance in which the user may be wearing an HMD having the passive waveguide. The dashed line 508 may indicate the auditory output enhancement experienced by the user in the absence of a system having a passive waveguide. The graph 501 may demonstrate (e.g., via the three solid lines 502, 504, 506) that sound pressure data, obtained in three separate instances, may be improved by utilizing the passive waveguide.

[0108] FIG. 6 illustrates a block diagram of an example hardware/software architecture of user equipment (UE) 30. The UE 30 may illustrate components of the HMD 100, for instance. As shown in FIG. 6, the UE 30 (also referred to herein as node 30) may include a processor 32, non-removable memory 44, removable memory 46, a speaker/microphone 38, a keypad 40, a display, touchpad, and/or indicators 42, a power source 48, a global positioning system (GPS) chipset 50, and other peripherals 52. The UE 30 may also include a camera 54. In an example, the camera 54 is a smart camera configured to detect objects appearing within one or more bounding boxes. The UE 30 may also include communication circuitry, such as a transceiver 34 and a transmit/receive element 36 for electronic communications 21 . It will be appreciated that the UE 30 may include any sub-combination of the foregoing elements while remaining consistent with an example.

[0109] The processor 32 may be a special purpose processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Array (FPGAs) circuits, any other type of integrated circuit (IC), a state machine, and the like. In general, the processor 32 may execute computer executable instructions stored in the memory (e.g., memory 44 and/or memory 46) of the node 30 in order to perform the various required functions of the node. For example, the processor 32 may perform signal coding, data processing, power control, input/output processing, and/or any other functionality that enables the node 30 to operate in a wireless or wired environment. The processor 32 may run application-layer programs (e.g., browsers) and/or radio access-layer (RAN) programs and/or other communications programs. The processor 32 may also perform security operations such as authentication, security key agreement, and/or cryptographic operations, such as at the access layer and/or application layer for example.

[0110] The processor 32 is coupled to its communication circuitry (e.g., transceiver 34 and transmit/receive element 36). The processor 32, through the execution of computer executable instructions, may control the communication circuitry in order to cause the node 30 to communicate with other nodes via the network to which it is connected.

[0111] The transmit/receive element 36 may be configured to transmit signals to, or receive signals from, other nodes or networking equipment. For example, in an example, the transmit/receive element 36 may be an antenna configured to transmit and/or receive radio frequency (RF) signals. The transmit/receive element 36 may support various networks and air interfaces, such as wireless local area network (WLAN), wireless personal area network (WPAN), cellular, and the like. In yet another example, the transmit/receive element 36 may be configured to transmit and receive both RF and light signals. It will be appreciated that the transmit/receive element 36 may be configured to transmit and/or receive any combination of wireless or wired signals.

[0112] The transceiver 34 may be configured to modulate the signals that are to be transmitted by the transmit/receive element 36 and to demodulate the signals that are received by the transmit/receive element 36. As noted above, the node 30 may have multi-mode capabilities. Thus, the transceiver 34 may include multiple transceivers for enabling the node 30 to communicate via multiple radio access technologies (RATs), such as universal terrestrial radio access (UTRA) and Institute of Electrical and Electronics Engineers (IEEE 802.1 1), for example.

[0113] The processor 32 may access information from, and store data in, any type of suitable memory, such as the non-removable memory 44 and/or the removable memory 46. For example, the processor 32 may store session context in its memory, as described above. The non-removable memory 44 may include RAM, ROM, a hard disk, or any other type of memory storage device. The removable memory 46 may include a subscriber identity module (SIM) card, a memory stick, a secure digital (SD) memory card, and the like. In other examples, the processor 32 may access information from, and store data in, memory that is not physically located on the node 30, such as on a server or a home computer.

[0114] The processor 32 may receive power from the power source 48 and may be configured to distribute and/or control the power to the other components in the node 30. The power source 48 may be any suitable device for powering the node 30. For example, the power source 48 may include one or more dry cell batteries (e.g., nickel-cadmium (NiCad), nickelzinc (NiZn), nickel metal hydride (NiMH), lithium-ion (Li-ion), etc.), solar cells, fuel cells, and the like.

[0115] The processor 32 may also be coupled to the GPS chipset 50, which may be configured to provide location information (e.g., longitude and latitude) regarding the current location of the node 30. It will be appreciated that the node 30 may acquire location information by way of any suitable location-determination method while remaining consistent with an example.

[0116] FIG. 7 illustrates a machine learning and training model, in accordance with an example of the present disclosure. The machine learning framework 600 associated with the machine learning model may be hosted remotely. Alternatively, the machine learning framework 600 may reside within the HMD 100 shown in FIG. 1 , or be processed by an electronic device (e.g., head mounted displays, smartphones, tablets, smartwatches, or any electronic device). The machine learning model 610 may be operably coupled to the stored training data 620 in a memory or database (e.g., ROM, RAM) such as a training database. In some examples, the machine learning model 610 may be associated with operations of FIG. 2, FIG. 3, or FIG. 4. In some other examples, the machine learning model 610 may be associated with other operations. The machine learning model 610 may be implemented by one or more machine learning models(s) and/or another device (e.g., a server and/or a computing system).

[0117] FIG. 8 is a flow diagram of an exemplary computer-implemented method 800 for generating a modified output signal from an input audio signal. The steps shown in FIG. 8 may be performed by any suitable computer-executable code and/or computing system, including any of the system(s) illustrated in FIGS. 1-6. In one example, each of the steps shown in FIG. 8 may represent an algorithm whose structure includes and/or is represented by multiple substeps, examples of which will be provided in greater detail below.

[0118] As illustrated in FIG. 8 at step 810 the system performing method 800 may generate an audio signal based on sound received by one or more microphones of an open-ear device. For example, audio signals may be generated from sound received by one or more microphones of the HMD 100 (e.g., one or more of input audio devices 106).

[0119] At step 820, the system performing method 800 may perform a hearing enhancement process in response to user input. For example, hearing enhancement pipeline 300 may perform one or more of the processes described above in response to user input. In some examples, the user input may include a touch gesture.

[0120] At step 830 the system performing method 800 may analyze the audio signal generated in step 810 to detect a speech component of the audio signal. For example, HMD 100 may detect one or more frequency components of the audio signal as originating from the user’s speech. The HMD 100 may further distinguish the speech component as being distinct from components of the audio signal produced by environmental noise or by the speech of others.

[0121] The system performing method 800 may perform step 830 in a variety of ways. In one example, the step of analyzing the audio signal to detect the speech component may include detecting the speech component using a neural network. For example, machine learningbased approaches may be utilized by example aspects of the present disclosure and the machine learning-based approaches may involve training models (e.g., neural networks) on large datasets to learn, train and/or adapt the datasets to the signal characteristics associated with audio, which may provide more nuanced and effective noise reduction and quality enhancement as HMD 100 learns from more data.

[0122] At step 840 the system performing method 800 applies a gain function to the speech component of the audio signal based on a plurality of gain parameters. For example, a gain function such as Adaptive Dynamic Range Optimization may be combined with machine learning based speech enhancement to employ a more nuanced, adaptive approach to linear gain adjustment. In step 840 the process of applying the gain function by the system performing method 800 produces a modified output signal. For example, the audio signal’s dynamic range may be dynamically optimized, thereby amplifying speech in a manner that preserves its natural qualities and minimizes the perceptibility of any spectral distortion that may have been introduced during the enhancement process.

[0123] The system performing method 800 may perform step 840 in a variety of ways. In one example, the gain function may include applying an adaptive dynamic range optimization gain to the speech component of the audio signal generated in step 810. In some examples, the gain function is further based on various elements including but not limited a comfort target levels, a background noise estimate, and audibility thresholds. In some examples, the speech component generated by the user may be separated from background noise prior to applying the gain function.

[0124] At step 850 the system performing method 800 may operate one or more loudspeakers of the open-ear device to produce sound in accordance with the modified output signal. For example, the enhanced audio signal may be provided to the user via output audio device 110 (e.g., a loudspeaker), which may be located proximate to and direct (202) audio to an ear of the user (e.g., on the temple of the HMD 100).

[0125] Embodiments of the present disclosure may include or be implemented in conjunction with various types of Artificial-Reality (AR) systems. AR may be any superimposed functionality and/or sensory-detectable content presented by an artificial-reality system within a user’s physical surroundings. In other words, AR is a form of reality that has been adjusted in some manner before presentation to a user. AR can include and/or represent virtual reality (VR), augmented reality, mixed AR (MAR), or some combination and/or variation of these types of realities. Similarly, AR environments may include VR environments (including non- immersive, semi-immersive, and fully immersive VR environments), augmented-reality environments (including marker-based augmented-reality environments, markerless augmented-reality environments, location-based augmented-reality environments, and projection-based augmented-reality environments), hybrid-reality environments, and/or any other type or form of mixed- or alternative-reality environments.

[0126] AR content may include completely computer-generated content or computergenerated content combined with captured (e.g., real-world) content. Such AR content may include video, audio, haptic feedback, or some combination thereof, any of which may be presented in a single channel or in multiple channels (such as stereo video that produces a three-dimensional (3D) effect to the viewer). Additionally, In some examples, AR may also be associated with applications, products, accessories, services, or some combination thereof, that are used to, for example, create content in an artificial reality and/or are otherwise used in (e.g., to perform activities in) an artificial reality.

[0127] AR systems may be implemented in a variety of different form factors and configurations. Some AR systems may be designed to work without near-eye displays (NEDs). Other AR systems may include a NED that also provides visibility into the real world (such as, e.g., augmented-reality system 1500 in FIG. 15) or that visually immerses a user in an artificial reality (such as, e.g., virtual-reality system 1600 in FIGS. 16A and 16B). While some AR devices may be self-contained systems, other AR devices may communicate and/or coordinate with external devices to provide an AR experience to a user. Examples of such external devices include handheld controllers, mobile devices, desktop computers, devices worn by a user, devices worn by one or more other users, and/or any other suitable external system.

[0128] FIGS. 9-12B illustrate example artificial-reality (AR) systems. FIG. 9 shows a first AR system 900 and first example user interactions using a wrist-wearable device 902, a headwearable device (e.g., AR glasses 1500), and/or a handheld intermediary processing device (HIPD) 906. FIG. 10 shows a second AR system 1000 and second example user interactions using a wrist-wearable device 1002, AR glasses 1004, and/or an HIPD 1006. FIGS. 11A and 11 B show a third AR system 1100 and third example user 1108 interactions using a wristwearable device 1102, a head-wearable device (e.g., VR headset 1150), and/or an HIPD 1106. FIGS. 12A and 12B show a fourth AR system 1200 and fourth example user 1208 interactions using a wrist-wearable device 1230, VR headset 1220, and/or a haptic device 1260 (e.g., wearable gloves).

[0129] A wrist-wearable device 1300, which can be used for wrist-wearable device 902, 1002, 1102, 1230, and one or more of its components, are described below in reference to FIGS. 13 and 14; head-wearable devices 1500 and 1600, which can respectively be used for AR glasses 904, 1004 or VR headset 1150, 1220, and their one or more components are described below in reference to FIGS. 15-17.

[0130] Referring to FIG. 9, wrist-wearable device 902, AR glasses 904, and/or HIPD 906 can communicatively couple via a network 925 (e.g., cellular, near field, Wi-Fi, personal area network, wireless LAN, etc.). Additionally, wrist-wearable device 902, AR glasses 904, and/or HIPD 906 can also communicatively couple with one or more servers 930, computers 940 (e.g., laptops, computers, etc.), mobile devices 950 (e.g., smartphones, tablets, etc.), and/or other electronic devices via network 925 (e.g., cellular, near field, Wi-Fi, personal area network, wireless LAN, etc.).

[0131] In FIG. 9, a user 908 is shown wearing wrist-wearable device 902 and AR glasses 904 and having HIPD 906 on their desk. The wrist-wearable device 902, AR glasses 904, and HIPD 906 facilitate user interaction with an AR environment. In particular, as shown by first AR system 900, wrist-wearable device 902, AR glasses 904, and/or HIPD 906 cause presentation of one or more avatars 910, digital representations of contacts 912, and virtual objects 914. As discussed below, user 908 can interact with one or more avatars 910, digital representations of contacts 912, and virtual objects 914 via wrist-wearable device 902, AR glasses 904, and/or HIPD 906.

[0132] User 908 can use any of wrist-wearable device 902, AR glasses 904, and/or HIPD 906 to provide user inputs. For example, user 908 can perform one or more hand gestures that are detected by wrist-wearable device 902 (e.g., using one or more EMG sensors and/or IMUs, described below in reference to FIGS. 13 and 14) and/or AR glasses 904 (e.g., using one or more image sensor or camera, described below in reference to FIGS. 15-10) to provide a user input. Alternatively, or additionally, user 908 can provide a user input via one or more touch surfaces of wrist-wearable device 902, AR glasses 904, HIPD 906, and/or voice commands captured by a microphone of wrist-wearable device 902, AR glasses 904, and/or HIPD 906. In some examples, wrist-wearable device 902, AR glasses 904, and/or HIPD 906 include a digital assistant to help user 908 in providing a user input (e.g., completing a sequence of operations, suggesting different operations or commands, providing reminders, confirming a command, etc.). In some examples, user 908 can provide a user input via one or more facial gestures and/or facial expressions. For example, cameras of wrist-wearable device 902, AR glasses 904, and/or HIPD 906 can track eyes of user 908 for navigating a user interface.

[0133] Wrist-wearable device 902, AR glasses 904, and/or HIPD 906 can operate alone or in conjunction to allow user 908 to interact with the AR environment. In some examples, HIPD 906 is configured to operate as a central hub or control center for the wrist-wearable device 902, AR glasses 904, and/or another communicatively coupled device. For example, user 908 can provide an input to interact with the AR environment at any of wrist-wearable device 902, AR glasses 904, and/or HIPD 906, and HIPD 906 can identify one or more back-end and frontend tasks to cause the performance of the requested interaction and distribute instructions to cause the performance of the one or more back-end and front-end tasks at wrist-wearable device 902, AR glasses 904, and/or HIPD 906. In some examples, a back-end task is a background processing task that is not perceptible by the user (e.g., rendering content, decompression, compression, etc.), and a front-end task is a user-facing task that is perceptible to the user (e.g., presenting information to the user, providing feedback to the user, etc.). HIPD 906 can perform the back-end tasks and provide wrist-wearable device 902 and/or AR glasses 904 operational data corresponding to the performed back-end tasks such that wrist-wearable device 902 and/or AR glasses 904 can perform the front-end tasks. In this way, HIPD 906, which has more computational resources and greater thermal headroom than wristwearable device 902 and/or AR glasses 904, performs computationally intensive tasks and reduces the computer resource utilization and/or power usage of wrist-wearable device 902 and/or AR glasses 904.

[0134] In the example shown by first AR system 900, HIPD 906 identifies one or more back- end tasks and front-end tasks associated with a user request to initiate an AR video call with one or more other users (represented by avatar 910 and the digital representation of contact 912) and distributes instructions to cause the performance of the one or more back-end tasks and front-end tasks. In particular, HIPD 906 performs back-end tasks for processing and/or rendering image data (and other data) associated with the AR video call and provides operational data associated with the performed back-end tasks to AR glasses 904 such that the AR glasses 904 perform front-end tasks for presenting the AR video call (e.g., presenting avatar 910 and digital representation of contact 912).

[0135] In some examples, HIPD 906 can operate as a focal or anchor point for causing the presentation of information. This allows user 908 to be generally aware of where information is presented. For example, as shown in first AR system 900, avatar 910 and the digital representation of contact 912 are presented above HIPD 906. In particular, HIPD 906 and AR glasses 904 operate in conjunction to determine a location for presenting avatar 910 and the digital representation of contact 912. In some examples, information can be presented a predetermined distance from HIPD 906 (e.g., within 5 meters). For example, as shown in first AR system 900, virtual object 914 is presented on the desk some distance from HIPD 906. Similar to the above example, HIPD 906 and AR glasses 904 can operate in conjunction to determine a location for presenting virtual object 914. Alternatively, In some examples, presentation of information is not bound by HIPD 906. More specifically, avatar 910, digital representation of contact 912, and virtual object 914 do not have to be presented within a predetermined distance of HIPD 906.

[0136] User inputs provided at wrist-wearable device 902, AR glasses 904, and/or HIPD 906 are coordinated such that the user can use any device to initiate, continue, and/or complete an operation. For example, user 908 can provide a user input to AR glasses 904 to cause AR glasses 904 to present virtual object 914 and, while virtual object 914 is presented by AR glasses 904, user 908 can provide one or more hand gestures via wrist-wearable device 902 to interact and/or manipulate virtual object 914.

[0137] FIG. 10 shows a user 1008 wearing a wrist-wearable device 1002 and AR glasses 1004, and holding an HIPD 1006. In second AR system 1000, the wrist-wearable device 1002, AR glasses 1004, and/or HIPD 1006 are used to receive and/or provide one or more messages to a contact of user 1008. In particular, wrist-wearable device 1002, AR glasses 1004, and/or HIPD 1006 detect and coordinate one or more user inputs to initiate a messaging application and prepare a response to a received message via the messaging application.

[0138] In some examples, user 1008 initiates, via a user input, an application on wristwearable device 1002, AR glasses 1004, and/or HIPD 1006 that causes the application to initiate on at least one device. For example, in second AR system 1000, user 1008 performs a hand gesture associated with a command for initiating a messaging application (represented by messaging user interface 1016), wrist-wearable device 1002 detects the hand gesture and, based on a determination that user 1008 is wearing AR glasses 1004, causes AR glasses 1004 to present a messaging user interface 1016 of the messaging application. AR glasses 1004 can present messaging user interface 1016 to user 1008 via its display (e.g., as shown by a field of view 1018 of user 1008). In some examples, the application is initiated and executed on the device (e.g., wrist-wearable device 1002, AR glasses 1004, and/or HIRD 1006) that detects the user input to initiate the application, and the device provides another device operational data to cause the presentation of the messaging application. For example, wrist-wearable device 1002 can detect the user input to initiate a messaging application, initiate and run the messaging application, and provide operational data to AR glasses 1004 and/or HIPD 1006 to cause presentation of the messaging application. Alternatively, the application can be initiated and executed at a device other than the device that detected the user input. For example, wrist-wearable device 1002 can detect the hand gesture associated with initiating the messaging application and cause HIPD 1006 to run the messaging application and coordinate the presentation of the messaging application.

[0139] Further, user 1008 can provide a user input provided at wrist-wearable device 1002, AR glasses 1004, and/or HIPD 1006 to continue and/or complete an operation initiated at another device. For example, after initiating the messaging application via wrist-wearable device 1002 and while AR glasses 1004 present messaging user interface 1016, user 1008 can provide an input at HIPD 1006 to prepare a response (e.g., shown by the swipe gesture performed on HIPD 1006). Gestures performed by user 1008 on HIPD 1006 can be provided and/or displayed on another device. For example, a swipe gestured performed on HIPD 1006 is displayed on a virtual keyboard of messaging user interface 1016 displayed by AR glasses 1004.

[0140] In some examples, wrist-wearable device 1002, AR glasses 1004, HIPD 1006, and/or any other communicatively coupled device can present one or more notifications to user 1008. The notification can be an indication of a new message, an incoming call, an application update, a status update, etc. User 1008 can select the notification via wrist-wearable device 1002, AR glasses 1004, and/or HIPD 1006 and can cause presentation of an application or operation associated with the notification on at least one device. For example, user 1008 can receive a notification that a message was received at wrist-wearable device 1002, AR glasses 1004, HIPD 1006, and/or any other communicatively coupled device and can then provide a user input at wrist-wearable device 1002, AR glasses 1004, and/or HIPD 1006 to review the notification, and the device detecting the user input can cause an application associated with the notification to be initiated and/or presented at wrist-wearable device 1002, AR glasses 1004, and/or HIPD 1006.

[0141] While the above example describes coordinated inputs used to interact with a messaging application, user inputs can be coordinated to interact with any number of applications including, but not limited to, gaming applications, social media applications, camera applications, web-based applications, financial applications, etc. For example, AR glasses 1004 can present to user 1008 game application data, and HIRD 1006 can be used as a controller to provide inputs to the game. Similarly, user 1008 can use wrist-wearable device 1002 to initiate a camera of AR glasses 1004, and user 1008 can use wrist-wearable device 1002, AR glasses 1004, and/or HIPD 1006 to manipulate the image capture (e.g., zoom in or out, apply filters, etc.) and capture image data.

[0142] Users may interact with the devices disclosed herein in a variety of ways. For example, as shown in FIGS. 1 1A and 11 B, a user 1 108 may interact with an AR system 1 100 by donning a VR headset 1 150 while holding HIPD 1 106 and wearing wrist-wearable device 1102. In this example, AR system 1 100 may enable a user to interact with a game 11 10 by swiping their arm. One or more of VR headset 1 150, HIPD 1106, and wrist-wearable device 1102 may detect this gesture and, in response, may display a sword strike in game 11 10. Similarly, in FIGS. 12A and 12B, a user 1208 may interact with an AR system 1200 by donning a VR headset 1220 while wearing haptic device 1260 and wrist-wearable device 1230. In this example, AR system 1200 may enable a user to interact with a game 1210 by swiping their arm. One or more of VR headset 1220, haptic device 1260, and wrist-wearable device 1230 may detect this gesture and, in response, may display a spell being cast in game 1 110.

[0143] Having discussed example AR systems, devices for interacting with such AR systems and other computing systems more generally will now be discussed in greater detail. Some explanations of devices and components that can be included in some or all of the example devices discussed below are explained herein for ease of reference. Certain types of the components described below may be more suitable for a particular set of devices, and less suitable for a different set of devices. But subsequent reference to the components explained here should be considered to be encompassed by the descriptions provided.

[0144] In some examples discussed below, example devices and systems, including electronic devices and systems, will be addressed. Such example devices and systems are not intended to be limiting, and one of skill in the art will understand that alternative devices and systems to the example devices and systems described herein may be used to perform the operations and construct the systems and devices that are described herein.

[0145] An electronic device may be a device that uses electrical energy to perform a specific function. An electronic device can be any physical object that contains electronic components such as transistors, resistors, capacitors, diodes, and integrated circuits. Examples of electronic devices include smartphones, laptops, digital cameras, televisions, gaming consoles, and music players, as well as the example electronic devices discussed herein. As described herein, an intermediary electronic device may be a device that sits between two other electronic devices and/or a subset of components of one or more electronic devices and facilitates communication, data processing, and/or data transfer between the respective electronic devices and/or electronic components.

[0146] An integrated circuit may be an electronic device made up of multiple interconnected electronic components such as transistors, resistors, and capacitors. These components may be etched onto a small piece of semiconductor material, such as silicon. Integrated circuits may include analog integrated circuits, digital integrated circuits, mixed signal integrated circuits, and/or any other suitable type or form of integrated circuit. Examples of integrated circuits include application-specific integrated circuits (ASICs), processing units, central processing units (CPUs), co-processors, and accelerators.

[0147] Analog integrated circuits, such as sensors, power management circuits, and operational amplifiers, may process continuous signals and perform analog functions such as amplification, active filtering, demodulation, and mixing. Examples of analog integrated circuits include linear integrated circuits and radio frequency circuits.

[0148] Digital integrated circuits, which may be referred to as logic integrated circuits, may include microprocessors, microcontrollers, memory chips, interfaces, power management circuits, programmable devices, and/or any other suitable type or form of integrated circuit. In some examples, examples of integrated circuits include central processing units (CPUs), [0149] Processing units, such as CPUs, may be electronic components that are responsible for executing instructions and controlling the operation of an electronic device (e.g., a computer). There are various types of processors that may be used interchangeably, or may be specifically required, by examples described herein. For example, a processor may be: (i) a general processor designed to perform a wide range of tasks, such as running software applications, managing operating systems, and performing arithmetic and logical operations; (ii) a microcontroller designed for specific tasks such as controlling electronic devices, sensors, and motors; (iii) an accelerator, such as a graphics processing unit (GPU), designed to accelerate the creation and rendering of images, videos, and animations (e.g., virtual-reality animations, such as three-dimensional modeling); (iv) a field-programmable gate array (FPGA) that can be programmed and reconfigured after manufacturing and/or can be customized to perform specific tasks, such as signal processing, cryptography, and machine learning; and/or (v) a digital signal processor (DSP) designed to perform mathematical operations on signals such as audio, video, and radio waves. One or more processors of one or more electronic devices may be used in various examples described herein.

[0150] Memory generally refers to electronic components in a computer or electronic device that store data and instructions for the processor to access and manipulate. Examples of memory can include: (i) random access memory (RAM) configured to store data and instructions temporarily; (ii) read-only memory (ROM) configured to store data and instructions permanently (e.g., one or more portions of system firmware, and/or boot loaders) and/or semi-permanently; (iii) flash memory, which can be configured to store data in electronic devices (e.g., USB drives, memory cards, and/or solid-state drives (SSDs)); and/or (iv) cache memory configured to temporarily store frequently accessed data and instructions. Memory, as described herein, can store structured data (e.g., SQL databases, MongoDB databases, GraphQL data, JSON data, etc.). Other examples of data stored in memory can include (i) profile data, including user account data, user settings, and/or other user data stored by the user, (ii) sensor data detected and/or otherwise obtained by one or more sensors, (iii) media content data including stored image data, audio data, documents, and the like, (iv) application data, which can include data collected and/or otherwise obtained and stored during use of an application, and/or any other types of data described herein.

[0151] Controllers may be electronic components that manage and coordinate the operation of other components within an electronic device (e.g., controlling inputs, processing data, and/or generating outputs). Examples of controllers can include: (i) microcontrollers, including small, low-power controllers that are commonly used in embedded systems and Internet of Things (loT) devices; (ii) programmable logic controllers (PLCs) that may be configured to be used in industrial automation systems to control and monitor manufacturing processes; (iii) system-on-a-chip (SoC) controllers that integrate multiple components such as processors, memory, I/O interfaces, and other peripherals into a single chip; and/or (iv) DSPs.

[0152] A power system of an electronic device may be configured to convert incoming electrical power into a form that can be used to operate the device. A power system can include various components, such as (i) a power source, which can be an alternating current (AC) adapter or a direct current (DC) adapter power supply, (ii) a charger input, which can be configured to use a wired and/or wireless connection (which may be part of a peripheral interface, such as a USB, micro-USB interface, near-field magnetic coupling, magnetic inductive and magnetic resonance charging, and/or radio frequency (RF) charging), (iii) a power-management integrated circuit, configured to distribute power to various components of the device and to ensure that the device operates within safe limits (e.g., regulating voltage, controlling current flow, and/or managing heat dissipation), and/or (iv) a battery configured to store power to provide usable power to components of one or more electronic devices.

[0153] Peripheral interfaces may be electronic components (e.g., of electronic devices) that allow electronic devices to communicate with other devices or peripherals and can provide the ability to input and output data and signals. Examples of peripheral interfaces can include (i) universal serial bus (USB) and/or micro-USB interfaces configured for connecting devices to an electronic device, (ii) Bluetooth interfaces configured to allow devices to communicate with each other, including Bluetooth low energy (BLE), (iii) near field communication (NFC) interfaces configured to be short-range wireless interfaces for operations such as access control, (iv) POGO pins, which may be small, spring-loaded pins configured to provide a charging interface, (v) wireless charging interfaces, (vi) GPS interfaces, (vii) Wi-Fi interfaces for providing a connection between a device and a wireless network, and/or (viii) sensor interfaces.

[0154] Sensors may be electronic components (e.g., in and/or otherwise in electronic communication with electronic devices, such as wearable devices) configured to detect physical and environmental changes and generate electrical signals. Examples of sensors can include (i) imaging sensors for collecting imaging data (e.g., including one or more cameras disposed on a respective electronic device), (ii) biopotential-signal sensors, (iii) inertial measurement units (e.g., IMUs) for detecting, for example, angular rate, force, magnetic field, and/or changes in acceleration, (iv) heart rate sensors for measuring a user’s heart rate, (v) SpO2 sensors for measuring blood oxygen saturation and/or other biometric data of a user, (vi) capacitive sensors for detecting changes in potential at a portion of a user’s body (e.g., a sensor-skin interface), and/or (vii) light sensors (e.g., time-of-flight sensors, infrared light sensors, visible light sensors, etc.).

[0155] Biopotential-signal-sensing components may be devices used to measure electrical activity within the body (e.g., biopotential-signal sensors). Some types of biopotential-signal sensors include (i) electroencephalography (EEG) sensors configured to measure electrical activity in the brain to diagnose neurological disorders, (ii) electrocardiography (ECG or EKG) sensors configured to measure electrical activity of the heart to diagnose heart problems, (iii) electromyography (EMG) sensors configured to measure the electrical activity of muscles and to diagnose neuromuscular disorders, and (iv) electrooculography (EOG) sensors configure to measure the electrical activity of eye muscles to detect eye movement and diagnose eye disorders.

[0156] An application stored in memory of an electronic device (e.g., software) may include instructions stored in the memory. Examples of such applications include (i) games, (ii) word processors, (iii) messaging applications, (iv) media-streaming applications, (v) financial applications, (vi) calendars, (vii) clocks, and (viii) communication interface modules for enabling wired and/or wireless connections between different respective electronic devices (e.g., IEEE 1502.15.4, Wi-Fi, ZigBee, 6L0WPAN, Thread, Z-Wave, Bluetooth Smart, ISA100.11 a, WirelessHART, or MiWi), custom or standard wired protocols (e.g., Ethernet or HomePlug), and/or any other suitable communication protocols).

[0157] A communication interface may be a mechanism that enables different systems or devices to exchange information and data with each other, including hardware, software, or a combination of both hardware and software. For example, a communication interface can refer to a physical connector and/or port on a device that enables communication with other devices (e.g., USB, Ethernet, HDMI, Bluetooth). In some examples, a communication interface can refer to a software layer that enables different software programs to communicate with each other (e.g., application programming interfaces (APIs), protocols like HTTP and TCP/IP, etc.). [0158] A graphics module may be a component or software module that is designed to handle graphical operations and/or processes and can include a hardware module and/or a software module.

[0159] Non-transitory computer-readable storage media may be physical devices or storage media that can be used to store electronic data in a non-transitory form (e.g., such that the data is stored permanently until it is intentionally deleted or modified).

[0160] FIGS. 13 and 14 illustrate an example wrist-wearable device 1300 and an example computer system 1400. Wrist-wearable device 1300 is an instance of wearable device 902 described in FIG. 9 herein, such that the wearable device 902 should be understood to have the features of the wrist-wearable device 1300 and vice versa. FIG. 14 illustrates components of the wrist-wearable device 1300, which can be used individually or in combination, including combinations that include other electronic devices and/or electronic components.

[0161] FIG. 13 shows a wearable band 1310 and a watch body 1320 (or capsule) being coupled, as discussed below, to form wrist-wearable device 1300. Wrist-wearable device 1300 can perform various functions and/or operations associated with navigating through user interfaces and selectively opening applications as well as the functions and/or operations described above with reference to FIGS. 9-12B.

[0162] As will be described in more detail below, operations executed by wrist-wearable device 1300 can include (i) presenting content to a user (e.g., displaying visual content via a display 1305), (ii) detecting (e.g., sensing) user input (e.g., sensing a touch on peripheral button 1323 and/or at a touch screen of the display 1305, a hand gesture detected by sensors (e.g., biopotential sensors)), (iii) sensing biometric data (e.g., neuromuscular signals, heart rate, temperature, sleep, etc.) via one or more sensors 1313, messaging (e.g., text, speech, video, etc.); image capture via one or more imaging devices or cameras 1325, wireless communications (e.g., cellular, near field, Wi-Fi, personal area network, etc.), location determination, financial transactions, providing haptic feedback, providing alarms, providing notifications, providing biometric authentication, providing health monitoring, providing sleep monitoring, etc.

[0163] The above-example functions can be executed independently in watch body 1320, independently in wearable band 1310, and/or via an electronic communication between watch body 1320 and wearable band 1310. In some examples, functions can be executed on wrist- wearable device 1300 while an AR environment is being presented (e.g., via one of AR systems 900 to 1200). The wearable devices described herein can also be used with other types of AR environments.

[0164] Wearable band 1310 can be configured to be worn by a user such that an inner surface of a wearable structure 131 1 of wearable band 1310 is in contact with the user’s skin. In this example, when worn by a user, sensors 1313 may contact the user’s skin. In some examples, one or more of sensors 1313 can sense biometric data such as a user’s heart rate, a saturated oxygen level, temperature, sweat level, neuromuscular signals, or a combination thereof. One or more of sensors 1313 can also sense data about a user’s environment including a user’s motion, altitude, location, orientation, gait, acceleration, position, or a combination thereof. In some examples, one or more of sensors 1313 can be configured to track a position and/or motion of wearable band 1310. One or more of sensors 1313 can include any of the sensors defined above and/or discussed below with respect to FIG. 13.

[0165] One or more of sensors 1313 can be distributed on an inside and/or an outside surface of wearable band 1310. In some examples, one or more of sensors 1313 are uniformly spaced along wearable band 1310. Alternatively, In some examples, one or more of sensors 1313 are positioned at distinct points along wearable band 1310. As shown in FIG. 13, one or more of sensors 1313 can be the same or distinct. For example, In some examples, one or more of sensors 1313 can be shaped as a pill (e.g., sensor 1313a), an oval, a circle a square, an oblong (e.g., sensor 1313c) and/or any other shape that maintains contact with the user’s skin (e.g., such that neuromuscular signal and/or other biometric data can be accurately measured at the user’s skin). In some examples, one or more sensors of 1313 are aligned to form pairs of sensors (e.g., for sensing neuromuscular signals based on differential sensing within each respective sensor). For example, sensor 1313b may be aligned with an adjacent sensor to form sensor pair 1314a and sensor 1313d may be aligned with an adjacent sensor to form sensor pair 1314b. In some examples, wearable band 1310 does not have a sensor pair. Alternatively, In some examples, wearable band 1310 has a predetermined number of sensor pairs (one pair of sensors, three pairs of sensors, four pairs of sensors, six pairs of sensors, sixteen pairs of sensors, etc.).

[0166] Wearable band 1310 can include any suitable number of sensors 1313. In some examples, the number and arrangement of sensors 1313 depends on the particular application for which wearable band 1310 is used. For instance, wearable band 1310 can be configured as an armband, wristband, or chest-band that include a plurality of sensors 1313 with different number of sensors 1313, a variety of types of individual sensors with the plurality of sensors 1313, and different arrangements for each use case, such as medical use cases as compared to gaming or general day-to-day use cases. [0167] In accordance with some examples, wearable band 1310 further includes an electrical ground electrode and a shielding electrode. The electrical ground and shielding electrodes, like the sensors 1313, can be distributed on the inside surface of the wearable band 1310 such that they contact a portion of the user’s skin. For example, the electrical ground and shielding electrodes can be at an inside surface of a coupling mechanism 1316 or an inside surface of a wearable structure 1311. The electrical ground and shielding electrodes can be formed and/or use the same components as sensors 1313. In some examples, wearable band

1310 includes more than one electrical ground electrode and more than one shielding electrode.

[0168] Sensors 1313 can be formed as part of wearable structure 131 1 of wearable band 1310. In some examples, sensors 1313 are flush or substantially flush with wearable structure

1311 such that they do not extend beyond the surface of wearable structure 131 1. While flush with wearable structure 131 1 , sensors 1313 are still configured to contact the user’s skin (e.g., via a skin-contacting surface). Alternatively, In some examples, sensors 1313 extend beyond wearable structure 131 1 a predetermined distance (e.g., 0.1 - 2 mm) to make contact and depress into the user’s skin. In some examples, sensors 1313 are coupled to an actuator (not shown) configured to adjust an extension height (e.g., a distance from the surface of wearable structure 1311) of sensors 1313 such that sensors 1313 make contact and depress into the user’s skin. In some examples, the actuators adjust the extension height between 0.01 mm - 1.2 mm. This may allow a the user to customize the positioning of sensors 1313 to improve the overall comfort of the wearable band 1310 when worn while still allowing sensors 1313 to contact the user’s skin. In some examples, sensors 1313 are indistinguishable from wearable structure 1311 when worn by the user.

[0169] Wearable structure 1311 can be formed of an elastic material, elastomers, etc., configured to be stretched and fitted to be worn by the user. In some examples, wearable structure 1311 is a textile or woven fabric. As described above, sensors 1313 can be formed as part of a wearable structure 1311. For example, sensors 1313 can be molded into the wearable structure 131 1 , be integrated into a woven fabric (e.g., sensors 1313 can be sewn into the fabric and mimic the pliability of fabric and can and/or be constructed from a series woven strands of fabric).

[0170] Wearable structure 131 1 can include flexible electronic connectors that interconnect sensors 1313, the electronic circuitry, and/or other electronic components (described below in reference to FIG. 14) that are enclosed in wearable band 1310. In some examples, the flexible electronic connectors are configured to interconnect sensors 1313, the electronic circuitry, and/or other electronic components of wearable band 1310 with respective sensors and/or other electronic components of another electronic device (e.g., watch body 1320). The flexible electronic connectors are configured to move with wearable structure 131 1 such that the user adjustment to wearable structure 131 1 (e.g., resizing, pulling, folding, etc.) does not stress or strain the electrical coupling of components of wearable band 1310.

[0171] As described above, wearable band 1310 is configured to be worn by a user. In particular, wearable band 1310 can be shaped or otherwise manipulated to be worn by a user. For example, wearable band 1310 can be shaped to have a substantially circular shape such that it can be configured to be worn on the user’s lower arm or wrist. Alternatively, wearable band 1310 can be shaped to be worn on another body part of the user, such as the user’s upper arm (e.g., around a bicep), forearm, chest, legs, etc. Wearable band 1310 can include a retaining mechanism 1312 (e.g., a buckle, a hook and loop fastener, etc.) for securing wearable band 1310 to the user’s wrist or other body part. While wearable band 1310 is worn by the user, sensors 1313 sense data (referred to as sensor data) from the user’s skin. In some examples, sensors 1313 of wearable band 1310 obtain (e.g., sense and record) neuromuscular signals.

[0172] The sensed data (e.g., sensed neuromuscular signals) can be used to detect and/or determine the user’s intention to perform certain motor actions. In some examples, sensors 1313 may sense and record neuromuscular signals from the user as the user performs muscular activations (e.g., movements, gestures, etc.). The detected and/or determined motor actions (e.g., phalange (or digit) movements, wrist movements, hand movements, and/or other muscle intentions) can be used to determine control commands or control information (instructions to perform certain commands after the data is sensed) for causing a computing device to perform one or more input commands. For example, the sensed neuromuscular signals can be used to control certain user interfaces displayed on display 1305 of wristwearable device 1300 and/or can be transmitted to a device responsible for rendering an artificial-reality environment (e.g., a head-mounted display) to perform an action in an associated artificial-reality environment, such as to control the motion of a virtual device displayed to the user. The muscular activations performed by the user can include static gestures, such as placing the user’s hand palm down on a table, dynamic gestures, such as grasping a physical or virtual object, and covert gestures that are imperceptible to another person, such as slightly tensing a joint by co-contracting opposing muscles or using sub- muscular activations. The muscular activations performed by the user can include symbolic gestures (e.g., gestures mapped to other gestures, interactions, or commands, for example, based on a gesture vocabulary that specifies the mapping of gestures to commands).

[0173] The sensor data sensed by sensors 1313 can be used to provide a user with an enhanced interaction with a physical object (e.g., devices communicatively coupled with wearable band 1310) and/or a virtual object in an artificial-reality application generated by an artificial-reality system (e.g., user interface objects presented on the display 1305, or another computing device (e.g., a smartphone)).

[0174] In some examples, wearable band 1310 includes one or more haptic devices 1446 (e.g., a vibratory haptic actuator) that are configured to provide haptic feedback (e.g., a cutaneous and/or kinesthetic sensation, etc.) to the user’s skin. Sensors 1313 and/or haptic devices 1446 (shown in FIG. 14) can be configured to operate in conjunction with multiple applications including, without limitation, health monitoring, social media, games, and artificial reality (e.g., the applications associated with artificial reality).

[0175] Wearable band 1310 can also include coupling mechanism 1316 for detachably coupling a capsule (e.g., a computing unit) or watch body 1320 (via a coupling surface of the watch body 1320) to wearable band 1310. For example, a cradle or a shape of coupling mechanism 1316 can correspond to shape of watch body 1320 of wrist-wearable device 1300. In particular, coupling mechanism 1316 can be configured to receive a coupling surface proximate to the bottom side of watch body 1320 (e.g., a side opposite to a front side of watch body 1320 where display 1305 is located), such that a user can push watch body 1320 downward into coupling mechanism 1316 to attach watch body 1320 to coupling mechanism 1316. In some examples, coupling mechanism 1316 can be configured to receive a top side of the watch body 1320 (e.g., a side proximate to the front side of watch body 1320 where display 1305 is located) that is pushed upward into the cradle, as opposed to being pushed downward into coupling mechanism 1316. In some examples, coupling mechanism 1316 is an integrated component of wearable band 1310 such that wearable band 1310 and coupling mechanism 1316 are a single unitary structure. In some examples, coupling mechanism 1316 is a type of frame or shell that allows watch body 1320 coupling surface to be retained within or on wearable band 1310 coupling mechanism 1316 (e.g., a cradle, a tracker band, a support base, a clasp, etc.).

[0176] Coupling mechanism 1316 can allow for watch body 1320 to be detachably coupled to the wearable band 1310 through a friction fit, magnetic coupling, a rotation-based connector, a shear-pin coupler, a retention spring, one or more magnets, a clip, a pin shaft, a hook and loop fastener, or a combination thereof. A user can perform any type of motion to couple the watch body 1320 to wearable band 1310 and to decouple the watch body 1320 from the wearable band 1310. For example, a user can twist, slide, turn, push, pull, or rotate watch body 1320 relative to wearable band 1310, or a combination thereof, to attach watch body 1320 to wearable band 1310 and to detach watch body 1320 from wearable band 1310. Alternatively, as discussed below, In some examples, the watch body 1320 can be decoupled from the wearable band 1310 by actuation of a release mechanism 1329.

[0177] Wearable band 1310 can be coupled with watch body 1320 to increase the functionality of wearable band 1310 (e.g., converting wearable band 1310 into wrist-wearable device 1300, adding an additional computing unit and/or battery to increase computational resources and/or a battery life of wearable band 1310, adding additional sensors to improve sensed data, etc.). As described above, wearable band 1310 and coupling mechanism 1316 are configured to operate independently (e.g., execute functions independently) from watch body 1320. For example, coupling mechanism 1316 can include one or more sensors 1313 that contact a user’s skin when wearable band 1310 is worn by the user, with or without watch body 1320 and can provide sensor data for determining control commands.

[0178] A user can detach watch body 1320 from wearable band 1310 to reduce the encumbrance of wrist-wearable device 1300 to the user. For examples in which watch body 1320 is removable, watch body 1320 can be referred to as a removable structure, such that in these examples wrist-wearable device 1300 includes a wearable portion (e.g., wearable band 1310) and a removable structure (e.g., watch body 1320).

[0179] Turning to watch body 1320, in some examples watch body 1320 can have a substantially rectangular or circular shape. Watch body 1320 is configured to be worn by the user on their wrist or on another body part. More specifically, watch body 1320 is sized to be easily carried by the user, attached on a portion of the user’s clothing, and/or coupled to wearable band 1310 (forming the wrist-wearable device 1300). As described above, watch body 1320 can have a shape corresponding to coupling mechanism 1316 of wearable band 1310. In some examples, watch body 1320 includes a single release mechanism 1329 or multiple release mechanisms (e.g., two release mechanisms 1329 positioned on opposing sides of watch body 1320, such as spring-loaded buttons) for decoupling watch body 1320 from wearable band 1310. Release mechanism 1329 can include, without limitation, a button, a knob, a plunger, a handle, a lever, a fastener, a clasp, a dial, a latch, or a combination thereof.

[0180] A user can actuate release mechanism 1329 by pushing, turning, lifting, depressing, shifting, or performing other actions on release mechanism 1329. Actuation of release mechanism 1329 can release (e.g., decouple) watch body 1320 from coupling mechanism 1316 of wearable band 1310, allowing the user to use watch body 1320 independently from wearable band 1310 and vice versa. For example, decoupling watch body 1320 from wearable band 1310 can allow a user to capture images using rear-facing camera 1325b. Although release mechanism 1329 is shown positioned at a corner of watch body 1320, release mechanism 1329 can be positioned anywhere on watch body 1320 that is convenient for the user to actuate. In addition, In some examples, wearable band 1310 can also include a respective release mechanism for decoupling watch body 1320 from coupling mechanism 1316. In some examples, release mechanism 1329 is optional and watch body 1320 can be decoupled from coupling mechanism 1316 as described above (e.g., via twisting, rotating, etc.).

[0181] Watch body 1320 can include one or more peripheral buttons 1323 and 1327 for performing various operations at watch body 1320. For example, peripheral buttons 1323 and 1327 can be used to turn on or wake (e.g., transition from a sleep state to an active state) display 1305, unlock watch body 1320, increase or decrease a volume, increase or decrease a brightness, interact with one or more applications, interact with one or more user interfaces, etc. Additionally or alternatively, In some examples, display 1305 operates as a touch screen and allows the user to provide one or more inputs for interacting with watch body 1320.

[0182] In some examples, watch body 1320 includes one or more sensors 1321. Sensors 1321 of watch body 1320 can be the same or distinct from sensors 1313 of wearable band 1310. Sensors 1321 of watch body 1320 can be distributed on an inside and/or an outside surface of watch body 1320. In some examples, sensors 1321 are configured to contact a user’s skin when watch body 1320 is worn by the user. For example, sensors 1321 can be placed on the bottom side of watch body 1320 and coupling mechanism 1316 can be a cradle with an opening that allows the bottom side of watch body 1320 to directly contact the user’s skin. Alternatively, In some examples, watch body 1320 does not include sensors that are configured to contact the user’s skin (e.g., including sensors internal and/or external to the watch body 1320 that are configured to sense data of watch body 1320 and the surrounding environment). In some examples, sensors 1321 are configured to track a position and/or motion of watch body 1320.

[0183] Watch body 1320 and wearable band 1310 can share data using a wired communication method (e.g., a Universal Asynchronous Receiver/Transmitter (UART), a USB transceiver, etc.) and/or a wireless communication method (e.g., near field communication, Bluetooth, etc.). For example, watch body 1320 and wearable band 1310 can share data sensed by sensors 1313 and 1321 , as well as application and device specific information (e.g., active and/or available applications, output devices (e.g., displays, speakers, etc.), input devices (e.g., touch screens, microphones, imaging sensors, etc.).

[0184] In some examples, watch body 1320 can include, without limitation, a front-facing camera 1325a and/or a rear-facing camera 1325b, sensors 1321 (e.g., a biometric sensor, an IMU, a heart rate sensor, a saturated oxygen sensor, a neuromuscular signal sensor, an altimeter sensor, a temperature sensor, a bioimpedance sensor, a pedometer sensor, an optical sensor (e.g., imaging sensor 1463), a touch sensor, a sweat sensor, etc.). In some examples, watch body 1320 can include one or more haptic devices 1476 (e.g., a vibratory haptic actuator) that is configured to provide haptic feedback (e.g., a cutaneous and/or kinesthetic sensation, etc.) to the user. Sensors 1421 and/or haptic device 1476 can also be configured to operate in conjunction with multiple applications including, without limitation, health monitoring applications, social media applications, game applications, and artificial reality applications (e.g., the applications associated with artificial reality).

[0185] As described above, watch body 1320 and wearable band 1310, when coupled, can form wrist-wearable device 1300. When coupled, watch body 1320 and wearable band 1310 may operate as a single device to execute functions (operations, detections, communications, etc.) described herein. In some examples, each device may be provided with particular instructions for performing the one or more operations of wrist-wearable device 1300. For example, in accordance with a determination that watch body 1320 does not include neuromuscular signal sensors, wearable band 1310 can include alternative instructions for performing associated instructions (e.g., providing sensed neuromuscular signal data to watch body 1320 via a different electronic device). Operations of wrist-wearable device 1300 can be performed by watch body 1320 alone or in conjunction with wearable band 1310 (e.g., via respective processors and/or hardware components) and vice versa. In some examples, operations of wrist-wearable device 1300, watch body 1320, and/or wearable band 1310 can be performed in conjunction with one or more processors and/or hardware components.

[0186] As described below with reference to the block diagram of FIG. 14, wearable band 1310 and/or watch body 1320 can each include independent resources required to independently execute functions. For example, wearable band 1310 and/or watch body 1320 can each include a power source (e.g., a battery), a memory, data storage, a processor (e.g., a central processing unit (CPU)), communications, a light source, and/or input/output devices. [0187] FIG. 14 shows block diagrams of a computing system 1430 corresponding to wearable band 1310 and a computing system 1460 corresponding to watch body 1320. Computing system 1400 of wrist-wearable device 1300 may include a combination of components of wearable band computing system 1430 and watch body computing system 1460.

[0188] Watch body 1320 and/or wearable band 1310 can include one or more components shown in watch body computing system 1460. In some examples, a single integrated circuit may include all or a substantial portion of the components of watch body computing system 1460 included in a single integrated circuit. Alternatively, In some examples, components of the watch body computing system 1460 may be included in a plurality of integrated circuits that are communicatively coupled. In some examples, watch body computing system 1460 may be configured to couple (e.g., via a wired or wireless connection) with wearable band computing system 1430, which may allow the computing systems to share components, distribute tasks, and/or perform other operations described herein (individually or as a single device).

[0189] Watch body computing system 1460 can include one or more processors 1479, a controller 1477, a peripherals interface 1461 , a power system 1495, and memory (e.g., a memory 1480).

[0190] Power system 1495 can include a charger input 1496, a power-management integrated circuit (PMIC) 1497, and a battery 1498. In some examples, a watch body 1320 and a wearable band 1310 can have respective batteries (e.g., battery 1498 and 1459) and can share power with each other. Watch body 1320 and wearable band 1310 can receive a charge using a variety of techniques. In some examples, watch body 1320 and wearable band 1310 can use a wired charging assembly (e.g., power cords) to receive the charge. Alternatively, or in addition, watch body 1320 and/or wearable band 1310 can be configured for wireless charging. For example, a portable charging device can be designed to mate with a portion of watch body 1320 and/or wearable band 1310 and wirelessly deliver usable power to battery 1498 of watch body 1320 and/or battery 1459 of wearable band 1310. Watch body 1320 and wearable band 1310 can have independent power systems (e.g., power system 1495 and 1456, respectively) to enable each to operate independently. Watch body 1320 and wearable band 1310 can also share power (e.g., one can charge the other) via respective PMICs (e.g., PMICs 1497 and 1458) and charger inputs (e.g., 1457 and 1496) that can share power over power and ground conductors and/or over wireless charging antennas.

[0191] In some examples, peripherals interface 1461 can include one or more sensors 1421. Sensors 1421 can include one or more coupling sensors 1462 for detecting when watch body 1320 is coupled with another electronic device (e.g., a wearable band 1310). Sensors 1421 can include one or more imaging sensors 1463 (e.g., one or more of cameras 1425, and/or separate imaging sensors 1463 (e.g., thermal-imaging sensors)). In some examples, sensors 1421 can include one or more SpO2 sensors 1464. In some examples, sensors 1421 can include one or more biopotential-signal sensors (e.g., EMG sensors 1465, which may be disposed on an interior, user-facing portion of watch body 1320 and/or wearable band 1310). In some examples, sensors 1421 may include one or more capacitive sensors 1466. In some examples, sensors 1421 may include one or more heart rate sensors 1467. In some examples, sensors 1421 may include one or more IMU sensors 1468. In some examples, one or more IMU sensors 1468 can be configured to detect movement of a user’s hand or other location where watch body 1320 is placed or held.

[0192] In some examples, one or more of sensors 1421 may provide an example humanmachine interface. For example, a set of neuromuscular sensors, such as EMG sensors 1465, may be arranged circumferentially around wearable band 1310 with an interior surface of EMG sensors 1465 being configured to contact a user’s skin. Any suitable number of neuromuscular sensors may be used (e.g., between 2 and 20 sensors). The number and arrangement of neuromuscular sensors may depend on the particular application for which the wearable device is used. For example, wearable band 1310 can be used to generate control information for controlling an augmented reality system, a robot, controlling a vehicle, scrolling through text, controlling a virtual avatar, or any other suitable control task.

[0193] In some examples, neuromuscular sensors may be coupled together using flexible electronics incorporated into the wireless device, and the output of one or more of the sensing components can be optionally processed using hardware signal processing circuitry (e.g., to perform amplification, filtering, and/or rectification). In other examples, at least some signal processing of the output of the sensing components can be performed in software such as processors 1479. Thus, signal processing of signals sampled by the sensors can be performed in hardware, software, or by any suitable combination of hardware and software, as aspects of the technology described herein are not limited in this respect.

[0194] Neuromuscular signals may be processed in a variety of ways. For example, the output of EMG sensors 1465 may be provided to an analog front end, which may be configured to perform analog processing (e.g., amplification, noise reduction, filtering, etc.) on the recorded signals. The processed analog signals may then be provided to an analog-to-digital converter, which may convert the analog signals to digital signals that can be processed by one or more computer processors. Furthermore, although this example is as discussed in the context of interfaces with EMG sensors, the embodiments and examples described herein can also be implemented in wearable interfaces with other types of sensors including, but not limited to, mechanomyography (MMG) sensors, sonomyography (SMG) sensors, and electrical impedance tomography (EIT) sensors.

[0195] In some examples, peripherals interface 1461 includes a near-field communication (NFC) component 1469, a global-position system (GPS) component 1470, a long-term evolution (LTE) component 1471 , and/or a Wi-Fi and/or Bluetooth communication component 1472. In some examples, peripherals interface 1461 includes one or more buttons 1473 (e.g., peripheral buttons 1323 and 1327 in FIG. 13), which, when selected by a user, cause operation to be performed at watch body 1320. In some examples, the peripherals interface 1461 includes one or more indicators, such as a light emitting diode (LED), to provide a user with visual indicators (e.g., message received, low battery, active microphone and/or camera, etc.).

[0196] Watch body 1320 can include at least one display 1305 for displaying visual representations of information or data to a user, including user-interface elements and/or three-dimensional virtual objects. The display can also include a touch screen for inputting user inputs, such as touch gestures, swipe gestures, and the like. Watch body 1320 can include at least one speaker 1474 and at least one microphone 1475 for providing audio signals to the user and receiving audio input from the user. The user can provide user inputs through microphone 1475 and can also receive audio output from speaker 1474 as part of a haptic event provided by haptic controller 1478. Watch body 1320 can include at least one camera 1425, including a front camera 1425a and a rear camera 1425b. Cameras 1425 can include ultra-wide-angle cameras, wide angle cameras, fish-eye cameras, spherical cameras, telephoto cameras, depth-sensing cameras, or other types of cameras.

[0197] Watch body computing system 1460 can include one or more haptic controllers 1478 and associated componentry (e.g., haptic devices 1476) for providing haptic events at watch body 1320 (e.g., a vibrating sensation or audio output in response to an event at the watch body 1320). Haptic controllers 1478 can communicate with one or more haptic devices 1476, such as electroacoustic devices, including a speaker of the one or more speakers 1474 and/or other audio components and/or electromechanical devices that convert energy into linear motion such as a motor, solenoid, electroactive polymer, piezoelectric actuator, electrostatic actuator, or other tactile output generating components (e.g., a component that converts electrical signals into tactile outputs on the device). Haptic controller 1478 can provide haptic events to that are capable of being sensed by a user of watch body 1320. In some examples, one or more haptic controllers 1478 can receive input signals from an application of applications 1482.

[0198] In some examples, wearable band computing system 1430 and/or watch body computing system 1460 can include memory 1480, which can be controlled by one or more memory controllers of controllers 1477. In some examples, software components stored in memory 1480 include one or more applications 1482 configured to perform operations at the watch body 1320. In some examples, one or more applications 1482 may include games, word processors, messaging applications, calling applications, web browsers, social media applications, media streaming applications, financial applications, calendars, clocks, etc. In some examples, software components stored in memory 1480 include one or more communication interface modules 1483 as defined above. In some examples, software components stored in memory 1480 include one or more graphics modules 1484 for rendering, encoding, and/or decoding audio and/or visual data and one or more data management modules 1485 for collecting, organizing, and/or providing access to data 1487 stored in memory 1480. In some examples, one or more of applications 1482 and/or one or more modules can work in conjunction with one another to perform various tasks at the watch body 1320.

[0199] In some examples, software components stored in memory 1480 can include one or more operating systems 1481 (e.g., a Linux-based operating system, an Android operating system, etc.). Memory 1480 can also include data 1487. Data 1487 can include profile data 1488A, sensor data 1489A, media content data 1490, and application data 1491. [0200] It should be appreciated that watch body computing system 1460 is an example of a computing system within watch body 1320, and that watch body 1320 can have more or fewer components than shown in watch body computing system 1460, can combine two or more components, and/or can have a different configuration and/or arrangement of the components. The various components shown in watch body computing system 1460 are implemented in hardware, software, firmware, or a combination thereof, including one or more signal processing and/or application-specific integrated circuits.

[0201] Turning to the wearable band computing system 1430, one or more components that can be included in wearable band 1310 are shown. Wearable band computing system 1430 can include more or fewer components than shown in watch body computing system 1460, can combine two or more components, and/or can have a different configuration and/or arrangement of some or all of the components. In some examples, all, or a substantial portion of the components of wearable band computing system 1430 are included in a single integrated circuit. Alternatively, In some examples, components of wearable band computing system 1430 are included in a plurality of integrated circuits that are communicatively coupled. As described above, In some examples, wearable band computing system 1430 is configured to couple (e.g., via a wired or wireless connection) with watch body computing system 1460, which allows the computing systems to share components, distribute tasks, and/or perform other operations described herein (individually or as a single device).

[0202] Wearable band computing system 1430, similar to watch body computing system 1460, can include one or more processors 1449, one or more controllers 1447 (including one or more haptics controllers 1448), a peripherals interface 1431 that can includes one or more sensors 1413 and other peripheral devices, a power source (e.g., a power system 1456), and memory (e.g., a memory 1450) that includes an operating system (e.g., an operating system 1451), data (e.g., data 1454 including profile data 1488B, sensor data 1489B, etc.), and one or more modules (e.g., a communications interface module 1452, a data management module 1453, etc.).

[0203] One or more of sensors 1413 can be analogous to sensors 1421 of watch body computing system 1460. For example, sensors 1413 can include one or more coupling sensors 1432, one or more SpO2 sensors 1434, one or more EMG sensors 1435, one or more capacitive sensors 1436, one or more heart rate sensors 1437, and one or more IMU sensors 1438.

[0204] Peripherals interface 1431 can also include other components analogous to those included in peripherals interface 1461 of watch body computing system 1460, including an NFC component 1439, a GPS component 1440, an LTE component 1441 , a Wi-Fi and/or Bluetooth communication component 1442, and/or one or more haptic devices 1446 as described above in reference to peripherals interface 1461. In some examples, peripherals interface 1431 includes one or more buttons 1443, a display 1433, a speaker 1444, a microphone 1445, and a camera 1455. In some examples, peripherals interface 1431 includes one or more indicators, such as an LED.

[0205] It should be appreciated that wearable band computing system 1430 is an example of a computing system within wearable band 1310, and that wearable band 1310 can have more or fewer components than shown in wearable band computing system 1430, combine two or more components, and/or have a different configuration and/or arrangement of the components. The various components shown in wearable band computing system 1430 can be implemented in one or more of a combination of hardware, software, or firmware, including one or more signal processing and/or application-specific integrated circuits.

[0206] Wrist-wearable device 1300 with respect to FIG. 13 is an example of wearable band 1310 and watch body 1320 coupled together, so wrist-wearable device 1300 will be understood to include the components shown and described for wearable band computing system 1430 and watch body computing system 1460. In some examples, wrist-wearable device 1300 has a split architecture (e.g., a split mechanical architecture, a split electrical architecture, etc.) between watch body 1320 and wearable band 1310. In other words, all of the components shown in wearable band computing system 1430 and watch body computing system 1460 can be housed or otherwise disposed in a combined wrist-wearable device 1300 or within individual components of watch body 1320, wearable band 1310, and/or portions thereof (e.g., a coupling mechanism 1316 of wearable band 1310).

[0207] The techniques described above can be used with any device for sensing neuromuscular signals but could also be used with other types of wearable devices for sensing neuromuscular signals (such as body-wearable or head-wearable devices that might have neuromuscular sensors closer to the brain or spinal column).

[0208] In some examples, wrist-wearable device 1300 can be used in conjunction with a headwearable device (e.g., AR glasses 1500 and VR system 1610) and/or an HIRD, and wristwearable device 1300 can also be configured to be used to allow a user to control any aspect of the artificial reality (e.g., by using EMG-based gestures to control user interface objects in the artificial reality and/or by allowing a user to interact with the touchscreen on the wristwearable device to also control aspects of the artificial reality). Having thus described example wrist-wearable devices, attention will now be turned to example head-wearable devices, such AR glasses 1500 and VR headset 1610.

[0209] FIGS. 15 to 17 show example artificial-reality systems, which can be used as or in connection with wrist-wearable device 1300. In some examples, AR system 1500 includes an eyewear device 1502, as shown in FIG. 15. In some examples, VR system 1610 includes a head-mounted display (HMD) 1612, as shown in FIGS. 16A and 16B. In some examples, AR system 1500 and VR system 1610 can include one or more analogous components (e.g., components for presenting interactive artificial-reality environments, such as processors, memory, and/or presentation devices, including one or more displays and/or one or more waveguides), some of which are described in more detail with respect to FIG. 17. As described herein, a head-wearable device can include components of eyewear device 1502 and/or headmounted display 1612. Some examples of head-wearable devices do not include any displays, including any of the displays described with respect to AR system 1500 and/or VR system 1610. While the example artificial-reality systems are respectively described herein as AR system 1500 and VR system 1610, either or both of the example AR systems described herein can be configured to present fully-immersive virtual-reality scenes presented in substantially all of a user’s field of view or subtler augmented-reality scenes that are presented within a portion, less than all, of the user’s field of view.

[0210] FIG. 15 show an example visual depiction of AR system 1500, including an eyewear device 1502 (which may also be described herein as augmented-reality glasses, and/or smart glasses). AR system 1500 can include additional electronic components that are not shown in FIG. 15, such as a wearable accessory device and/or an intermediary processing device, in electronic communication or otherwise configured to be used in conjunction with the eyewear device 1502. In some examples, the wearable accessory device and/or the intermediary processing device may be configured to couple with eyewear device 1502 via a coupling mechanism in electronic communication with a coupling sensor 1724 (FIG. 17), where coupling sensor 1724 can detect when an electronic device becomes physically or electronically coupled with eyewear device 1502. In some examples, eyewear device 1502 can be configured to couple to a housing 1790 (FIG. 17), which may include one or more additional coupling mechanisms configured to couple with additional accessory devices. The components shown in FIG. 15 can be implemented in hardware, software, firmware, or a combination thereof, including one or more signal-processing components and/or applicationspecific integrated circuits (ASICs).

[0211] Eyewear device 1502 includes mechanical glasses components, including a frame 1504 configured to hold one or more lenses (e.g., one or both lenses 1506-1 and 1506-2). One of ordinary skill in the art will appreciate that eyewear device 1502 can include additional mechanical components, such as hinges configured to allow portions of frame 1504 of eyewear device 1502 to be folded and unfolded, a bridge configured to span the gap between lenses 1506-1 and 1506-2 and rest on the user’s nose, nose pads configured to rest on the bridge of the nose and provide support for eyewear device 1502, earpieces configured to rest on the user’s ears and provide additional support for eyewear device 1502, temple arms configured to extend from the hinges to the earpieces of eyewear device 1502, and the like. One of ordinary skill in the art will further appreciate that some examples of AR system 1500 can include none of the mechanical components described herein. For example, smart contact lenses configured to present artificial reality to users may not include any components of eyewear device 1502.

[0212] Eyewear device 1502 includes electronic components, many of which will be described in more detail below with respect to FIG. 17. Some example electronic components are illustrated in FIG. 15, including acoustic sensors 1525-1 , 1525-2, 1525-3, 1525-4, 1525-5, and 1525-6, which can be distributed along a substantial portion of the frame 1504 of eyewear device 1502. Eyewear device 1502 also includes a left camera 1539A and a right camera 1539B, which are located on different sides of the frame 1504. Eyewear device 1502 also includes a processor 1548 (or any other suitable type or form of integrated circuit) that is embedded into a portion of the frame 1504.

[0213] FIGS. 16A and 16B show a VR system 1610 that includes a head-mounted display (HMD) 1612 (e.g., also referred to herein as an artificial-reality headset, a head-wearable device, a VR headset, etc.). As noted, some artificial-reality systems (e.g., AR system 1500) may, instead of blending an artificial reality with actual reality, substantially replace one or more of a user’s visual and/or other sensory perceptions of the real world with a virtual experience (e.g., AR systems 1 100 and 1200).

[0214] HMD 1612 includes a front body 1614 and a frame 1616 (e.g., a strap or band) shaped to fit around a user’s head. In some examples, front body 1614 and/or frame 1616 include one or more electronic elements for facilitating presentation of and/or interactions with an AR and/or VR system (e.g., displays, IMUs, tracking emitter or detectors). In some examples, HMD 1612 includes output audio transducers (e.g., an audio transducer 1618), as shown in FIG. 16B. In some examples, one or more components, such as the output audio transducer(s) 1618 and frame 1616, can be configured to attach and detach (e.g., are detachably attachable) to HMD 1612 (e.g., a portion or all of frame 1616, and/or audio transducer 1618), as shown in FIG. 16B. In some examples, coupling a detachable component to HMD 1612 causes the detachable component to come into electronic communication with HMD 1612.

[0215] FIGS. 16A and 16B also show that VR system 1610 includes one or more cameras, such as left camera 1639A and right camera 1639B, which can be analogous to left and right cameras 1539A and 1539B on frame 1504 of eyewear device 1502. In some examples, VR system 1610 includes one or more additional cameras (e.g., cameras 1639C and 1639D), which can be configured to augment image data obtained by left and right cameras 1639A and 1639B by providing more information. For example, camera 1639C can be used to supply color information that is not discerned by cameras 1639A and 1639B. In some examples, one or more of cameras 1639A to 1639D can include an optional IR cut filter configured to remove IR light from being received at the respective camera sensors.

[0216] FIG. 17 illustrates a computing system 1720 and an optional housing 1790, each of which show components that can be included in AR system 1500 and/or VR system 1610. In some examples, more or fewer components can be included in optional housing 1790 depending on practical restraints of the respective AR system being described.

[0217] In some examples, computing system 1720 can include one or more peripherals interfaces 1722A and/or optional housing 1790 can include one or more peripherals interfaces 1722B. Each of computing system 1720 and optional housing 1790 can also include one or more power systems 1742A and 1742B, one or more controllers 1746 (including one or more haptic controllers 1747), one or more processors 1748A and 1748B (as defined above, including any of the examples provided), and memory 1750A and 1750B, which can all be in electronic communication with each other. For example, the one or more processors 1748A and 1748B can be configured to execute instructions stored in memory 1750A and 1750B, which can cause a controller of one or more of controllers 1746 to cause operations to be performed at one or more peripheral devices connected to peripherals interface 1722A and/or 1722B. In some examples, each operation described can be powered by electrical power provided by power system 1742A and/or 1742B.

[0218] In some examples, peripherals interface 1722A can include one or more devices configured to be part of computing system 1720, some of which have been defined above and/or described with respect to the wrist-wearable devices shown in FIGS. 13 and 14. For example, peripherals interface 1722A can include one or more sensors 1723A. Some example sensors 1723A include one or more coupling sensors 1724, one or more acoustic sensors 1725, one or more imaging sensors 1726, one or more EMG sensors 1727, one or more capacitive sensors 1728, one or more IMU sensors 1729, and/or any other types of sensors explained above or described with respect to any other examples discussed herein.

[0219] In some examples, peripherals interfaces 1722A and 1722B can include one or more additional peripheral devices, including one or more NFC devices 1730, one or more GPS devices 1731 , one or more LTE devices 1732, one or more Wi-Fi and/or Bluetooth devices 1733, one or more buttons 1734 (e.g., including buttons that are slidable or otherwise adjustable), one or more displays 1735A and 1735B, one or more speakers 1736A and 1736B, one or more microphones 1737, one or more cameras 1738A and 1738B (e.g., including the left camera 1739A and/or a right camera 1739B), one or more haptic devices 1740, and/or any other types of peripheral devices defined above or described with respect to any other examples discussed herein.

[0220] AR systems can include a variety of types of visual feedback mechanisms (e.g., presentation devices). For example, display devices in AR system 1500 and/or VR system 1610 can include one or more liquid-crystal displays (LCDs), light emitting diode (LED) displays, organic LED (OLED) displays, and/or any other suitable types of display screens. Artificial-reality systems can include a single display screen (e.g., configured to be seen by both eyes), and/or can provide separate display screens for each eye, which can allow for additional flexibility for varifocal adjustments and/or for correcting a refractive error associated with a user’s vision. Some examples of AR systems also include optical subsystems having one or more lenses (e.g., conventional concave or convex lenses, Fresnel lenses, or adjustable liquid lenses) through which a user can view a display screen.

[0221] For example, respective displays 1735A and 1735B can be coupled to each of the lenses 1506-1 and 1506-2 of AR system 1500. Displays 1735A and 1735B may be coupled to each of lenses 1506-1 and 1506-2, which can act together or independently to present an image or series of images to a user. In some examples, AR system 1500 includes a single display 1735A or 1735B (e.g., a near-eye display) or more than two displays 1735A and 1735B. In some examples, a first set of one or more displays 1735A and 1735B can be used to present an augmented-reality environment, and a second set of one or more display devices 1735A and 1735B can be used to present a virtual-reality environment. In some examples, one or more waveguides are used in conjunction with presenting artificial-reality content to the user of AR system 1500 (e.g., as a means of delivering light from one or more displays 1735A and 1735B to the user’s eyes). In some examples, one or more waveguides are fully or partially integrated into the eyewear device 1502. Additionally, or alternatively to display screens, some artificial-reality systems include one or more projection systems. For example, display devices in AR system 1500 and/or VR system 1610 can include micro-LED projectors that project light (e.g., using a waveguide) into display devices, such as clear combiner lenses that allow ambient light to pass through. The display devices can refract the projected light toward a user’s pupil and can enable a userto simultaneously view both artificial-reality content and the real world. Artificial-reality systems can also be configured with any other suitable type or form of image projection system. In some examples, one or more waveguides are provided additionally or alternatively to the one or more display(s) 1735A and 1735B.

[0222] Computing system 1720 and/or optional housing 1790 of AR system 1500 or VR system 1610 can include some or all of the components of a power system 1742A and 1742B. Power systems 1742A and 1742B can include one or more charger inputs 1743, one or more PMICs 1744, and/or one or more batteries 1745A and 1744B.

[0223] Memory 1750A and 1750B may include instructions and data, some or all of which may be stored as non-transitory computer-readable storage media within the memories 1750A and 1750B. For example, memory 1750A and 1750B can include one or more operating systems 1751 , one or more applications 1752, one or more communication interface applications 1753A and 1753B, one or more graphics applications 1754A and 1754B, one or more AR processing applications 1755A and 1755B, and/or any other types of data defined above or described with respect to any other examples discussed herein.

[0224] Memory 1750A and 1750B also include data 1760A and 1760B, which can be used in conjunction with one or more of the applications discussed above. Data 1760A and 1760B can include profile data 1761 , sensor data 1762A and 1762B, media content data 1763A, AR application data 1764A and 1764B, and/or any other types of data defined above or described with respect to any other examples discussed herein.

[0225] In some examples, controller 1746 of eyewear device 1502 may process information generated by sensors 1723A and/or 1723B on eyewear device 1502 and/or another electronic device within AR system 1500. For example, controller 1746 can process information from acoustic sensors 1525-1 and 1525-2. For each detected sound, controller 1746 can perform a direction of arrival (DOA) estimation to estimate a direction from which the detected sound arrived at eyewear device 1502 of AR system 1500. As one or more of acoustic sensors 1725 (e.g., the acoustic sensors 1525-1 , 1525-2) detects sounds, controller 1746 can populate an audio data set with the information (e.g., represented in FIG. 17 as sensor data 1762A and 1762B).

[0226] In some examples, a physical electronic connector can convey information between eyewear device 1502 and another electronic device and/or between one or more processors 1548, 1748A, 1748B of AR system 1500 or VR system 1610 and controller 1746. The information can be in the form of optical data, electrical data, wireless data, or any other transmittable data form. Moving the processing of information generated by eyewear device 1502 to an intermediary processing device can reduce weight and heat in the eyewear device, making it more comfortable and safer for a user. In some examples, an optional wearable accessory device (e.g., an electronic neckband) is coupled to eyewear device 1502 via one or more connectors. The connectors can be wired or wireless connectors and can include electrical and/or non-electrical (e.g., structural) components. In some examples, eyewear device 1502 and the wearable accessory device can operate independently without any wired or wireless connection between them.

[0227] In some situations, pairing external devices, such as an intermediary processing device (e.g., HIPD 906, 1006, 1106) with eyewear device 1502 (e.g., as part of AR system 1500) enables eyewear device 1502 to achieve a similar form factor of a pair of glasses while still providing sufficient battery and computation power for expanded capabilities. Some, or all, of the battery power, computational resources, and/or additional features of AR system 1500 can be provided by a paired device or shared between a paired device and eyewear device 1502, thus reducing the weight, heat profile, and form factor of eyewear device 1502 overall while allowing eyewear device 1502 to retain its desired functionality. For example, the wearable accessory device can allow components that would otherwise be included on eyewear device 1502 to be included in the wearable accessory device and/or intermediary processing device, thereby shifting a weight load from the user’s head and neck to one or more other portions of the user’s body. In some examples, the intermediary processing device has a larger surface area over which to diffuse and disperse heat to the ambient environment. Thus, the intermediary processing device can allow for greater battery and computation capacity than might otherwise have been possible on eyewear device 1502 standing alone. Because weight carried in the wearable accessory device can be less invasive to a user than weight carried in the eyewear device 1502, a user may tolerate wearing a lighter eyewear device and carrying or wearing the paired device for greater lengths of time than the user would tolerate wearing a heavier eyewear device standing alone, thereby enabling an artificialreality environment to be incorporated more fully into a user’s day-to-day activities.

[0228] AR systems can include various types of computer vision components and subsystems. For example, AR system 1500 and/or VR system 1610 can include one or more optical sensors such as two-dimensional (2D) or three-dimensional (3D) cameras, time-of- flight depth sensors, structured light transmitters and detectors, single-beam or sweeping laser rangefinders, 3D LiDAR sensors, and/or any other suitable type or form of optical sensor. An AR system can process data from one or more of these sensors to identify a location of a user and/or aspects of the use’s real-world physical surroundings, including the locations of real- world objects within the real-world physical surroundings. In some examples, the methods described herein are used to map the real world, to provide a user with context about real- world surroundings, and/or to generate digital twins (e.g., interactable virtual objects), among a variety of other functions. For example, FIGS. 16A and 16B show VR system 1610 having cameras 1639A to 1639D, which can be used to provide depth information for creating a voxel field and a two-dimensional mesh to provide object information to the user to avoid collisions. [0229] In some examples, AR system 1500 and/or VR system 1610 can include haptic (tactile) feedback systems, which may be incorporated into headwear, gloves, body suits, handheld controllers, environmental devices (e.g., chairs or floormats), and/or any other type of device or system, such as the wearable devices discussed herein. The haptic feedback systems may provide various types of cutaneous feedback, including vibration, force, traction, shear, texture, and/or temperature. The haptic feedback systems may also provide various types of kinesthetic feedback, such as motion and compliance. The haptic feedback may be implemented using motors, piezoelectric actuators, fluidic systems, and/or a variety of other types of feedback mechanisms. The haptic feedback systems may be implemented independently of other artificial-reality devices, within other artificial-reality devices, and/or in conjunction with other artificial-reality devices.

[0230] In some examples of an artificial reality system, such as AR system 1500 and/or VR system 1610, ambient light (e.g., a live feed of the surrounding environment that a user would normally see) can be passed through a display element of a respective head-wearable device presenting aspects of the AR system. In some examples, ambient light can be passed through a portion less that is less than all of an AR environment presented within a user’s field of view (e.g., a portion of the AR environment co-located with a physical object in the user’s real-world environment that is within a designated boundary (e.g., a guardian boundary) configured to be used by the user while they are interacting with the AR environment). For example, a visual user interface element (e.g., a notification user interface element) can be presented at the head-wearable device, and an amount of ambient light (e.g., 15-50% of the ambient light) can be passed through the user interface element such that the user can distinguish at least a portion of the physical environment over which the user interface element is being displayed. [0231] In some examples, the augmented reality systems described herein may also include a microphone array with a plurality of acoustic transducers. Acoustic transducers may represent transducers that detect air pressure variations induced by sound waves. Each acoustic transducer may be configured to detect sound and convert the detected sound into an electronic format (e.g., an analog or digital format). A microphone array may include, for example, ten acoustic transducers that may be designed to be placed inside a corresponding ear of the user, acoustic transducers that may be positioned at various locations on an HMD frame a watch band, etc.

[0232] In some examples, one or more of acoustic transducers may be used as output transducers (e.g., speakers). For example, the artificial reality systems described herein may include acoustic transducers that are earbuds or any other suitable type of headphone or speaker.

[0233] The configuration of acoustic transducers of a microphone array may vary and may include any suitable number of transducers. In some examples, using higher numbers of acoustic transducers may increase the amount of audio information collected and/or the sensitivity and accuracy of the audio information. In contrast, using a lower number of acoustic transducers may decrease the computing power required by an associated controller to process the collected audio information. In addition, the position of each acoustic transducer of the microphone array may vary. For example, the position of an acoustic transducer may include a defined position on the user, a defined coordinate on a frame of an HMD, an orientation associated with each acoustic transducer, or some combination thereof.

[0234] Acoustic transducers and may be positioned on different parts of the user’s ear, such as behind the pinna, behind the tragus, and/or within the auricle or fossa. Or, there may be additional acoustic transducers on or surrounding the ear in addition to acoustic transducers inside the ear canal. Having an acoustic transducer positioned next to an ear canal of a user may enable the microphone array to collect information on how sounds arrive at the ear canal. By positioning at least two of acoustic transducers on either side of a user’s head (e.g., as binaural microphones), an artificial-reality device may simulate binaural hearing and capture a 3D stereo sound field around about a user’s head. In some examples, acoustic transducers may be connected to artificial reality systems via a wired connection, and in other examples acoustic transducers may be connected to artificial-reality systems via a wireless connection (e.g., a BLUETOOTH connection).

[0235] Acoustic transducers may be positioned on HMDs frames in a variety of different ways, including along the length of the temples, across the bridge, above or below display devices, or some combination thereof. Acoustic transducers may also be oriented such that the microphone array is able to detect sounds in a wide range of directions surrounding the user wearing the augmented-reality system. In some examples, an optimization process may be performed during manufacturing of augmented-reality system to determine relative positioning of each acoustic transducer in the microphone array.

[0236] The artificial-reality systems described herein may also include one or more input and/or output audio transducers. Output audio transducers may include voice coil speakers, ribbon speakers, electrostatic speakers, piezoelectric speakers, bone conduction transducers, cartilage conduction transducers, tragus-vibration transducers, and/or any other suitable type or form of audio transducer. Similarly, input audio transducers may include condenser microphones, dynamic microphones, ribbon microphones, and/or any other type or form of input transducer. In some examples, a single transducer may be used for both audio input and audio output.

[0237] When the user is wearing an augmented-reality headset or virtual-reality headset in a given environment, the user may be interacting with other users or other electronic devices that serve as audio sources. In some cases, it may be desirable to determine where the audio sources are located relative to the user and then present the audio sources to the user as if they were coming from the location of the audio source. The process of determining where the audio sources are located relative to the user may be referred to as “localization,” and the process of rendering playback of the audio source signal to appear as if it is coming from a specific direction may be referred to as “spatialization.”

[0238] Localizing an audio source may be performed in a variety of different ways. In some cases, an augmented-reality or virtual-reality headset may initiate a DOA analysis to determine the location of a sound source. The DOA analysis may include analyzing the intensity, spectra, and/or arrival time of each sound at the artificial-reality device to determine the direction from which the sounds originated. The DOA analysis may include any suitable algorithm for analyzing the surrounding acoustic environment in which the artificial reality device is located. [0239] For example, the DOA analysis may be designed to receive input signals from a microphone and apply digital signal processing algorithms to the input signals to estimate the direction of arrival. These algorithms may include, for example, delay and sum algorithms where the input signal is sampled, and the resulting weighted and delayed versions of the sampled signal are averaged togetherto determine a direction of arrival. A least mean squared (LMS) algorithm may also be implemented to create an adaptive filter. This adaptive filter may then be used to identify differences in signal intensity, for example, or differences in time of arrival. These differences may then be used to estimate the direction of arrival. In another example, the DOA may be determined by converting the input signals into the frequency domain and selecting specific bins within the time-frequency (TF) domain to process. Each selected TF bin may be processed to determine whether that bin includes a portion of the audio spectrum with a direct-path audio signal. Those bins having a portion of the direct-path signal may then be analyzed to identify the angle at which a microphone array received the direct-path audio signal. The determined angle may then be used to identify the direction of arrival for the received input signal. Other algorithms not listed above may also be used alone or in combination with the above algorithms to determine DOA.

[0240] In some examples, different users may perceive the source of a sound as coming from slightly different locations. This may be the result of each user having a unique head-related transfer function (HRTF), which may be dictated by a user’s anatomy including ear canal length and the positioning of the ear drum. The artificial-reality device may provide an alignment and orientation guide, which the user may follow to customize the sound signal presented to the user based on their unique HRTF. In some examples, an artificial reality device may implement one or more microphones to listen to sounds within the user’s environment. The augmented reality or virtual reality headset may use a variety of different array transfer functions (e.g., any of the DOA algorithms identified above) to estimate the direction of arrival for the sounds. Once the direction of arrival has been determined, the artificial-reality device may play back sounds to the user according to the user’s unique HRTF. Accordingly, the DOA estimation generated using the array transfer function (ATF) may be used to determine the direction from which the sounds are to be played from. The playback sounds may be further refined based on how that specific user hears sounds according to the HRTF.

[0241] In addition to or as an alternative to performing a DOA estimation, an artificial-reality device may perform localization based on information received from other types of sensors. These sensors may include cameras, IR sensors, heat sensors, motion sensors, GPS receivers, or in some cases, sensors that detect a user’s eye movements. For example, as noted above, an artificial-reality device may include an eye tracker or gaze detector that determines where the user is looking. Often, the user’s eyes will look at the source of the sound, if only briefly. Such clues provided by the user’s eyes may further aid in determining the location of a sound source. Other sensors such as cameras, heat sensors, and IR sensors may also indicate the location of a user, the location of an electronic device, or the location of another sound source. Any or all of the above methods may be used individually or in combination to determine the location of a sound source and may further be used to update the location of a sound source over time.

[0242] Some examples may implement the determined DOA to generate a more customized output audio signal for the user. For instance, an “acoustic transfer function” may characterize or define how a sound is received from a given location. More specifically, an acoustic transfer function may define the relationship between parameters of a sound at its source location and the parameters by which the sound signal is detected (e.g., detected by a microphone array or detected by a user’s ear). An artificial-reality device may include one or more acoustic sensors that detect sounds within range of the device. A controller of the artificial-reality device may estimate a DOAforthe detected sounds (using, e.g., any of the methods identified above) and, based on the parameters of the detected sounds, may generate an acoustic transfer function that is specific to the location of the device. This customized acoustic transfer function may thus be used to generate a spatialized output audio signal where the sound is perceived as coming from a specific location.

[0243] Indeed, once the location of the sound source or sources is known, the artificial-reality device may re-render (i.e., spatialize) the sound signals to sound as if coming from the direction of that sound source. The artificial-reality device may apply filters or other digital signal processing that alterthe intensity, spectra, or arrival time of the sound signal. The digital signal processing may be applied in such a way that the sound signal is perceived as originating from the determined location. The artificial-reality device may amplify or subdue certain frequencies or change the time that the signal arrives at each ear. In some cases, the artificial-reality device may create an acoustic transfer function that is specific to the location of the device and the detected direction of arrival of the sound signal. In some examples, the artificial-reality device may re-render the source signal in a stereo device or multi-speaker device (e.g., a surround sound device). In such cases, separate and distinct audio signals may be sent to each speaker. Each of these audio signals may be altered according to the user’s HRTF and according to measurements of the user’s location and the location of the sound source to sound as if they are coming from the determined location of the sound source. Accordingly, in this manner, the artificial-reality device (or speakers associated with the device) may re-render an audio signal to sound as if originating from a specific location.

[0244] As detailed above, the computing devices and systems described and/or illustrated herein broadly represent any type or form of computing device or system capable of executing computer-readable instructions, such as those contained within the modules described herein. In their most basic configuration, these computing device(s) may each include at least one memory device and at least one physical processor.

[0245] In some examples, the term “memory device” generally refers to any type or form of volatile or non-volatile storage device or medium capable of storing data and/or computer- readable instructions. In one example, a memory device may store, load, and/or maintain one or more of the modules described herein. Examples of memory devices include, without limitation, Random Access Memory (RAM), Read Only Memory (ROM), flash memory, Hard Disk Drives (HDDs), Solid-State Drives (SSDs), optical disk drives, caches, variations or combinations of one or more of the same, or any other suitable storage memory.

[0246] In some examples, the term “physical processor” generally refers to any type or form of hardware-implemented processing unit capable of interpreting and/or executing computer- readable instructions. In one example, a physical processor may access and/or modify one or more modules stored in the above-described memory device. Examples of physical processors include, without limitation, microprocessors, microcontrollers, Central Processing Units (CPUs), Field-Programmable Gate Arrays (FPGAs) that implement softcore processors, Application-Specific Integrated Circuits (ASICs), portions of one or more of the same, variations or combinations of one or more of the same, or any other suitable physical processor.

[0247] Although illustrated as separate elements, the modules described and/or illustrated herein may represent portions of a single module or application. In addition, in certain examples one or more of these modules may represent one or more software applications or programs that, when executed by a computing device, may cause the computing device to perform one or more tasks. For example, one or more of the modules described and/or illustrated herein may represent modules stored and configured to run on one or more of the computing devices or systems described and/or illustrated herein. One or more of these modules may also represent all or portions of one or more special-purpose computers configured to perform one or more tasks.

[0248] In addition, one or more of the modules described herein may transform data, physical devices, and/or representations of physical devices from one form to another. For example, one or more of the modules recited herein may receive [data] to be transformed, transform the data, output a result of the transformation to perform a function, use the result of the transformation to perform a function, and store the result of the transformation to perform a function. Additionally or alternatively, one or more of the modules recited herein may transform a processor, volatile memory, non-volatile memory, and/or any other portion of a physical computing device from one form to another by executing on the computing device, storing data on the computing device, and/or otherwise interacting with the computing device.

[0249] In some examples, the term “computer-readable medium’’ generally refers to any form of device, carrier, or medium capable of storing or carrying computer-readable instructions. Examples of computer-readable media include, without limitation, transmission-type media, such as carrier waves, and non-transitory-type media, such as magnetic-storage media (e.g., hard disk drives, tape drives, and floppy disks), optical-storage media (e.g., Compact Disks (CDs), Digital Video Disks (DVDs), and BLU-RAY disks), electronic-storage media (e.g., solid- state drives and flash media), and other distribution systems.

[0250] The process parameters and sequence of the steps described and/or illustrated herein are given by way of example only and can be varied as desired. For example, while the steps illustrated and/or described herein may be shown or discussed in a particular order, these steps do not necessarily need to be performed in the order illustrated or discussed. The various exemplary methods described and/or illustrated herein may also omit one or more of the steps described or illustrated herein or include additional steps in addition to those disclosed.

[0251] Herein, “or” is inclusive and not exclusive, unless expressly indicated otherwise or indicated otherwise by context. Therefore, herein, “A or B” means “A, B, or both,” unless expressly indicated otherwise or indicated otherwise by context. Moreover, “and” is both joint and several, unless expressly indicated otherwise or indicated otherwise by context. Therefore, herein, “A and B” means “A and B, jointly or severally,” unless expressly indicated otherwise or indicated otherwise by context.

[0252] The foregoing description of the examples has been presented for the purpose of illustration; it is not intended to be exhaustive or to limit the patent rights to the precise forms disclosed. Persons skilled in the relevant art can appreciate that many modifications and variations are possible in light of the disclosure.

[0253] The scope of this disclosure encompasses all changes, substitutions, variations, alterations, and modifications to the example examples described or illustrated herein that a person having ordinary skill in the art would comprehend. The scope of this disclosure is not limited to the example examples described or illustrated herein. Moreover, although this disclosure describes and illustrates respective examples herein as including particular components, elements, feature, functions, operations, or steps, any of these examples may include any combination or permutation of any of the components, elements, features, functions, operations, or steps described or illustrated anywhere herein that a person having ordinary skill in the art would comprehend. Furthermore, reference in the appended claims to an apparatus or system or a component of an apparatus or system being adapted to, arranged to, capable of, configured to, enabled to, operable to, or operative to perform a particular function encompasses that apparatus, system, component, whether or not it or that particular function is activated, turned on, or unlocked, as long as that apparatus, system, or component is so adapted, arranged, capable, configured, enabled, operable, or operative. Additionally, although this disclosure describes or illustrates particular examples as providing particular advantages, particular examples may provide none, some, or all of these advantages.

[0254] Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the patent rights be limited not by this detailed description, but rather by any claims that issue on an application based hereon. Accordingly, the disclosure of the examples is intended to be illustrative, but not limiting, of the scope of the patent rights, which is set forth in the following claims.

[0255] The preceding description has been provided to enable others skilled in the art to best utilize various aspects of the examples disclosed herein. This exemplary description is not intended to be exhaustive or to be limited to any precise form disclosed. Many modifications and variations are possible without departing from the scope of the present disclosure. The examples disclosed herein should be considered in all respects illustrative and not restrictive. Reference should be made to the appended claims and their equivalents in determining the scope of the present disclosure.

[0256] Unless otherwise noted, the terms “connected to” and “coupled to” (and their derivatives), as used in the specification and claims, are to be construed as permitting both direct and indirect (i.e. , via other elements or components) connection. In addition, the terms “a” or “an,” as used in the specification and claims, are to be construed as meaning “at least one of.” Finally, for ease of use, the terms “including” and “having” (and their derivatives), as used in the specification and claims, are interchangeable with and have the same meaning as the word “comprising.”

Claims

1. A method comprising: generating an audio signal based on sound received by one or more microphones of an open-ear device; and performing a hearing enhancement process in response to user input, the hearing enhancement process comprising: detecting a speech component of the audio signal; applying a gain function to the speech component of the audio signal based on a plurality of gain parameters to generate a modified output signal; and operating one or more loudspeakers of the open-ear device to produce sound according to the modified output signal.

2. The method of claim 1 , wherein applying the gain function comprises applying an adaptive dynamic range optimization gain to the speech component of the audio signal.

3. The method of claim 1 or claim 2, wherein applying the gain function is based on one or more of: a comfort target; a background noise estimate; and an audibility threshold.

4. The method of any preceding claim, wherein detecting the speech component of the audio signal comprises providing at least part of the audio signal, or data derived therefrom, to a neural network.

5. The method of any preceding claim, wherein detecting the speech component of the audio signal is performed prior to applying the gain function.

6. The method of any preceding claim, wherein the open-ear device comprises a waveguide accessory, and wherein the method further comprises reflecting the sound produced by the one or more loudspeakers toward an ear of a user.

7. The method of claim 6, wherein the waveguide accessory includes a passive waveguide structure removably attachable to the open-ear device.

8. The method of any preceding claim, wherein the user input comprises a touch gesture applied to the open-ear device.

9. A method comprising: generating an audio signal based on sound received by one or more microphones of an open-ear device; and performing a hearing enhancement process comprising: detecting a speech component of the audio signal; computing a signal level of the speech component of the audio signal; applying an adaptive dynamic range optimization gain to the speech component of the audio signal based on the computed signal level and one or more parameters, thereby generating a processed signal; operating one or more loudspeakers of the open-ear device to produce sound according to the processed signal; and reflecting the sound produced by the one or more loudspeakers toward an ear of a user using a waveguide accessory of the open-ear device.

10. The method of claim 9, wherein the waveguide accessory comprises a passive waveguide structure removably attachable to the open-ear device.

11 . The method of claim 9 or 10, wherein the adaptive dynamic range optimization gain is updated in real time based on continuous computation of the signal level of the speech component of the audio signal.

12. The method of any of claims 9 to 11 , wherein the adaptive dynamic range optimization gain is selectively applied to the speech component of the audio signal while suppressing non-speech components of the audio signal.

13. A wearable open-ear device comprising: at least one microphone; at least one loudspeaker comprising a passive waveguide; and at least one processing unit configured to carry out the method of any preceding claim.

14. The wearable open-ear device of claim 13, wherein the at least one microphone is spatially located in a predetermined distance from the at least one loudspeaker.

15. The wearable open-ear device of claim 13 or 14, wherein the passive waveguide comprises a structure configured to couple to the open-ear device.