JP7618799B2 - Breathing feedback to improve exercise performance - Google Patents

Description

The present invention relates to respiratory feedback to improve exercise performance.

Proper breathing can help reduce stress, control emotions, improve attention, and maximize the benefits of exercise by increasing oxygenated blood flow to the heart. This prevents injuries (such as hernias or blood pressure spikes) and improves exercise efficiency, allowing people to exercise for longer periods of time and more comfortably. New exercisers want to know how to exercise properly and most effectively for their personal ability level, but are often deterred by the expense of a personal trainer or are overly intimidated by attending a gym. In addition to learning about the exercise itself, learning the proper breathing techniques for such exercises can be difficult. Also, exercisers who have been exercising for some time and those who have been exercising for a long time may record their progress through handwritten notes or fitness tracking applications, but such tracking techniques do not provide feedback during the exercise. Some people use wearable heart rate monitors when exercising, but heart rate measurements may not provide the necessary information about whether the exerciser is performing the exercise properly and may not be useful for non-aerobic exercises such as yoga. Cameras or motion sensors that monitor a user's movements do not provide user feedback designed to help improve breathing during a wide variety of exercises. Proper breathing morphology may include targeting a certain breathing-to-movement cadence (e.g., one breath for every two steps while running) and breathing deeply from the diaphragm (e.g., shallow chest breathing versus rib cage expanding in all directions). Breathing easily from the diaphragm is also generally a good indicator of proper muscle morphology.

Various aspects include a method executed by a processor of a user equipment, and a computing device implementing the method, for providing information regarding a user's breathing pattern during exercise. Various aspects may include determining a current exercise being performed by a user, determining a target breathing pattern appropriate for the current exercise being performed by the user, monitoring the user's current breathing pattern while performing the current exercise based on input from a breathing sensor, determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern, and providing the user with information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern.

Some aspects may include receiving sensor input from an exercise sensor that provides information regarding the user's physical movement, and determining the current exercise is based on the sensor input received from the exercise sensor. In some aspects, the target breathing pattern is based on sensor input received from the exercise sensor that indicates how the user is moving during exercise. Some aspects may include receiving sensor input from an exercise sensor that provides exercise information regarding the current exercise, and the exercise sensor is associated with exercise equipment being used by the user to perform the current exercise.

Some aspects may include receiving user physical motion information from an exercise sensor indicating which of the first and second portions of the current exercise the user is currently performing. In some aspects, the target breathing pattern may include an associated first breathing pattern associated with the first portion of the current exercise and a second breathing pattern associated with the second portion of the current exercise that is different from the first breathing pattern, and determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern may include determining a difference between the target breathing pattern appropriate for the first and second portions of the current exercise and the user's current breathing pattern during the first and second portions of the current exercise, and the information provided to the user may include a difference between the target breathing pattern appropriate for the first and second portions of the current exercise and the user's current breathing pattern during the first and second portions of the current exercise.

Some aspects may include receiving manual user input regarding at least one of the current exercise or the target breathing pattern, and determining the target breathing pattern is further based on the received manual user input. Some aspects may include receiving contextual information indicating a context in which the user is performing the current exercise, and determining the target breathing pattern is further based on the received contextual information. In some aspects, the target breathing pattern may be based on at least one of the user's body type, health goals, or experience level performing the current exercise.

Some aspects may include determining an alternative target breathing pattern for the user to achieve in response to the current breathing pattern exceeding a normal breathing pattern threshold and providing additional information to the user regarding the alternative target breathing pattern. Some aspects may include activating a breathing sensor configured to monitor the user's current breathing pattern while performing the current exercise in response to determining that the current exercise is being performed by the user. In some aspects, determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern may include comparing the user's current breathing pattern to at least one of a previously determined breathing rate, rhythm, or quality of the user as the user performed the current exercise.

Some embodiments may include activating an additional sensor in response to the user's current breathing pattern exceeding a normal breathing pattern threshold. Some embodiments may include determining a first range of physical movement by the user attributable to the determined current exercise, separate from respiration, and the user's current breathing pattern is associated with a second range of physical movement by the user attributable to respiration and separate from the first range of physical movement.

In some aspects, the user's current breathing pattern includes at least one of a breathing rate, rhythm, or quality of the respiratory exercise. In some aspects, providing the user with information regarding the determined difference includes notifying the user through at least one of a visual, an audio, or a tactile alert. In some aspects, the current exercise is determined based on information regarding the determined difference between the user's current breathing pattern and a target breathing pattern appropriate for the exercise equipment used by the user and the current exercise being performed by the user, and the user's current breathing pattern is provided to the user through feedback from the exercise equipment.

A further aspect includes a user equipment device including a processor configured with processor-executable instructions for performing any of the operations of the methods summarized above. A further aspect includes a non-transitory processor-readable storage medium having stored thereon processor-executable software instructions configured to cause a processor to perform any of the operations of the methods summarized above. A further aspect includes a processing device for use in a computing device and configured to perform any of the operations of the methods summarized above.

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments and, together with the general description given above and the detailed description given below, serve to explain features of the various embodiments.

FIG. 1 is a schematic diagram illustrating a user device working in conjunction with a wearable device to provide information regarding a user's breathing patterns during resistance training exercise, in accordance with various embodiments. FIG. 1 is a schematic diagram illustrating a user device working in conjunction with a wearable device to provide information regarding the breathing patterns of a user performing yoga poses, according to various embodiments. FIG. 1 is a schematic diagram illustrating a user device working in conjunction with a wearable device to provide information regarding the breathing patterns of a user running on a treadmill, according to various embodiments. FIG. 1 is a schematic diagram illustrating a user device working in conjunction with a wearable device to provide information regarding a user's breathing patterns on a computerized exercise bike, according to various embodiments. FIG. 1 is a block diagram illustrating components of an exemplary system in a package for use in a computing device, in accordance with various embodiments. FIG. 1 is a component block diagram of an example system configured to be executed by a processor of a user equipment for ensuring that a user receives scheduled notifications. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a process flow diagram of an exemplary method for providing information regarding a user's breathing patterns performed by a processor of a user equipment, according to an embodiment. FIG. 1 is a component block diagram of a networked computing device suitable for use with the various embodiments. FIG. 1 is a component block diagram of a networked computing device suitable for use with the various embodiments. FIG. 1 is a component block diagram of example smart glasses suitable for use with various embodiments.

Various aspects are described in detail with reference to the accompanying drawings. Wherever possible, the same reference numbers are used throughout the drawings to refer to the same or similar parts. References made to specific examples and embodiments are for illustrative purposes only and are not intended to limit the scope of the various aspects or the claims.

Various embodiments provide a method executed by a processor of a user equipment to provide information regarding a user's breathing pattern while exercising. Various embodiments may include determining a current exercise being performed by a user, determining a target breathing pattern appropriate for the current exercise, and determining the user's current breathing pattern while performing the current exercise based on input from a breathing sensor. Further, a difference between the target breathing pattern and the user's current breathing pattern may be determined such that information regarding the determined difference may be provided to the user.

As used herein, the term "breathing pattern" refers to the rate, depth, timing, and consistency of a user's breathing. A user may attempt to achieve a target breathing pattern while performing an exercise that is configured to provide greater benefit to the user. To achieve the target breathing pattern, the user may attempt to gain better control over the physical movements involved in the exercise, or may attempt to directly modify their breathing to match their current breathing pattern with the target breathing pattern.

As used herein, the term "computing device" refers to an electronic device equipped with at least a processor, a communication system, and a memory configured with a contact database. Also, as used herein, the term "user equipment" refers to a particular computing device from which a user may receive notifications. Computing devices include user equipment and may include any one or all of cellular phones, smartphones, portable computing devices, personal or portable multimedia players, laptop computers, tablet computers, 2-in-1 laptop/table computers, smartbooks, ultrabooks, palmtop computers, wireless email receivers, multimedia Internet-enabled cellular phones, smart watches, smart glasses, smart contact lenses, wearable devices including augmented/virtual reality devices, entertainment devices (e.g., wireless game controllers, music and video players, satellite radios, etc.), and similar electronic devices that include memory, wireless communication components, and programmable processors. In various embodiments, the computing device may be configured with memory and/or storage. Additionally, the computing devices referenced in the various exemplary embodiments may be coupled to or include wired or wireless communication capabilities to implement the various embodiments, such as a network transceiver and antenna configured to communicate with a wireless communications network.

As used herein, the term "smart" in reference to a device refers to a device that includes a processor for automated operation to collect and/or process data and/or may be programmed to perform all or a portion of the operations described with respect to various embodiments herein. For example, smartphones, smart glasses, smart contact lenses, smart watches, smart rings, smart necklaces, smart cups, smart straws, smart appliances, etc.

The term "system on a chip" (SOC) is used herein to refer to a single integrated circuit (IC) chip that contains multiple resources and/or processors integrated on a single substrate. A single SOC may include circuits for digital, analog, mixed-signal, and radio frequency functions. A single SOC may also include any number of general-purpose and/or special-purpose processors (digital signal processors, modem processors, video processors, etc.), memory blocks (e.g., ROM, RAM, Flash, etc.), and resources (e.g., timers, voltage regulators, oscillators, etc.). A SOC may also include software for controlling the integrated resources and processors, as well as for controlling peripheral devices.

The term "system in package" (SIP) may be used herein to refer to a single module or package that contains multiple resources, computing units, cores, and/or processors on two or more IC chips, substrates, or SOCs. For example, a SIP may include a single substrate on which multiple IC chips or semiconductor dies are stacked in a vertical configuration. Similarly, a SIP may include one or more multi-chip modules (MCMs) on which multiple ICs or semiconductor dies are packaged in a unifying substrate. A SIP may also include multiple independent SOCs packaged in close proximity, coupled to each other via high-speed communication circuits, such as on a single motherboard or within a single wireless device. The proximity of the SOCs facilitates high-speed communication and sharing of memory and resources.

Various embodiments may detect user activity associated with one or more exercises using one or more of a variety of sensors, as well as detect the user's breathing pattern during the detected activity. In particular, the sensors may be included in one or more adhesive patches, smart clothing, inertial measurement units, sensor-equipped wearable computing devices (sometimes referred to herein as "wearable devices"), sensor-equipped exercise equipment, or other sensors or sensor-equipped computing devices to measure activity associated with the exercise and/or breathing patterns. Wearable devices may include smart glasses, earpieces, other head-worn devices, necklaces, chest bands, watches, bracelets, other wrist-worn devices, and/or smart rings. Input from the one or more sensors may be used to automatically monitor the user's current breathing pattern and determine a target breathing pattern based on the detected current exercise being performed by the user. Additionally, information regarding the determined difference between the target breathing pattern appropriate for the current exercise and the user's current breathing pattern may be provided to the user.

1A-1D show several environments 100, 101, 102, 103 in which a user 5 is exercising and simultaneously using various sensors to provide the user 5 with feedback about the user's breathing in relation to the exercise. In FIGS. 1A and 1B, the users 5, 6 have nearby user equipment 110 that may be configured to communicate with a remote computing device (e.g., a server 195) over a wireless network 190 by a wireless connection 50 (e.g., Wi-Fi, Bluetooth, cellular, etc.), which may be supported by a wireless local area network router (not shown), such as a Wi-Fi wireless router, or a cellular network base station. In FIGS. 1C and 1D, users 7, 8 are located on exercise equipment 160, 170, which may also be configured to communicate with server 195 over wireless network 190 by wireless connection 50 (e.g., Wi-Fi, Bluetooth, cellular, etc.), which may be supported by a wireless local area network router (not shown), such as a Wi-Fi wireless router, or a cellular network base station.

FIG. 1A illustrates an environment 100 in which a user 5 is performing a barbell bench press (i.e., an exercise) while various sensors, such as an adhesive patch sensor 120, smart glasses 130, and/or a smart watch 140, take measurements that are processed by a user device 110 to determine a difference between a target breathing pattern appropriate for the exercise and the current breathing pattern of the user 5, according to various embodiments. Alternatively, or in addition, the adhesive patch sensor 120, smart glasses 130, and/or smart watch 140, according to various embodiments, may be standalone processing units having a display or other user interface (to provide feedback to the user) and may include a processor configured to use the measurements to determine a difference between a target breathing pattern appropriate for the exercise and the current breathing pattern of the user 5.

To perform a conventional barbell bench press, a user 5 lies supine on a bench 90 while holding a bar 92 supporting a weight 94. The user 5 then raises the bar 92 supporting the weight 94 from a first position A close to the user's chest to a second position B where the arms are fully extended from the chest. The user 5 then lowers the bar 92 supporting the weight 94 to the chest and repeats the exercise several times. The amount of weight 94 (i.e., the total weight of the weight) is selected to limit the number of repetitions that the user 5 can perform before fatigue. Because conventional bench press equipment does not include sensors, various embodiments use additional equipment including sensors and computing devices, such as a user equipment 110 configured to provide information regarding the breathing pattern of the user 5 during exercise. The illustrated user equipment 110 is in the form of a cellular phone (i.e., a smartphone), although other forms of computing devices may be used (e.g., tablets, personal computers, exercise machines, wearable devices, smart appliances, etc.).

The adhesive patch sensor 120 may be worn by the user 5 directly on the skin over one or more major muscles used in the exercise (e.g., chest, shoulders, neck, and/or triceps). The adhesive patch sensor 120 may detect blood flow, electrical activity, sweat, lower muscle movement, etc., and may operate without a battery (i.e., passively), be powered by near field communication (NFC), or include an on-board battery. Additionally, the adhesive patch sensor 120 may communicate with the user equipment 110 or other computing devices by wireless connection 50 (e.g., Wi-Fi, Bluetooth, cellular, etc.) through NFC or an on-board transceiver. The adhesive patch sensor 120 may include one or more processors configured to implement the methods of the various embodiments described herein. In some embodiments, the adhesive patch sensor 120 may provide feedback to the user 5 through a speaker and/or a haptic feedback device, thereby providing one or more user interfaces. The adhesive patch sensor 120 may operate as a standalone device or may cooperate with other computing devices, including the user device 110, other wearable devices, and/or exercise equipment.

The smart glasses 130 are a form of wearable equipment that may include a built-in camera, as well as a head-up display or augmented reality functionality on or near the front lens. As with other sensor devices that provide information to the user equipment 110, the smart glasses 130 may include a processor or control unit configured to collect information from an on-board sensor, such as a camera having a field of view 137. The camera may be used to capture images of the exercise equipment and/or the exercise performed by the user to identify what exercise is being performed and/or what portion of the exercise is being performed. For example, if there is a bar 92 within the field of view 137, the images collected by the camera may be used to determine when the user is moving the bar 92 from position A to position B (contractional movement) or when the user is moving the bar 92 from position B to position A (eccentric movement). Additionally, the smart glasses 130 may include an electromyograph (e.g., in the arms of the frame), a microphone, a thermometer, and/or internal sensors such as an inertial measurement unit (IMU), a proximity/motion sensor, a light sensor, a lidar, a gas sensor, and the like. The electromyograph may detect muscle movements associated with the exercise. The microphone may detect breathing patterns from the mouth and/or nose. The thermometer may register the user's body temperature and/or the ambient temperature around the user 5, which may provide contextual information relevant to determining the user's target breathing pattern. The smart glasses 130 may support wireless technologies such as Bluetooth or Wi-Fi to enable communication over a wireless connection 50 (e.g., wireless communication link) to the user equipment 110 and/or other sensors (e.g., 120, 140), etc. Additionally, the smart glasses 130 may control or retrieve data from other sensors (e.g., 120, 140) and/or remote computing devices (110, 195). In some embodiments, the smart glasses 130 may provide feedback to the user 5 through an augmented reality or head-up display, a speaker, and/or a haptic feedback device, thereby providing one or more user interfaces. The smart glasses 130 may include one or more processors configured to implement the methods of the various embodiments described herein. The smart glasses 130 may operate as a standalone device or may cooperate with other computing devices, including the user equipment 110, other wearable devices, and/or exercise equipment.

The smartwatch 140 is a form of wearable device that may include an array of sensors, such as electrical cardiac sensors for taking ECG readings, optical cardiac sensors for measuring heart rate, photoplethysmogram (PPG) sensors for estimating respiration rate (e.g., detecting changes in blood volume), accelerometers and/or gyroscopes for tracking movement and rotation, barometric altimeters for measuring altitude, and ambient light sensors for controlling display brightness. The smartwatch 140 may include a processor or control unit configured to collect information from on-board sensors, support wireless technologies such as Bluetooth or Wi-Fi, and enable communication over a wireless connection 50 to the user equipment 110 and/or other sensors (e.g., 120, 130), etc. The smartwatch 140 provides feedback to the user 5 through a display, speaker, and/or haptic feedback devices, and thus functions as a user interface. Additionally, the smartwatch 140 may control or retrieve data from other sensors (e.g., 120, 130) and/or remote computing devices (110, 195). In some embodiments, smartwatch 140 may operate in conjunction with a mobile operating system to provide feedback to user 5 via a watch face display, vibration, and/or audio. Smartwatch 140 may include one or more processors configured to implement the methods of the various embodiments described herein. Smartwatch 140 may operate as a standalone device or cooperate with other computing devices, including user equipment 110, other wearable devices, and/or exercise equipment.

In various embodiments, a processor of the user device 110, wearable device, or other computing device may determine a current exercise being performed by the user 5, such as by way of input received from a sensor in one or more of the wearable devices 120, 130, 140. Based on the determined exercise, the processor may further determine a target breathing pattern appropriate for the current exercise being performed by the user. The target breathing pattern may be based on at least one of the user's body shape, health goals, or experience level performing the current exercise. Additionally, further input received from a sensor in one or more of the wearable devices 120, 130, 140 may be used by the processor to monitor the user's current breathing pattern while performing the current exercise. The target breathing pattern may be based on received sensor input from one or more exercise sensors indicating how the user is moving during the current exercise. The user's current breathing pattern may include at least one of a breathing rate, rhythm, or quality of the respiratory movement. For example, the input received from the sensor may be used to distinguish diaphragmatic breathing from pulmonary breathing, and vice versa. Similarly, different exercises may require different breathing patterns. For example, running, cycling, and swimming may be performed more efficiently while maintaining a constant cadence or stroke rate, which may be detected from the sensor input. Also, some exercises, such as swimming, may be more efficient if the exhalation or inhalation is performed at a particular portion of the stroke, which may also be detected from the sensor input. The processor may then determine a difference between the target breathing pattern and the user's current breathing pattern. The processor may then provide information to the user 5 regarding the determined difference between the target breathing pattern and the current breathing pattern. For example, the user device 110 may be configured to provide feedback to the user 5 via the display 115, such as an alert that may read "take a breath," or provide audible feedback 116 using the speaker of the user device 110, such as an automated voice output of "take a breath," "breathe into your tummy," customized messages, and/or other messages.

In some embodiments, the processor may also or additionally receive sensor inputs from exercise sensors, such as from exercise equipment (e.g., a treadmill, bike, rowing machine, elliptical machine, etc.) used during exercise that provide information about the user's physical movement useful in determining the current exercise. For example, the processor of user equipment 110 may monitor the current breathing patterns of user 5 as well as determine the current exercise being performed by the user (e.g., barbell bench press, running, fitness biking, swimming, etc.) by analyzing video images of what user 5 is doing (e.g., captured by smart glasses 130) and/or other sensor inputs that detect movement, sound, vibration, or muscle activity.

In some embodiments, the processor may receive user body motion information from an exercise sensor that indicates how the user is moving during an exercise. Additionally or alternatively, the processor may receive user body motion information from an exercise sensor that indicates whether the user is currently performing a first or second portion of the current exercise. For example, an adhesive patch sensor 120 placed on the skin near a particular muscle being trained (i.e., a major muscle used in a particular exercise), or other wearable device such as a smart watch 140, may provide the processor with input that is used to determine not only what exercise is being performed, but also the particular body motion being performed and/or the particular portion of the exercise being performed. Additionally, a sensor placed on the diaphragm may be used to monitor the user's current breathing pattern during exercise, including the particular portion of the exercise. The processor may correlate the measured diaphragm motion associated with the current breathing pattern with the muscle motion associated with the individual portion of the exercise. Using yoga as an example, the target breathing pattern may include exhaling while stretching further into a pose (i.e., the first portion of the current exercise) and then inhaling when breaking out of the pose (i.e., the second portion of the current exercise). In this manner, the determined target breathing pattern may include a first breathing pattern associated with a first portion of the current exercise and a second breathing pattern different from the first breathing pattern and associated with a second portion of the current exercise. As another example, in resistance training, the first portion of the exercise may include lifting (i.e., pushing) a weight, which should be done while exhaling, and the second portion of the exercise may include holding the weight in an elevated position, which should be done while inhaling, immediately prior to a pull-down movement, which is done while holding the breath. During running, swimming, or cycling exercise, different portions of the movement may be associated with different portions of breathing.

Further, the processor may determine a difference between a target breathing pattern appropriate for each of the first and second portions of the current exercise and the user's current breathing pattern during the respective first and second portions of the current exercise. The processor may also provide information to the user 5 including a difference between a target breathing pattern appropriate for each of the first and second portions of the current exercise and the user's current breathing pattern during the respective first and second portions of the current exercise.

In some embodiments, the processor may activate a respiration sensor (i.e., a sensor configured to measure a current respiration pattern or an aspect of a current respiration pattern) in response to determining that a current exercise is being performed by the user 5. For example, the processor may activate one or more sensors in the smart glasses 130 that are configured to measure a current respiration pattern. In this manner, the respiration sensor need not be continuously active, which may conserve power, but once activated, may be configured to monitor the user's current respiration pattern while performing the current exercise.

The user equipment 110, adhesive patch sensor 120, smart glasses 130, and/or smart watch 140 may include other or additional sensors, such as cameras, microphones, IMUs, clocks, electromyographs, gas sensors, pressure sensors, proximity/motion sensors, light sensors, and thermometers. Although three wearable devices 120, 130, 140 are shown in FIG. 1A, various embodiments may include a fewer or greater number of wearable devices and/or remote computing devices, including one or more different types of wearable devices and/or computing devices not shown in the environment 100.

The user device 110 may use conventional functionality, such as a clock/timer, applied to determining what exercise is being performed, the target breathing pattern, or the current breathing pattern, and the clock/timer may provide a measurement of how long each portion of the exercise or breathing pattern lasts, thereby indicating what exercise is being performed, what portion of the exercise is being performed, and/or the user's current breathing pattern.

FIG. 1B illustrates an example 101 in which a user 6 is performing yoga (i.e., an exercise) while various sensors, such as a smart watch 140, a chest band sensor 150, and a camera 117 in the user device 110, provide information useful in determining the current exercise (i.e., the current yoga pose in the illustrated example) as well as measuring the current breathing pattern of the user 6. According to various embodiments, the user device 110 may use this information to determine the difference between a target breathing pattern appropriate for the current yoga pose and the measured breathing pattern.

According to various embodiments, a processor in the user equipment or other computing device may provide information to the user that may help the user properly coordinate their breathing pattern with each movement of an exercise. In some embodiments, the user equipment 110 may provide the user with information regarding a determined difference between the current breathing pattern and the target breathing pattern. This information may be provided to the user 6 via at least one of a visual, an auditory, or a tactile alert. In FIG. 1B, the user equipment 110 issues a verbal instruction (i.e., audible feedback 116) commanding the user 6 to "take a breath." This type of instruction may be useful in encouraging the user to relax and coordinate their breathing with each movement.

According to various embodiments, existing wrist-worn sensors, such as the smartwatch 140, may be improved in many ways to increase value for various exercises. The smartwatch 140 or other wrist-worn sensors may be used for muscle strength measurement and/or respiration tracking. Strength measurement may measure the level of muscle exertion, such as during a challenging isometric yoga pose that requires the user to hold the muscles still and contracted without significant joint movement. Additionally, using one wrist-worn sensor on each arm may improve accuracy for detecting the type of exercise as well as the number of repetitions compared to using only a single wrist-worn sensor on one of the user's two arms.

Each of the smartwatch 140 and the chest band sensor 150 may include a control unit 131, which may include various circuits and devices used to control their operation. In the example shown in FIG. 1B, the control unit 131 includes a processor 132, a memory 133, an input module 134, and an output module 135. Additionally, the control unit 131 may be coupled to a transceiver 138 for transmitting and receiving wireless communications, and coupled to one or more sensors 139. In some embodiments, similar to the smartwatch 140, the chest band sensor 150 may provide feedback to the user 6 via a speaker and/or a haptic feedback device, which may be located on the smartwatch 140, the chest band sensor 150, or both, thereby constituting one or more user interfaces.

FIG. 1C illustrates an environment 102 in which a user 7 is running (i.e., exercising) on a treadmill 160, according to various embodiments, while various sensors, such as sensors within the treadmill 160 (i.e., exercise equipment), including a chest band sensor 150 and a camera (shown as camera imaging angle 167), provide information useful in determining differences between a target breathing pattern appropriate for exercise and the user 7's current breathing pattern.

The treadmill 160 may also include a control unit 131 with a processor 132, a memory 133, an input module 134, and an output module 135 that may render feedback information on a display 165 of the treadmill 160. Additionally, the control unit 131 may be coupled to a transceiver 138 for sending and receiving wireless communications, and coupled to one or more sensors 139. The treadmill 160 provides feedback to the user 7 via a display, a speaker, and/or a haptic feedback device (e.g., a vibrator on or in the handgrip), thereby providing one or more user interfaces.

In some embodiments, the sensor-equipped exercise equipment may include a treadmill, an elliptical machine, a stationary bike, and/or a rowing machine. In this manner, the processor may receive sensor input from an exercise sensor that provides exercise information about a current exercise, the exercise sensor being associated with the exercise equipment being used by the user to perform the current exercise.

FIG. 1D illustrates an environment 103 in which a user 8 is riding (i.e., performing an exercise) on a fitness bike 170, according to various embodiments, while various sensors within the fitness bike 170, including a camera (shown as camera imaging angle 167), provide information useful in determining the difference between a target breathing pattern appropriate for exercise and the current breathing pattern of the user 6.

The exercise bike 170 may also include a control unit 131 with a processor 132, a memory 133, an input module 134, and an output module 135 coupled to a display 175 on which feedback may be displayed. Additionally, the control unit 131 may be coupled to a transceiver 138 for sending and receiving wireless communications, and coupled to one or more sensors 139. The exercise bike 170 provides feedback to the user 8 via a display, a speaker, and/or a haptic feedback device (e.g., a vibrator on or in the handlebars), thereby providing one or more user interfaces.

The various embodiments may be implemented using a number of single-processor and multi-processor computer systems, including systems-on-chips (SOCs) or systems-in-packages (SIPs), in control units within various types of user equipment, computing devices, and other devices. Figure 2 illustrates an exemplary computing system or SIP 200 architecture that may be used in a computing device, such as one or more of the user equipment (e.g., 110) and/or wearable devices (e.g., 130, 150, 170, etc.) that implement various embodiments.

With reference to FIGS. 1A-2, the illustrated exemplary SIP 200 includes two SOCs 202, 204, a clock 206, a voltage regulator 208, and a wireless transceiver 266. In some embodiments, the first SOC 202 operates as a central processing unit (CPU) of the wireless device, implementing the instructions of a software application program by performing arithmetic, logic, control, and input/output (I/O) operations specified by the instructions. In some embodiments, the second SOC 204 may operate as a dedicated processing unit. For example, the second SOC 204 may operate as a dedicated 5G processing unit responsible for managing high-capacity, high-speed (e.g., 5 Gbps, etc.), and/or very short wavelength (e.g., 28 GHz mmWave spectrum, etc.) communications.

The first SOC 202 may include a digital signal processor (DSP) 210, a modem processor 212, a graphics processor 214, an application processor 216, one or more coprocessors 218 (e.g., vector coprocessors) connected to one or more of the processors, memory 220, custom circuitry 222, system components and resources 224, an interconnect/bus module 226, one or more sensors 230 (e.g., thermal sensors, motion sensors, proximity sensors, multimeters, etc.), a thermal management unit 232, and a thermal power envelope (TPE) component 234. The second SOC 204 may include a 5G modem processor 252, a power management unit 254, an interconnect/bus module 264, multiple mmWave transceivers 256, memory 258, and various additional processors 260, such as application processors, packet processors, etc.

Each processor 210, 212, 214, 216, 218, 252, 260 may include one or more cores, and each processor/core may perform operations independent of the other processors/cores. For example, the first SOC 202 may include a processor that runs a first type of operating system (e.g., FreeBSD, LINUX, OS X, etc.) and a processor that runs a second type of operating system (e.g., MICROSOFT WINDOWS® 10). In addition, any or all of the processors 210, 212, 214, 216, 218, 252, 260 may be included as part of a processor cluster architecture (e.g., a synchronous processor cluster architecture, an asynchronous or heterogeneous processor cluster architecture, etc.).

The first SOC 202 and the second SOC 204 may include various system components, resources, and custom circuits for managing sensor data, analog-to-digital conversion, wireless data transmission, and performing other specialized operations, such as processing encoded audio and video signals for decoding data packets and rendering in a web browser. For example, the system components and resources 224 of the first SOC 202 may include power amplifiers, voltage regulators, oscillators, phase-locked loops, peripheral bridges, data controllers, memory controllers, system controllers, access ports, timers, and other similar components used to support processors and software clients running on the wireless device. The system components and resources 224 and/or custom circuits 222 may also include circuits for interfacing with peripheral devices, such as cameras, electronic displays, wireless communication devices, external memory chips, etc.

The first SOC 202 and the second SOC 204 may communicate via an interconnect/bus module 250. The various processors 210, 212, 214, 216, 218 may be interconnected to one or more memory elements 220, system components and resources 224, and custom circuits 222, as well as a thermal management unit 232, via an interconnect/bus module 226. Similarly, the processor 252 may be interconnected to a power management unit 254, an mmWave transceiver 256, a memory 258, and various additional processors 260, via an interconnect/bus module 264. The interconnect/bus modules 226, 250, 264 may include an array of reconfigurable logic gates and/or implement a bus architecture (e.g., CoreConnect, AMBA, etc.). Communication may be by advanced interconnects such as high-performance networks on chips (NoCs).

The first SOC 202 and/or the second SOC 204 may further include input/output modules (not shown) for communicating with resources external to the SOC, such as a clock 206 and a voltage regulator 208. Resources external to the SOC (e.g., clock 206, voltage regulator 208) may be shared by two or more of the internal SOC processors/cores.

Various embodiments may be implemented in a wide variety of computing systems, in addition to the exemplary SIP 200 described above, and the computing system may include a single processor, multiple processors, a multi-core processor, or any combination thereof.

In some embodiments, only one SOC (e.g., 132, 202) may be used in a less capable computing device, such as a wearable device (e.g., 130, 150, 170, etc.) that is configured to provide sensor information to a more capable user equipment, such as a smartphone (e.g., UE 110). In such embodiments, the communication capabilities of the wearable device (e.g., 130, 150, 170, etc.) may be limited to a short-range communication link, such as Bluetooth or Wi-Fi, in which case the 5G-enabled SOC 204 may not be included in the processing system of the wearable device.

As used herein, terms such as "component," "system," "unit," "module," and the like include computer-related entities, such as, but not limited to, hardware, firmware, a combination of hardware and software, software, or software in execution, configured to perform a particular operation or function. For example, a component may be, but is not limited to, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a communication device and the communication device may be referred to as a component. One or more components may reside within a process and/or thread of execution, and a component may be localized on one processor or core and/or distributed among two or more processors or cores. In addition, these components may execute from various non-transitory computer-readable media having various instructions and/or data structures stored thereon. Components may communicate by way of local and/or remote processes, function or procedure calls, electronic signals, data packets, memory read/write, and other computer, processor, and/or process related communication methods known.

Figure 3 is a component block diagram illustrating a system 300 configured to provide information about a user's breathing pattern executed by a processor of a computing device, according to various embodiments. With reference to Figures 1A-3, the system 300 may include a user equipment 110 and may be configured to communicate with one or more remote devices 315 (e.g., 120, 130, 140, 150, 160, 170 in Figures 1A-1D) or other computing devices via a local wireless connection 50 (e.g., Wi-Fi, Bluetooth, Ant, etc.) or other NFC communication techniques. The user equipment 110 may be configured to communicate with an external resource 320 (e.g., a server 195) via a wireless connection 50 with a wireless network 190, such as a cellular wireless communication network.

User equipment 110 may include electronic storage 325, one or more processors 330, wireless transceiver 266, and other components. User equipment 110 may include communication lines or ports to enable exchange of information with networks and/or other computing platforms. The illustration of user equipment 110 in FIG. 3 is not intended to be limiting. User equipment 110 may include multiple hardware, software, and/or firmware components that operate together to provide the functionality attributed to user equipment 110 herein.

Electronic storage 325 may include non-transitory storage media that electronically store information. The electronic storage media of electronic storage 325 may include one or both of system storage that is integral with user equipment 110 (i.e., substantially non-removable) and/or removable storage that is removably connectable to user equipment 110, for example, via a port (e.g., a Universal Serial Bus (USB) port, a Firewire port, etc.) or a drive (e.g., a disk drive, etc.). Electronic storage 325 may include one or more of optically readable storage media (e.g., optical disks, etc.), magnetically readable storage media (e.g., magnetic tape, magnetic hard drives, floppy drives, etc.), charge-based storage media (e.g., EEPROM, RAM, etc.), solid-state storage media (e.g., flash drives, etc.), and/or other electronically readable storage media. Electronic storage 325 may include one or more virtual storage resources (e.g., cloud storage, virtual private networks, and/or other virtual storage resources). The electronic storage 325 may store software algorithms, information determined by the processor 330, information received from the user equipment 110, information received from the remote platform 304, and/or other information that enables the user equipment 110 to function as described herein.

The processor 330 may include one or more processors (e.g., 210, 212, 214, 216, 218, 252, 260), which may be configured to provide information processing functionality in the user equipment 110. Thus, the processor 330 may include one or more of a digital processor, an analog processor, a digital circuit designed to process information, an analog circuit designed to process information, a state machine, and/or other mechanisms for electronically processing information. Although the processor 330 is shown in FIG. 3 as a single entity, this is for illustrative purposes only. In some embodiments, the processor 330 may include multiple processing units. These processing units may be physically located within the same device, or the processor 330 may represent the processing functionality of multiple devices operating in concert.

The user device 110 may be configured with machine-readable instructions 335, which may include one or more instruction modules. The instruction modules may include computer program modules. In particular, the instruction modules may include one or more of a sensor/manual input receiving module 340, a context information receiving module 345, a body motion analysis module 350, a current exercise determination module 355, a target breathing pattern determination module 360, a sensor activation module 365, a current breathing pattern monitoring module 370, a normal breathing pattern determination module 375, a breathing pattern difference determination module 380, a user information delivery module 385, and/or other instruction modules.

The sensor/manual input receiving module 340 may be configured to receive sensor input from one or more sensors (e.g., adhesive patch sensor 120, smart glasses 130, smart watch 140, chest band sensor 150, exercise equipment 160, 170, etc.) that communicate information to the user equipment (e.g., 110) and/or to a remote computing device 315 (e.g., smart glasses 130, smart watch 140, chest band sensor 150, exercise equipment 160, 170, etc.) within the vicinity of the user equipment 110. The processor may then determine a current exercise being performed by the user and/or a target breathing pattern appropriate for the current exercise being performed by the user based on the received sensor input. The sensor may detect the user performing a type of action associated with one or more particular exercises and/or may detect the user's current breathing pattern. As non-limiting examples, the sensor information may be obtained from a camera, a lidar, a light sensor, a microphone, an IMU, an electromyograph, a pressure sensor, and/or a proximity/motion sensor. The camera and lidar may detect movement associated with a particular exercise and/or equipment and/or accessories associated with a particular exercise. The microphone may detect a current breathing pattern. The IMU may detect movement associated with a particular exercise. The electromyograph may detect muscle movement and/or activation associated with a particular exercise, as well as muscle movement associated with a current breathing pattern.

Additionally, the sensor/manual input receiving module 340 may be configured to receive manual input from a user or other operator regarding at least one of the current exercise or the target breathing pattern. For example, a user may manually enter or select instructions regarding what exercise is being performed. Similarly, a user may manually enter or select a desired target breathing pattern. In this manner, the current exercise and/or the target breathing pattern may be determined based on the received manual input.

The user equipment processor 330 may receive sensor information directly from on-board sensors and/or may use one or more transceivers (e.g., 256, 266) to detect available wireless connections 50 (e.g., Wi-Fi, Bluetooth, cellular, etc.) to obtain sensor information from remote sensors. The sensor/manual input receiving module 340 may also be configured to determine whether a detected communication link is available to the wearable equipment or other remote computing device.

The context information receiving module 345 may be configured to receive context information indicative of the context in which the user is performing the current exercise, taking into account available information regarding the environment and/or conditions in which the user is performing the exercise in its entirety. In that case, the determined target breathing pattern may be further based on the received context information. For example, a thermometer may indicate that the user is performing the exercise in an extremely cold or hot environment. Similarly, a thermometer may be used to determine the user's body temperature, and may indicate that if the user's body temperature is too high, a lower target breathing pattern should be selected to reduce the intensity of the current exercise, which may help cool the user's body. In addition, the context information may include information regarding the environment (e.g., humidity, air pressure), the time of day, or the user's activity level or health, which may affect the determination of the target breathing pattern. Furthermore, the context information may include information from a user input or other sources, such as the user's age, sex, gender, weight, exercise experience or at least the current execution of the exercise, and/or the user's current health condition. In some embodiments, the received context information may indicate the context in which the user is performing the current exercise. Thus, the determined target breathing pattern may be further based on the received context information.

As non-limiting examples, a camera and/or lidar may collect images identifying lighting conditions or other elements of the surrounding environment, a thermometer may detect the ambient temperature, a microphone may collect audio (e.g., current breathing patterns, coughs, sneezes, etc.), and an electromyograph may collect indications of muscle movement (e.g., associated with exercise). Thus, contextual information may be received from sensors that provide information to the user equipment (e.g., 110) and/or a local computing device within the vicinity of the user equipment 110.

The context information receiving module 345 may also access a database containing one or more data records stored in memory (e.g., 220, 258, 325) or from a remote source such as a remote system (e.g., 315) or external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components to determine the context information. A processor of the user equipment may access the data records to compare the data received from the sensor with pre-stored information regarding the sensor data to determine what the received sensor indication information represents. For example, a look-up table may provide information used to determine an appropriate target breathing pattern corresponding to the current temperature, pressure, and/or humidity conditions.

The body motion analysis module 350 may be configured to determine the extent, type, and/or speed of the body motion the user is performing based on the sensor or manual input received from the sensor/manual input receiving module 340. The user's body motion may be useful in detecting not only what exercise the user is performing, but more specifically what part of the exercise the user is performing. Many exercises have multiple parts, each part having a different motion that may be associated with a different breathing pattern. In this manner, the received user body motion information may indicate which part of the exercise the user is currently performing. Furthermore, the user's body motion may provide information directly related to the user's current breathing pattern. Circulatory motion of the user's chest, abdomen, and/or nostrils may generally be correlated with the user's breathing rate or the depth of such breathing. Furthermore, how the user is breathing may be determined based on several sensor inputs, such as whether the user is diaphragmatically breathing or pulmonary breathing.

Furthermore, the analysis of the user's physical motion may determine what portions of the user's physical motion, apart from breathing, may be due to the determined current exercise, and what portions of the user's physical motion, apart from motion related to the current exercise, may be due to breathing. For example, the user's chest may rise and fall when the user runs, jumps, or performs other motions that are a natural part of a given exercise, but such exercise motions may be distinguished from the inhalation or exhalation motion of the user's chest that is a natural part of breathing. By storing historical respiration measurement data, the user's general chest motion for the determined exercise may be recognized by the physical motion analysis module 350. Thus, the physical motion analysis module 350 may compare the user's current chest motions with those general chest motions to identify improper or abnormal breathing patterns.

A user generally benefits from being provided with feedback regarding proper form and breathing during an exercise. For example, proper form in yoga involves not only muscle activity but also body alignment and breathing in particular, and consistent practice is required to achieve breathing. Similarly, analysis of the body movement by the body movement analysis module 350 may help ensure that the user safely and effectively performs strength training exercises, such as by providing feedback to the user to help them perform the exercise using only muscles that should/are firing upon completion of a repetition of the exercise. Tracking of the user's progress toward optimal alignment over time may be used to reinforce/maintain the user's motivation to perform the exercise regularly. Performing an exercise with improper form may in some cases make the exercise overly easy or may cause the user to injure themselves. Body alignment may be determined as part of the body movement analysis by the body movement analysis module 350. Additionally, if the user is using muscles that should not be exposed to a certain intensity, the user benefits from the body movement analysis module 350 providing real-time feedback on how to improve their form for a more effective and safer exercise. As non-limiting examples, a camera and/or a lidar may collect images identifying body movements, and/or an electromyograph may collect indications of muscle movements (e.g., associated with an exercise) that may be analyzed by the body movement analysis module 350.

Furthermore, muscle strength during a lifting exercise may be determined by the body motion analysis module 350 by using an IMU or a wearable camera such as smart glasses (e.g., 130) to measure the relative speed of the lift over a single repetition, set, or workout. The speed of the concentric portion of the lift may be used by the body motion analysis module 350 as a measure of muscle strength and may be used for tracking and guidance (in combination with heart rate data) on when to increase weight or repetition. Similarly, the body motion analysis may be used by the body motion analysis module 350 to reduce the weight the user (e.g., 5) is using for an exercise if the muscle strength measurement indicates that the weight is too heavy. Lower muscle strength indicates that the user is overtraining and needs to increase rest between workouts or sets. The muscle strength measurement by the body motion analysis module 350 may be provided audibly to the user after each repetition, and the user can apply the information to guide their own movements during the exercise.

As a non-limiting example, the physical motion information may be received by the physical motion analysis module 350 from a sensor that provides information to the user equipment (e.g., 110) and/or a local computing device (e.g., adhesive patch sensor 120, smart glasses 130, smart watch 140, chest band sensor 150, exercise equipment 160, 170, etc.) within the vicinity of the user equipment 110. The physical motion analysis module 350 may also analyze the physical motion information by accessing a database that includes one or more data records stored in a local memory (e.g., 220, 258, 325) or from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

The current exercise determination module 355 may be configured to determine a current exercise being performed by a user. In some embodiments, the current exercise may be determined based on a determination from the body motion analysis module 350. In some other embodiments, the current exercise may be determined by the current exercise determination module 355 based on manual user input. In some embodiments, the current exercise may be determined by the current exercise determination module 355 based on input from exercise equipment (e.g., 160, 170) dedicated to a particular type of exercise. In some embodiments, the current exercise may be determined by the current exercise determination module 355 based on a combination of body motion analysis, manual user input, and/or input from exercise equipment or sensors.

The determination regarding the current exercise becomes more reliable after an initial calibration of the current exercise determination module 355, which identifies the exercise. Thus, the user may be prompted to input, describe, select, and/or perform a particular exercise during the calibration of the current exercise determination module 355. During its initial calibration, the user equipment may process information received from various sensors and calibrate or correlate the information with the prescribed exercise. The sensor data collected during the initial calibration may be used by the current exercise determination module 355 to automatically identify the exercise when the exercise is later performed again by the user. For example, the processor of the user equipment may record and/or analyze sensor data received while the user performs a particular exercise and correlate the various sensor readings with the exercise. The calibration process may enable the processor to later correlate similar sensor data with the prescribed exercise. After the calibration process is completed, the results may be stored in memory in the form of a lookup table, which the processor may use to determine what exercise is being performed.

Alternatively, or in addition, the processor may then, in response to detecting a recognized exercise from the calibration process, use long-term sensor readings associated with the exercise to more accurately identify the exercise in the future after the exercise has been confirmed by the user. The processor may alternatively maintain a moving average of sensor readings associated with the exercise and prompt the user when the moving average changes beyond a threshold. The prompt may request the user to confirm the calculated estimate (i.e., estimate) for the exercise being performed to obtain feedback and provide further calibration to generate updates to the previously determined sensor readings associated with the exercise. Various embodiments may apply machine learning to determine updates that may be made from time to time to identify a user's habits or tendencies with respect to certain exercises at certain times of the day or days of the week, which may be useful in determining what exercises are being performed. The processor may correlate contextual information with the determined updates. For example, circumstances in which a user has a fever, is sweating more than normal, is unusually active, or the exercise is taking place on a hot or very cold day may be correlated with determined updates for future occurrences of similar environments.

The initial calibration of the current exercise determination module 355 may require the user to wear one or more additional sensors that may not be needed to subsequently detect the exercise. By using multiple types of sensors during the initial calibration, the processor may subsequently identify the exercise when the user is wearing fewer than all of those sensors. In this way, the user may avoid wearing all of the calibration sensors every time they perform an exercise.

As a non-limiting example, the user equipment processor 330 may use active and/or passive calibration techniques to determine the current exercise being performed by the user. Manual input of instructions for the exercise being performed may be useful in identifying the exercise at a later time, particularly during an initial calibration process. However, also or alternatively, automatic detection of the current exercise by a sensor may be used in the initial calibration process to determine baseline parameters that identify the exercise as it is performed by a particular user. Additionally, the baseline parameters may take into account contextual factors that may be affecting the detection of the exercise, such as temperature, environment, time of day, or information about the user's activity level, age, sex, weight, or health condition (e.g., diabetes).

The current exercise determination module 355 may receive information from sensors and/or access a database containing one or more data records to determine the current exercise. The records may be stored in a local memory (e.g., 220, 258, 325) or may be received from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. The sensors may be part of the user equipment as well or may be received from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

The target breathing pattern determination module 360 may be configured to determine a target breathing pattern appropriate for a current exercise being performed by the user. For example, a look-up table may provide information used to determine an appropriate target breathing pattern corresponding to a current exercise being performed by the user. The determined target breathing pattern may include a first breathing pattern associated with a first portion of the current exercise and a second breathing pattern different from the first breathing pattern and associated with a second portion of the current exercise. In some embodiments, three or more different breathing patterns may be associated with the exercise. In some embodiments, the target breathing pattern may be based on sensor input received from an exercise sensor that indicates how the user is moving during the exercise. In some embodiments, the target breathing pattern may be determined based on the context (i.e., context information) of the exercise being performed (e.g., obtained by the context information receiving module 345). Also, in some aspects, the target breathing pattern may be based on information provided by the user via a user interface, such as the user's body type, health goals, or experience level performing the current exercise.

Additionally, the processor may receive input from a user indicating that the target breathing pattern requires an update. For example, after a user is provided with information regarding a determined target breathing pattern, the user may feel that the proposed target breathing pattern is too challenging rather than challenging enough, or that it may need to be changed. In response to receiving user input indicating that the user desires to change the target breathing pattern, the processor may recalculate the target breathing pattern, possibly with further input from the user.

Alternatively, after receiving input from the sensor indicating the user's current breathing pattern, or other biometric readings of the user exceed a threshold, the processor may determine and provide to the user a new target breathing pattern that may be safer for the user. For example, the dangerous breathing threshold may be a value when the user is breathing less than 12 breaths per minute or more than 25 breaths per minute for very light exercise, or a relatively high breathing rate for other exercise requiring more strenuous exertion. Conditions that may alter a user's normal breathing rate include asthma, anxiety, pneumonia, congestive heart failure, lung disease, narcotic use, or drug overdose.

As a non-limiting example, the processor 330 of the user equipment 110 may determine the target breathing pattern by accessing a database, such as a look-up table, that includes one or more records. The records may be stored in a local memory (e.g., 220, 258, 325) or received from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. The records may be maintained on the user equipment or received from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

The sensor activation module 365 may be configured to activate one or more particular sensors in response to a number of conditions. In some embodiments, a respiration sensor configured to determine a user's current breathing pattern may be activated in response to the processor determining that the user is performing an exercise. Additional sensors may be required due to the characteristics of the exercise. Alternatively, additional sensors may be required so that the exhalation sensor can be kept as inactive as possible (i.e., when the user is not performing an exercise). In some embodiments, the additional sensors may be activated in response to the user's current breathing pattern meeting a predetermined threshold. For example, if the user's breathing pattern falls below a low threshold or exceeds a high threshold, the processor may activate the additional sensors to confirm the detected low/high breathing pattern. In some embodiments, a biosensor configured to measure the user's vital signs may be activated in response to the user's current breathing pattern meeting a predetermined threshold (e.g., a low or high breathing threshold).

As a non-limiting example, the additionally activated sensors may include one or more sensors in the user equipment 110 and/or one or more sensors in the remote device 315 (e.g., 120, 130, 140, 150, 160, 170 in Figures 1A-1D).

The current breathing pattern monitoring module 370 may be configured to monitor the user's current breathing pattern while performing the current exercise based on input from a breathing sensor. The breathing sensor may be any one or more sensors configured to detect characteristics of the user's breathing, such as the breathing rate, depth, timing, and consistency of the user's breathing. In some embodiments, the current breathing pattern may be monitored by regular or continuous measurements obtained from the body motion analysis module 350. In some embodiments, the current breathing pattern may be determined based on input from exercise equipment (e.g., 160, 170) dedicated to a particular type of exercise or other sensors (e.g., 120, 130, 140, 150). In some embodiments, the current breathing pattern may be determined based on a combination of body motion analysis and/or input from exercise equipment or other sensors.

Various embodiments include devices that may be configured to more accurately measure and track a user's breathing patterns by creating, maintaining, and using a baseline breathing pattern for the individual under various conditions. For example, controlled breathing pattern measurements may be obtained and recorded for an individual, possibly through a calibration or learning process, under various circumstances (e.g., varying temperature, time of day, type of activity, etc.), where the user breathes normally for a predetermined period of time and sensors calculate one or more breathing patterns, such as breathing rate, rhythm, and/or quality of breathing. Such controlled breathing measurements use the user's active participation and input, and are therefore referred to herein as "active baselining." Active baselining may be particularly useful in initially determining a user's regular breathing pattern. Active baselining may also help identify conditions in which the user's breathing is irregular, or may provide an early warning of developing health problems. For example, a user's increased breathing intensity with only low levels of physical exertion may indicate a respiratory or cardiac problem.

A processor implementing various embodiments may compare the user's currently detected breathing pattern to a target breathing pattern without using a predetermined baseline breathing pattern and without considering the baseline breathing pattern. Furthermore, when the processor receives reconfirmation (e.g., from a redundant sensor) that the sensor readings accurately measure the current breathing pattern, the measured breathing pattern may be used to determine, verify, and/or update the baseline breathing pattern without the user manually or actively inputting information about it, referred to herein as "passive baselining." Passive baselining may be useful in situations where a sensor can reliably measure and determine the user's current breathing pattern. In this manner, after an active baseline is established for the user, passive baselining may allow for continuous calibration or adjustment of the baseline to more accurately estimate the user's breathing pattern.

As a non-limiting example, the user's current breathing pattern may be monitored and determined from the body motion analysis module 350. The current breathing pattern may also be determined by information received from sensors providing information to the user equipment (e.g., 110) and/or local computing devices within the vicinity of the user equipment 110 (e.g., adhesive patch sensor 120, smart glasses 130, smart watch 140, chest band sensor 150, exercise equipment 160, 170, etc.).

The current breathing pattern monitoring module 370 may also receive breathing pattern information by accessing a database containing one or more data records stored in a local memory (e.g., 220, 258, 325) or from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. Additionally, the current breathing pattern monitoring module 370 may store determined values of the user's current breathing pattern in a local memory (e.g., 220, 258, 325) or in a memory of a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

The normal breathing pattern determination module 375 may be configured to determine when a user's current breathing pattern is likely within the user's normal range. A breathing pattern outside of the normal range (i.e., an abnormal breathing pattern) may be dangerous to the user's health and/or may require the initiation of additional action by the processor. Detecting an abnormal breathing pattern may trigger the provision of additional information to the user, such as further prompting or additional instructions regarding breathing or exercise movements. A significantly abnormal breathing pattern may be an indication of a health risk to the user. For example, the processor may receive an input indicating a breathing rate below 12 or above 25 breaths per minute while the user is performing very light exercise, or an input indicating a relatively high breathing rate for other exercises requiring more strenuous exercise. Similarly, a sudden increase in the frequency of the breathing pattern or an irregular breathing pattern may be considered abnormal or dangerous to the user. A device implementing some embodiments may be configured to constantly monitor and promote stable breathing appropriate to the user and the current activity (e.g., a particular exercise), or attempt to prevent the user from developing a dangerous breathing pattern by recommending a different cadence or other change in the movement or breathing associated with the exercise.

As a non-limiting example, the processor 330 of the user equipment 110 may determine when the user's current breathing pattern is considered normal by accessing a database that includes one or more data records, such as a look-up table, that indicate what breathing patterns or individual parameters of the breathing pattern are risky for this particular user. The records may be stored in a local memory (e.g., 220, 258, 325) or received from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. The records may be maintained on the user equipment or received from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

The breathing pattern difference determination module 380 may be configured to determine a difference between the target breathing pattern determined by the target breathing pattern determination module 360 and the user's current breathing pattern determined by the current breathing pattern monitoring module 370. In some embodiments, determining the difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern may include comparing at least one of a breathing rate, rhythm, and/or quality of the user's current breathing pattern and the determined breathing rate, rhythm, and/or quality of the user's breathing when the user previously performed the current exercise. In some embodiments, determining the difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern may include determining the difference between the target breathing pattern appropriate for the first and second portions of the current exercise and the user's current breathing pattern during the first and second portions of the current exercise.

As a non-limiting example, the user equipment processor 330 may calculate the difference determined by the breathing pattern difference determination module 380. The difference may be reflected in a different breathing rate, rhythm, or quality of breathing. Additionally, the user equipment processor 330 may transmit the determined difference to a remote computing device (e.g., 120, 130, 140) using one or more transceivers (e.g., 256, 266), along with instructions on what to do with the information.

The user information delivery module 385 may be configured to provide the user with information regarding the difference determined by the breathing pattern difference determination module 380 between a target breathing pattern appropriate for a current exercise being performed by the user and the user's current breathing pattern. In some embodiments, the information provided to the user may include the difference between a target breathing pattern appropriate for the first and second portions of the current exercise and the user's current breathing pattern during the first and second portions of the current exercise. In some embodiments, the user may be provided with additional information regarding another target breathing pattern determined in response to the current breathing pattern exceeding a normal breathing threshold.

The information provided to the user regarding the determined difference between the target breathing pattern and the current breathing pattern may include an actual measurement of the breathing rate, volume, and/or stability of the user's breathing relative to the target breathing pattern. The provided information may be communicated to the user via a display (e.g., 115) on the user equipment (e.g., 110). Alternatively, or in addition, the provided information may be transmitted to a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. For example, the processor may generate text or render an image on a display of the user equipment to provide an alert message regarding the user's breathing pattern during exercise. In particular, the alert message may instruct the user to regulate their breathing, prompt the user to synchronize their breathing with certain exercise movements, or prompt the user not to hold their breath. Alternatively, the processor may transmit information to the remote computing device configured to cause the remote computing device to perform a notification function on behalf of the user equipment.

In addition to providing the user with feedback on how or when to perform each portion of the exercise, the system may provide a score on how well the user's breathing matched the specified motion of the exercise. Alternatively, the system may provide a score on how closely the user matched a target breathing pattern. This feedback may be provided after the exercise is completed, or may be provided as breathing reminders or reminders on how and/or when to breathe during the session. Similarly, in the case of weight training, the feedback provided may measure whether the user is inhaling on the eccentric portion of the lift and exhaling on the concentric portion of the lift and provide appropriate feedback.

After receiving input from the sensors indicating that the user's current breathing pattern or other biometric readings of the user have exceeded a threshold, a display and/or audio output from the system may recommend a user-modified exercise pattern, such as changing cadence while running (e.g., changing the number of steps between breaths) or cadence while biking (e.g., changing the number of pedal revolutions per minute) to determine a more appropriate target breathing pattern. If the user follows the suggested change in exercise pattern but the user's breathing pattern continues to exceed the threshold or exceeds the threshold for a predetermined percentage of the time (e.g., 80%), the system may alert the user to a potential problem and/or advise the user to rest.

As a non-limiting example, the processor 330 of the user equipment 110 may report the determined breathing pattern differences to the user using a display (e.g., 115) and/or speaker. Additionally, the processor 330 of the user equipment 110 may transmit the determined breathing pattern differences to a remote computing device (e.g., 120, 130, 140) using one or more transceivers (e.g., 256, 266), along with instructions regarding how, when, and/or under what circumstances the remote computing device notification function to the user may be performed.

The remote computing device 315 may include one or more processors configured to execute computer program modules similar to those in the machine-readable instructions 335 described above. As non-limiting examples, the remote computing device may include one or more of a smart ring, a smart appliance, a desktop computer, a laptop computer, a handheld computer, a tablet computing platform, a netbook, another smartphone, a gaming console, and/or other computing devices, in addition to the wearable devices (e.g., 120, 130, 140, 150) described above.

External resources 320 may include remote servers storing lookup tables in a database (backup copies of lookup databases), information sources external to system 300, external entities participating in system 300, and/or other resources. In some embodiments, some or all of the functionality attributed to external resources 320 herein may be provided by resources included within system 300.

The processor 330 may be configured to execute modules 340, 345, 350, 355, 360, 365, 370, 375, 380, and/or 385, and/or other modules. The processor 330 may be configured to execute modules 340, 345, 350, 355, 360, 365, 370, 375, 380, and/or 385, and/or other modules by software, hardware, firmware, some combination of software, hardware, and/or firmware, and/or other mechanisms for configuring processing power on the processor 330. As used herein, the term "module" may refer to any component or set of components that performs the function attributed to a module. This may include one or more physical processors in execution of processor-readable instructions, processor-readable instructions, circuitry, hardware, storage media, or any other component.

The following description of the functionality provided by the various modules 340, 345, 350, 355, 360, 365, 370, 375, 380, and/or 385 is for illustrative purposes and is not intended to be limiting, as any of the modules 340, 345, 350, 355, 360, 365, 370, 375, 380, and/or 385 may provide more or less functionality than described. For example, one or more of the modules 340, 345, 350, 355, 360, 365, 370, 375, 380, and/or 385 may be removed and some or all of its functionality may be provided by other of the modules 340, 345, 350, 355, 360, 365, 370, 375, 380, and/or 385. As another example, the processor 330 may be configured to execute one or more additional modules that may perform some or all of the functionality attributed below to one of modules 340, 345, 350, 355, 360, 365, 370, 375, 380, and/or 385.

Figure 4A illustrates a method 400 that may be performed by a processor of a user equipment and/or one or more other computing devices to provide respiratory feedback to improve activity performance, according to various embodiments. Figures 4B, 4C, 4D, 4E, 4F, 4G, 4H, and/or 4I illustrate additional or alternative operations in methods 401, 402, 403, 404, 405, 406, 407, 408, and 409 that may be performed as part of method 400 in some embodiments. The operations of methods 400, 401, 402, 403, 404, 405, 406, 407, 408, and 409 are exemplary. In some embodiments, methods 400, 401, 402, 403, 404, 405, 406, 407, 408, and 409 may be accomplished with one or more additional operations not described and/or without one or more of the operations described. Additionally, the order in which the operations of methods 400, 401, 402, 403, 404, 405, 406, 407, 408, and 409 are illustrated in Figures 4A, 4B, 4C, 4D, 4E, 4F, 4G, 4H, 4I, and 4J and described below is not intended to be limiting.

1A-1J, methods 400, 401, 402, 403, 404, 405, 406, 407, 408, and 409 may be implemented in one or more processors (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) of a user equipment (e.g., 110) and/or one or more other computing devices, including wearable equipment (e.g., 130, 140, 150) and/or exercise equipment (e.g., 160, 170) on which the processor-executable instructions stored on a non-transitory processor-readable storage medium are configured. The one or more processors may include one or more devices configured via hardware, firmware, and/or software specifically designed to perform one or more of the operations of the methods.

FIG. 4A illustrates a method 400 in which a processor in a user device may provide information regarding a user's breathing patterns during exercise, according to one or more embodiments.

In block 420, the processor of the user equipment may perform operations including determining a current exercise being performed by the user. To make the determination in block 420, the processor may use a body movement analysis module (e.g., 350) and/or a current exercise determination module (e.g., 355). Also in block 420, the processor may access a database including one or more data records stored in a local memory (e.g., 220, 258) or from a remote source such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. The database may provide information regarding known exercises, as well as movements associated with those exercises. The means for performing the operations of block 420 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), or may be from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

In block 422, the processor of the user equipment may perform operations including determining a target breathing pattern appropriate for a current exercise being performed by the user. To perform the operations in block 422, the processor may use a target breathing pattern determination module (e.g., 360). Also in block 422, the processor may access a database including one or more data records stored in a local memory (e.g., 220, 258) or from a remote source such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. The database may provide information regarding the target breathing pattern, as well as the exercise associated with the target breathing pattern. The means for performing the operations of block 422 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), or may be from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

In block 424, the processor of the user equipment may perform operations including monitoring the user's current breathing pattern while performing the current exercise based on input from the breathing sensor. To perform the operations in block 424, the processor may use a current breathing pattern monitoring module (e.g., 370). Also in block 424, the processor may receive input regarding the user's current breathing pattern from sensors included in the user equipment (e.g., 110), devices including sensors (e.g., 120, 130, 140, 150), and/or exercise equipment (e.g., 160, 170). The means for performing the operations of block 424 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), and one or more devices (e.g., 110, 120, 130, 140, 150, 160, 170) including a sensor. Other means for performing the operations of block 424 may include a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

In block 426, the processor of the user equipment may perform operations including determining a difference between a target breathing pattern appropriate for a current exercise being performed by the user and the user's current breathing pattern. To perform the operations in block 426, the processor may use a breathing pattern difference determination module (e.g., 380). Also in block 426, the processor may access a database including one or more data records stored in a local memory (e.g., 220, 258) or from a remote source such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. The database may provide information regarding the target breathing pattern, the current breathing pattern and/or other breathing patterns, as well as exercises associated with those breathing patterns. The means for performing the operations of block 426 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), or may be from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

In block 428, the processor of the user equipment may perform operations including providing the user with information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern. To perform the operations in block 428, the processor may use a user information delivery module (e.g., 385). Also in block 428, the processor may cause a display (e.g., 115) to show information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern. The information regarding the determined difference may take the form of a message to the user (e.g., "take a breath"). Additionally or alternatively, the processor may initiate an audible alert, a flash, or a flicker light, and/or cause a vibration to alert the user in block 428. Additionally or alternatively, the processor may instruct the remote computing device to display an indication of the determined difference in breathing pattern (current breathing pattern vs. target breathing pattern). The means for performing the operations of block 428 may include a speaker, a vibration device, a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), or may be from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

Providing information about the difference between the user's current breathing pattern and the target breathing pattern may help the user achieve the target breathing pattern and obtain additional benefit from the current exercise. For example, if the processor prompts the user to regulate their breathing, it may maximize the benefit of the exercise the user is performing if the user complies.

The operations of method 400 may be repeated, such as when changing a current exercise or changing a user's current breathing pattern.

FIG. 4B illustrates a method 401 in which a processor may provide information regarding a user's breathing pattern during exercise. In block 430, the processor may receive sensor input from an exercise sensor that provides information regarding the user's physical motion, and the determined current exercise in block 420 may be based on the sensor input received from the exercise sensor. For example, the processor may recognize a movement of the user's arm or hand from a first position near the user's chest (see position A in FIG. 1A) to a second position where the arm is extended away from the chest (see position B in FIG. 1A) from a motion sensor input received from the smart watch 140. Such physical motion information may enable the processor to determine that the user is performing a barbell bench press (as shown in FIG. 1A). Similarly, an image of the bar 92 and weights 94 from a camera image received from the smart glasses (e.g., 130) may reinforce the conclusion by the processor that the user is performing a barbell bench press. Similarly, the processor may recognize yoga movements/poses from camera images received from a camera of the user equipment (e.g., 110) and therefore determine that the user is performing yoga (as shown in FIG. 1B). As another example, a processor receiving sensor input from an exercise sensor may recognize the speed and/or type of movement in one or more parts of the body associated with a particular exercise. In this manner, a biking motion and/or its cadence, a running motion and/or its stride rate/step length, or a swimming motion and/or its stroke rate/length may be determined. In some embodiments, the target breathing pattern (e.g., determined in block 422) may be based on sensor input received from an exercise sensor that indicates how the user is moving during the exercise.

To perform the operations in block 430, the processor may use the sensor/manual input receiving module 340. The means for performing the operations in block 430 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), as well as a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

Following the operations at block 430, the processor may perform the operations at block 420 of method 400 as described.

FIG. 4C illustrates a method 402 in which a processor may provide information regarding a user's breathing pattern during exercise. In block 432, the processor may receive sensor input from an exercise sensor that provides exercise information regarding a current exercise, the exercise sensor being associated with the exercise equipment being used by the user to perform the current exercise. For example, the processor may recognize that the user is running on a treadmill from a message received from a closely proximate treadmill (e.g., 160) indicating that the user is running on the treadmill. Alternatively, the processor may receive a camera image received from a camera included in the treadmill (e.g., 160) and thus determine that the user is running. As another example, the processor may recognize that the user is exercising on a stationary exercise bike (e.g., 170) from a wireless communication link (e.g., 50) between the user equipment (e.g., 110) and the stationary exercise bike. The processor may determine that the user is pedaling the stationary exercise bike based on the wireless communication link. Alternatively, the processor may receive camera images from a camera included in a stationary exercise bike (e.g., 170) and therefore determine that the user is pedaling the exercise bike.

To perform the operations in block 432, the processor may use the sensor/manual input receiving module 340. The means for performing the operations of block 430 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), and a remote source such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and related components.

Following the operations at block 432, the processor may perform the operations at block 420 of method 400 as described.

FIG. 4D illustrates a method 403 in which the processor may provide information regarding the user's breathing pattern during exercise. In block 434, the processor may receive sensor input from an exercise sensor that provides exercise information regarding the current exercise, the exercise sensor being associated with the exercise equipment being used by the user to perform the current exercise. For example, the processor may recognize when the user is performing different portions of the exercise from camera images received from the smart glasses 130 or from a motion sensor or gyro input received from the smart watch 140. The entire exercise may be a barbell bench press, but one portion of the exercise may include the user pushing the barbell away from his or her chest (e.g., from position A to position B in FIG. 1A). A second portion of the exercise may include the user lowering the barbell from a raised position to a lowered position (e.g., from position B to position A in FIG. 1A). Such physical motion information may enable the processor to associate different breathing patterns with different portions of the exercise.

To perform the operations in block 434, the processor may use the sensor/manual input receiving module 340. The means for performing the operations of block 430 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), and a remote source such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and related components.

Following the operations at block 434, the processor may perform the operations at block 420 of method 400 as described.

FIG. 4E illustrates a method 404 in which a processor may provide information regarding a user's breathing pattern during exercise. In block 436, the processor may receive a manual user input regarding at least one of the current exercise or the target breathing pattern, and determining the target breathing pattern is further based on the received manual user input. For example, the processor may receive a manual input entered into a treadmill (e.g., 160) or exercise bike (e.g., 170) indicating what exercise the user is performing. Alternatively, the processor may receive a manual input entered into a user device (e.g., 110) or a wearable device such as a smart watch (e.g., 140) indicating that the user wants to attempt to maintain an inefficient target breathing pattern (e.g., 15% faster than an optimal efficient breathing pattern) while performing the current exercise.

To perform the operations in block 436, the processor may use the sensor/manual input receiving module 340. The means for performing the operations of block 430 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), and a remote source such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

Following the operations at block 434, the processor may perform the operations at block 420 of method 400 as described.

FIG. 4F illustrates a method 405 in which a processor in a user equipment may receive context information and use the context information to select a target breathing pattern, according to some embodiments.

In block 438, following the operations in block 420, the processor of the user equipment may perform operations including receiving context information indicating a context in which the user is performing the current exercise, and determining the target breathing pattern is further based on the received context information. For example, the processor may receive a sensor input from a thermometer in the user's smartwatch (e.g., 140), which indicates that the user's body temperature is high. In this manner, the processor may select a low target breathing pattern that gives the user's body an opportunity to recover from the heat. Alternatively, the processor may receive information from the user equipment (e.g., 110) providing a profile and/or biometric information about the user (e.g., the user's body shape, health goals, experience level performing the current exercise, age, gender, weight, etc.) and may use this information to select an appropriate target breathing pattern for the particular exercise. To perform the operations in block 438, the processor may use the context information receiving module 345. The means for performing the operations of block 438 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), or from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

As non-limiting examples, the context information may be received from a sensor providing information to the user equipment (e.g., 110) and/or a local computing device (e.g., smart glasses 130, smart watch 140, chest band sensor 150, etc.) within the vicinity of the user equipment 110. The context information may be received by accessing a database including one or more data records stored in a local memory (e.g., 220, 258, 325), or may be received from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

Following the operations at block 438, the processor may perform the operations at block 422 of method 400 as described.

FIG. 4G illustrates a method 406 in which the processor may determine an alternative target breathing pattern for the user when the user's current breathing pattern is not within the normal range.

In decision block 440, following the operations in block 424, the processor of the user equipment may perform operations including determining whether the current breathing pattern exceeds a normal breathing pattern threshold. For any given person, the normal breathing pattern may vary, as may individual parameters of the person's breathing pattern, such as the breathing rate, rhythm, or quality of the breathing movement. Accordingly, one or more thresholds may be established that represent general ranges for one or more of those parameters. Those thresholds are designed to trigger additional actions by the processor, such as activating one or more additional sensors, determining another target breathing pattern for the user, or providing the user with additional information that may help the user correct the breathing pattern. Individual thresholds may be established for each parameter that may trigger additional actions. In this manner, any of the breathing rate, rhythm, or quality of the user's breathing movement may trigger the system to perform additional actions. Additionally, the system may be configured to combine thresholds for each parameter that are lower than the individual thresholds to determine whether to perform additional actions when two or more of such parameters are exceeded. For example, if both the user's combined breathing rate and rhythm thresholds are exceeded, additional actions may be triggered even though higher individual breathing rate and rhythm thresholds are not exceeded. When the user's breathing rate is too high or too low, this may be a sign of a life-threatening health problem. The normal breathing pattern threshold may be a predetermined upper and/or lower limit of breaths per minute. Similarly, abnormally shallow breathing (e.g., breathing 25% shallower than normal for the user) may reflect the occurrence of a dangerous health condition. Thus, a predetermined limit on the shallowness of the user's current breathing pattern may be used as the normal breathing pattern threshold. To make the determination in decision block 440, the processor may use a normal breathing pattern determination module (e.g., 375). Also, in decision block 440, the processor may access a database including one or more data records stored in a local memory (e.g., 220, 258) or from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. The database may provide information regarding a breathing pattern threshold, which if exceeded may be deemed abnormal or dangerous to the user. The means for performing the operations of block 420 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325) or from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

In response to a determination that the user's current breathing pattern does not exceed the normal breathing pattern threshold (i.e., decision block 440="No"), the processor may perform the actions in block 426.

In response to a determination that the user's current breathing pattern exceeds the normal breathing pattern threshold (i.e., decision block 440="Yes"), the processor may perform operations including determining another target breathing pattern for the user to achieve in block 442. To make the determination in block 442, the processor may use a target breathing pattern determination module (e.g., 360). Also in block 442, the processor may access a database including one or more data records stored in a local memory (e.g., 220, 258) or from a remote source such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components. The database may provide information regarding the target breathing patterns, as well as exercises associated with those target breathing patterns. The means for performing the operations of block 442 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), or from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

Following the operations at block 442, the processor may perform the operations at block 424 of method 400 as described.

FIG. 4H illustrates a method 407 in which a processor in the user equipment may activate a sensor to measure and/or verify the user's current breathing pattern, according to some embodiments.

Following the operations at block 420, in block 444, the processor of the user equipment may perform operations including activating a respiration sensor configured to monitor the user's current breathing pattern while performing the current exercise in response to determining that the current exercise is being performed by the user. The user may be wearing a chest band (e.g., 150) configured to detect chest motion associated with breathing but operate in a sleep mode until awakened by a signal from the user equipment (e.g., 110). Thus, the processor of the user equipment may signal the chest band to awaken from a sleep mode in response to the processor determining that the user is performing an exercise.

To perform the operations in block 444, the processor may use the sensor activation module 365. The means for performing the operations of block 444 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), or from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

Following the operations at block 444, the processor may perform the operations at block 422 of method 400 as described.

FIG. 4I illustrates a method 408 in which a processor in the user equipment may activate additional sensors, according to some embodiments.

In response to a determination that the user's current breathing pattern exceeds the normal breathing pattern threshold (i.e., decision block 440="Yes"), the processor of the user equipment may perform operations including activating an additional sensor. The additional sensor may be another breathing sensor for redundant and/or more accurate measurements. For example, if one breathing sensor (e.g., an exercise equipment sensor) is already providing input regarding the current breathing pattern, a second breathing sensor (e.g., on a wearable device) may be activated in response to a determination that the user's current breathing pattern exceeds the normal breathing pattern threshold. Alternatively, the additional sensor may be a biosensor for measuring the user's vital signs. In this manner, in response to a determination that the user's current breathing pattern exceeds the normal breathing pattern threshold, a biosensor such as a heart rate monitor may be activated to ensure that the level of exercise is not hazardous to the user.

Alternatively, following the operations at block 444, the processor of the user equipment may perform operations including activating additional sensors. For example, in response to the processor determining (e.g., at block 420) that the user is performing high-intensity exercise, the processor may activate a heart rate monitor or other biosensor at block 446 to alert the user if the user's heart rate or other vital signs become too high during exercise, in addition to activating a respiration sensor at block 444. As a further example, in response to determining that a currently active respiration sensor is insufficient or not optimal for measuring the user's breathing pattern, the processor may activate an additional sensor at block 446.

To perform the operations in block 446, the processor may use the sensor activation module 365. The means for performing the operations of block 446 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), or from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

Following the operations at block 446, the processor may perform the operations at block 422 of method 400 as described.

FIG. 4J illustrates a method 409 in which a processor in a user device may distinguish physical motion associated with a current exercise from physical motion associated with breathing alone, according to some embodiments.

Following the operations at block 424, in block 448, the processor of the user equipment may perform operations including determining a first range of user physical motion attributable to the determined current exercise, separate from breathing, and the user's current breathing pattern is associated with a second range of user physical motion attributable to breathing and separate from the first range of physical motion. For example, when performing a barbell bench press exercise (see FIG. 1A), the user's chest may rise and fall slightly while moving the barbell between a lowered position (e.g., position A) and an elevated position (e.g., position B), and this chest motion may be associated with a first range of user physical motion attributable to the determined current exercise, separate from breathing. Additionally, the user's chest may rise and fall as part of the normal process of breathing, and this chest motion may be associated with a first range of user physical motion attributable to breathing and separate from the first range of physical motion.

To perform the operations in block 448, the processor may use the body movement analysis module 350 and the current breathing pattern monitoring module 370. The means for performing the operations in block 448 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325), or from a remote source, such as a remote system (e.g., 315) or an external resource (e.g., 320) using a transceiver (e.g., 256, 266) and associated components.

Following the operations at block 448, the processor may perform the operations at block 426 of method 400 as described.

Various embodiments (including, but not limited to, those described above with reference to FIGS. 1A-4J) may also be implemented on various computing devices, an example of which is shown in FIG. 5 in the form of a server. With reference to FIGS. 1A-5, a network computing device 500 may include a processor 501 coupled to a volatile memory 502 and a large capacity non-volatile memory, such as a disk drive 503. The network computing device 500 may also include a peripheral memory access device, such as a floppy disk drive, compact disk (CD), or digital video disk (DVD) drive 506, coupled to the processor 501. The network computing device 500 may also include a network access port 504 (or interface) coupled to the processor 501 for establishing a data connection with a network, such as the Internet and/or a local area network coupled to other system computers and servers. The network computing device 500 may include one or more antennas 507 for transmitting and receiving electromagnetic radiation, which may be connected to a wireless communication link. The network computing device 500 may include additional access ports, such as USB, Firewire, Thunderbolt, etc., for coupling to peripherals, external memory, or other devices.

Various embodiments (including but not limited to those described above with reference to FIGS. 1A-4J) may also be implemented on various computing devices, an example of which is shown in FIG. 6 in the form of a mobile computing device. With reference to FIGS. 1A-6, a mobile computing device 600 may include a first SoC 202 (e.g., SoC-CPU) coupled to a second SoC 204 (e.g., a 5G-enabled SoC), such as a D2D link established in a dedicated ITS 5.9 GHz spectrum communication. The first SOC 202 and/or the second SOC 204 may be coupled to internal memory 325, 625, a display 115, and a speaker 614. In addition, the mobile computing device 600 may include one or more antennas 604 for transmitting and receiving electromagnetic radiation, which may be connected to one or more wireless transceivers 266 (e.g., wireless data links and/or cellular transceivers, etc.) coupled to one or more processors in the first SOC 202 and/or second SOC 204. The mobile computing device 600 may also include menu selection buttons or rocker switches 620 for receiving user input.

The mobile computing device 600 may further include a voice encoding/decoding (codec) circuit 610 that digitizes sound received from the microphone into data packets suitable for wireless transmission and decodes the received sound data packets to generate analog signals that are provided to a speaker to generate sound. One or more of the processors, wireless transceiver 266, and codec circuit 610 in the first SOC 202 and/or second SOC 204 may also include digital signal processor (DSP) circuitry (not separately shown).

Various embodiments (including but not limited to those described above with reference to FIGS. 1A-4J) may also be implemented on various wearable devices, one example of which is shown in FIG. 7 in the form of smart glasses 130. With reference to FIGS. 1A-7, smart glasses 130 work similarly to traditional eyeglasses, but with enhanced computing capabilities and sensors, such as a built-in camera 735 and head-up display or augmented reality capabilities located on or near lenses 731. As with any eyeglasses, smart glasses may include a frame 702 coupled to temples 704 that are worn along the wearer's head and behind the ears. The frame 702 holds the lenses 731 in place in front of the wearer's eyes when nose pads 706 on bridge 708 are positioned over the wearer's nose.

In some embodiments, the smart glasses 130 may include an image rendering device 714 (e.g., an image projector) embedded in one or both temples 704 of the frame 702 and configured to project an image onto the optical lens 731. In some embodiments, the image rendering device 714 may include a light emitting diode (LED) module, a light tunnel, a homogenizing lens, an optical display, a folding mirror, or other components, such as a well-known projector or head-mounted display. In some embodiments (e.g., embodiments in which the image rendering device 714 is not included or used), the optical lens 731 may be or include a transparent or partially transparent electronic display. In some embodiments, the optical lens 731 includes an image generating element, such as a transparent organic light emitting diode (OLED) display element or a liquid crystal on silicon (LCOS) display element. In some embodiments, the optical lens 731 may include separate left-eye and right-eye display elements. In some embodiments, the optical lens 731 may include or act as a light guide to direct light from the display element to the wearer's eye.

The smart glasses 130 may include a number of external sensors that may be configured to obtain information about the wearer's actions and external conditions that may be useful in sensing images, sounds, muscle movements, and other phenomena that may be useful in determining that an exercise is being performed. In some embodiments, the smart glasses 130 may include a camera 735 configured to capture an object in front of the wearer in a still image or video stream that may be transmitted to another computing device (e.g., the mobile device 600) for analysis. In some embodiments, the smart glasses 130 may include a microphone 710 positioned and configured to record sounds in the vicinity of the wearer. In some embodiments, multiple microphones may be positioned at different locations on the frame 702, such as on the distal end of the temple 704 near the chin to record sounds emitted by the wearer, such as jaw movements, breathing sounds, etc. In some embodiments, the smart glasses 130 may include one or more electromyographs 716 mounted on one or both temples 704, such as near the temples or above the ears, and configured to measure nerve and muscle electrical activity in the wearer's chin and temple area. In some embodiments, the smart glasses 130 may include pressure sensors, such as nose pads 706 configured to sense facial movements. In some embodiments, the smart glasses 130 may include other sensors (e.g., thermometers, heart rate monitors, body temperature sensors, pulse oximeters, etc.) to gather information about a user's condition that may be useful in determining the user's lung condition, oxygen levels, and/or breathing patterns of the user.

The processing system 712 may include a processing and communications SOC 202, which may include one or more processors (e.g., 132, 202, 204, 210, 212, 214, 216, 218), one or more of which may be configured with processor-executable instructions for performing the operations of the various embodiments. The processing and communications SOC 202 may be coupled to an internal sensor 720, an internal memory 722, and a communications circuit 724, which is coupled to one or more antennas 726 for establishing a wireless database link with an external computing device (e.g., the mobile device 600), such as via a Bluetooth link. The processing and communications SOC 202 may also be coupled to a sensor interface circuit 728, which is configured to control and receive data from a camera 735, a microphone 710, one or more electromyographs 716, and other sensors disposed on the frame 702.

The internal sensors 720 may include an IMU, which includes an electronic gyroscope, an accelerometer, and a magnetic compass configured to measure the movement and orientation of the wearer's head. The internal sensors 720 may further include a magnetometer, an altimeter, an odometer, and an atmospheric pressure sensor, as well as other sensors useful in determining the orientation and movement of the smart glasses 130. Such sensors may be useful in various embodiments for detecting head movements associated with the consumption of liquids as described.

The processing system 712 may further include a power source, such as a rechargeable battery 730 coupled to the SOC 202, as well as external sensors on the frame 702.

The processor implementing the various embodiments may be any programmable microprocessor, microcomputer, or one or more multi-processor chips that may be configured by software instructions (applications) to perform various functions, including the functions of the various aspects described herein. In some communication devices, multiple processors may be provided, such as one processor dedicated to wireless communication functions and one processor dedicated to running other applications. Typically, software applications may be stored in an internal memory before being accessed and loaded into the processor. The processor may include sufficient internal memory to store application software instructions.

As used in this application, terms such as "component," "module," and "system" are intended to include computer-related entities, such as, but not limited to, hardware, firmware, a combination of hardware and software, software, or software in execution, configured to perform a particular operation or function. For example, a component may be, but is not limited to, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a processor of a communications device and the communications device may be referred to as a component. One or more components may reside within a process and/or thread of execution, and components may be localized on one processor or core and/or distributed among two or more processors or cores. In addition, these components may execute from various non-transitory computer-readable media having various instructions and/or data structures stored thereon. Components may communicate by local and/or remote processes, function or procedure calls, electronic signals, data packets, memory reads/writes, and other known network, computer, processor, and/or process-related communication methods.

A number of different cellular and mobile communication services and standards are available or are contemplated in the future, all of which may implement and benefit from various aspects. Such services and standards include, for example, 3rd Generation Partnership Project (3GPP®), Long Term Evolution (LTE) systems, third generation wireless mobile communication technology (3G), fourth generation wireless mobile communication technology (4G), fifth generation wireless mobile communication technology (5G), Global System for Mobile Communications (GSM), Universal Mobile Telecommunications System (UMTS), 3GSM, General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA) systems (e.g., cdmaOne, CDMA1020™), EDGE, Advanced Mobile Phone System (AMPS), Digital AMPS (IS-136/TDMA), Evolution Data Optimized (EV-DO), Digital Enhanced Cordless Telecommunications (DECT), and others. Telecommunications (V2X), Worldwide Interoperability for Microwave Access (WiMAX), Wireless Local Area Network (WLAN), Wi-Fi Protected Access I & II (WPA, WPA2), Integrated Digital Enhanced Network (iden), C-V2X, V2V, V2P, V2I, and V2N, etc. Each of these technologies includes, for example, sending and receiving voice, data, signaling, and/or content messages. It should be understood that any reference to terminology and/or technical details relating to a particular telecommunications standard or technology is for illustrative purposes only and does not limit the scope of the claims to a particular communication system or technology unless specifically recited in the claim language.

Example implementations are described in the following paragraphs. Some of the following example implementations are described with respect to example methods, but further example implementations may include the example methods described in the following paragraphs implemented by a computing device having a processor configured to cause processor-executable instructions to perform the operations of the example methods, the example methods described in the following paragraphs implemented by a computing device including means for performing the functions of the example methods, and the example methods described in the following paragraphs implemented as a non-transitory processor-readable storage medium having stored thereon processor-executable instructions configured to cause a processor of a computing device to perform the operations of the example methods.

Example 1 A method executed by a processor of a user device for providing information regarding a user's breathing pattern during exercise, the method including the steps of: determining a current exercise being performed by the user; determining a target breathing pattern appropriate for the current exercise being performed by the user; monitoring the user's current breathing pattern while performing the current exercise based on input from a breathing sensor; determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern; and providing the user with information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern.

Example 2 The method of example 1, further comprising receiving a sensor input from an exercise sensor that provides information about the user's physical movement, and determining the current exercise is based on the sensor input received from the exercise sensor.

Example 3: The method of example 2, wherein the target breathing pattern is based on sensor input received from an exercise sensor that indicates how the user is moving during exercise.

Example 4: The method of any one of Examples 1 to 3, further comprising receiving a sensor input from an exercise sensor that provides exercise information about a current exercise, the exercise sensor being associated with exercise equipment being used by the user to perform the current exercise.

Example 5 A method according to any one of Examples 1 to 4, further comprising receiving user body movement information from an exercise sensor indicating which of the first and second portions of the current exercise the user is currently performing, the target breathing pattern comprising a first breathing pattern associated with the first portion of the current exercise and a second breathing pattern distinct from the first breathing pattern and associated with the second portion of the current exercise, the step of determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern comprises determining a difference between the target breathing pattern appropriate for the first and second portions of the current exercise and the user's current breathing pattern during the first and second portions of the current exercise, and the step of providing information to the user comprises providing information to the user regarding the difference between the target breathing pattern appropriate for the first and second portions of the current exercise and the user's current breathing pattern during the first and second portions of the current exercise.

Example 6: The method of any one of Examples 1 to 5, further comprising receiving a manual user input regarding at least one of a current exercise or a target breathing pattern, and determining the target breathing pattern is further based on the received manual user input.

Example 7: The method of any one of Examples 1 to 6, further comprising receiving context information indicating a context in which the user is performing the current exercise, and determining the target breathing pattern is further based on the received context information.

Example 8: The method of any of Examples 1 to 7, wherein the target breathing pattern is based at least in part on at least one of the user's body habitus, health goals, or current exercise performance experience level.

Example 9: The method of any one of Examples 1 to 8, further comprising determining an alternative target breathing pattern for the user to achieve in response to the current breathing pattern exceeding a normal breathing pattern threshold, and providing the user with additional information regarding the alternative target breathing pattern.

Example 10: The method of any one of Examples 1 to 9, further comprising, in response to determining that the current exercise is being performed by the user, activating a respiratory sensor configured to monitor the user's current breathing pattern while performing the current exercise.

Example 11: A method according to any of Examples 1 to 10, wherein determining the difference between a target breathing pattern appropriate for a current exercise being performed by the user and the user's current breathing pattern includes comparing the user's current breathing pattern with at least one of the user's previously determined breathing rate, rhythm, or quality when the user performs the current exercise.

Example 12: The method of any one of Examples 1 to 11, further comprising activating an additional sensor in response to the user's current breathing pattern exceeding a normal breathing pattern threshold.

Example 13: The method of any of Examples 1 to 12, further comprising determining a first range of physical movement by the user attributable to the determined current exercise separately from respiration, wherein the user's current breathing pattern is attributable to respiration and is associated with a second range of physical movement by the user that is separate from the first range of physical movement.

Example 14: The method of any of Examples 1 to 13, wherein the user's current breathing pattern includes at least one of a respiratory rate, rhythm, or quality of the respiratory movement.

Example 15: A method according to any of Examples 1 to 14, wherein the step of providing the user with information regarding the determined difference includes notifying the user through at least one of a visual, an auditory, or a tactile alert.

Example 16: A method according to any of Examples 1 to 15, wherein the current exercise is determined based on information regarding the exercise equipment used by the user and a determined difference between a target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern, and the user's current breathing pattern is provided to the user through feedback from the exercise equipment.

The various embodiments shown and described are provided merely as examples to illustrate various features of the claims. However, features shown and described with respect to any given embodiment are not necessarily limited to the associated embodiment and may be used with or combined with other embodiments shown and described. Moreover, the claims are not intended to be limited by any one exemplary embodiment. For example, one or more of the operations of the method may be substituted for or combined with one or more operations of the method.

The above method descriptions and process flow diagrams are provided merely as illustrative examples and do not require or imply that the operations of the various aspects must be performed in the order presented. As will be appreciated by one of ordinary skill in the art, the order of operations in the above aspects may be performed in any order. Words such as "then," "then," and "next" do not limit the order of operations, but rather these words are used to guide the reader through the method description. Additionally, any reference to a claim element in the singular, for example using the articles "a," "an," or "the," should not be construed as limiting the element to the singular.

The various example logical blocks, modules, components, circuits, and algorithmic operations described with respect to the aspects disclosed herein may be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability of hardware and software, the various example components, blocks, modules, circuits, and operations have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in varying ways for each particular application, but such aspect determinations should not be interpreted as causing a departure from the scope of the claims.

The hardware used to implement the various example logic, logic blocks, modules, and circuits described with respect to the aspects disclosed herein may be implemented or performed using a general purpose processor, a digital signal processor (DSP), an ASIC, a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but alternatively, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of receiver smart objects, e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Alternatively, some operations or methods may be performed by circuitry specific to a given function.

In one or more aspects, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a non-transitory computer-readable storage medium or a non-transitory processor-readable storage medium. The operations of the methods or algorithms disclosed herein may be embodied in a processor-executable software module or processor-executable instructions that may reside on a non-transitory computer-readable or processor-readable storage medium. A non-transitory computer-readable or processor-readable storage medium may be any storage medium that may be accessed by a computer or processor. By way of example and not limitation, such non-transitory computer-readable or processor-readable storage medium may include RAM, ROM, EEPROM, FLASH memory, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage smart objects, or any other medium that may be used to store desired program code in the form of instructions or data structures and that may be accessed by a computer. As used herein, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and Blu-ray disc, where disks typically reproduce data magnetically and discs reproduce data optically using lasers. Combinations of the above are also included within the scope of non-transitory computer-readable media and non-transitory processor-readable media. Additionally, the operations of a method or algorithm may be present as one or any combination or set of code and/or instructions on a non-transitory processor-readable storage medium and/or a non-transitory computer-readable storage medium, which may be incorporated into a computer program product.

The foregoing description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the claims. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the scope of the claims. Thus, the present disclosure is not intended to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the following claims and the principles and novel features disclosed herein.

5 Users
6 Users
7 Users
8 Users
50 Wireless Connection
90 Bench
92 Bar
94 Weight
100, 101, 102, 103 Environment
110 User Equipment, Remote Computing Devices
115 Display
116 Audible Feedback
117 Camera
120 Adhesive Patch Sensor
130 Smart Glasses
131 Control Unit
132 processors
133 Memory
134 Input Module
135 Output Module
137 Field of View
138 Transceiver
139 Sensors
140 Smart Watch
150 Chest Band Sensor
160 Exercise Equipment, Treadmills
165 Display
167 Camera imaging angle
170 Exercise Equipment, Fitness Bikes
190 Wireless Network
195 Servers, remote computing devices
200 SIP
202 First SOC
204 Second SOC, 5G-compatible SOC
206 Clock
208 Voltage Regulator
210 Digital Signal Processor (DSP)
212 Modem Processor
214 Graphics Processor
216 Application Processor
218 Coprocessor
220 Memory, memory elements
222 Custom Circuit
224 System Components and Resources
226 Interconnect/Bus Module
230 Sensors
232 Thermal Management Unit
234 Thermal Power Envelope (TPE) Components
250 Interconnect/Bus Module
252 5G modem processor
254 Power Management Unit
256 mmWave transceiver
258 memory
260 processor
264 Interconnect/Bus Module
266 Wireless Transceiver
300 Systems
304 Remote Platform
315 Remote Device
320 External Resources
325 Electronic Storage Devices
330 Processor
335 Machine Readable Instructions
340 Sensor/Manual Input Receiving Module
345 Context Information Receiving Module
350 Body Movement Analysis Module
355 Current Exercise Judgment Module
360 Target breathing pattern determination module
365 Sensor Activation Module
370 Current Breathing Pattern Monitoring Module
375 Normal Breathing Pattern Determination Module
380 Breathing Pattern Difference Judgment Module
385 User Information Distribution Module
400, 401, 402, 403, 404, 405, 406, 407, 408, 409 method
500 Network Computing Devices
502 Volatile Memory
503 Disk Drive
504 network access port
506 Compact Disc (CD) or Digital Video Disc (DVD) drive
507 Antenna
600 Mobile Computing Devices
604 Antenna
610 Voice coding/decoding (codec) circuit
614 Speaker
620 Menu selection button or rocker switch
625 Memory
702 frames
704 Temple
706 Nose pad
708 Bridge
710 Microphone
712 Processing System
714 Image Rendering Device
716 Electromyograph
720 Internal Sensor
722 Internal Memory
724 Communication Circuits
726 Antenna
728 Sensor Interface Circuit
730 Rechargeable Batteries
731 Lenses, Optical Lenses
735 Built-in Camera

Claims (26)

1. A method executed by a processor of a user equipment for providing information regarding a user's breathing pattern during exercise, the method comprising:
determining a current exercise being performed by the user;
receiving user physical movement information from an exercise sensor indicating whether the user is currently performing a first portion or a second portion of the current exercise;
determining a target breathing pattern appropriate for the current exercise being performed by the user , the target breathing pattern including a first breathing pattern associated with the first portion of the current exercise and a second breathing pattern different from the first breathing pattern and associated with the second portion of the current exercise;
monitoring a current breathing pattern of the user while performing the current exercise based on input from a respiration sensor;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user, the difference being determined between the target breathing pattern appropriate for the first and second portions of the current exercise and the current breathing pattern of the user during the first and second portions of the current exercise;
providing the user with information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user , comprising providing the user with information regarding the difference between the target breathing pattern appropriate for the first and second portions of the current exercise and the current breathing pattern of the user during the first and second portions of the current exercise . 1. A method executed by a processor of a user equipment for providing information regarding a user's breathing pattern during exercise, the method comprising:
determining a current exercise being performed by the user;
determining a target breathing pattern appropriate for the current exercise being performed by the user;
monitoring a current breathing pattern of the user while performing the current exercise based on input from a respiration sensor;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
providing the user with information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
determining an alternative target breathing pattern for the user to achieve in response to the current breathing pattern exceeding a normal breathing pattern threshold;
providing the user with additional information regarding the alternative target breathing pattern;
A method comprising: 1. A method executed by a processor of a user equipment for providing information regarding a user's breathing pattern during exercise, the method comprising:
determining a current exercise being performed by the user;
determining a target breathing pattern appropriate for the current exercise being performed by the user;
in response to determining that the current exercise is being performed by the user, activating a respiratory sensor configured to monitor the current breathing pattern of the user while performing the current exercise;
monitoring a current breathing pattern of the user while performing the current exercise based on input from the respiration sensor;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
providing the user with information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
A method comprising: 1. A method executed by a processor of a user equipment for providing information regarding a user's breathing pattern during exercise, the method comprising:
determining a current exercise being performed by the user;
determining a target breathing pattern appropriate for the current exercise being performed by the user;
monitoring a current breathing pattern of the user while performing the current exercise based on input from a respiration sensor;
activating an additional sensor in response to the current breathing pattern of the user exceeding a normal breathing pattern threshold;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
providing the user with information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
A method comprising: 1. A method executed by a processor of a user equipment for providing information regarding a user's breathing pattern during exercise, the method comprising:
determining a current exercise being performed by the user;
determining a target breathing pattern appropriate for the current exercise being performed by the user;
monitoring a current breathing pattern of the user while performing the current exercise based on input from a respiration sensor;
determining a first range of physical movement by the user attributable to the determined current exercise separately from respiration, the current breathing pattern of the user being associated with a second range of physical movement by the user attributable to the respiration and separate from the first range of physical movement;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
providing the user with information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
A method comprising: The method of any one of claims 1 to 5 , further comprising the step of receiving a sensor input from an exercise sensor providing information regarding a user's physical movement, and wherein determining the current exercise is based on the sensor input received from the exercise sensor. The method of claim 6 , wherein the target breathing pattern is based on the sensor input received from the exercise sensor that is indicative of how the user is moving during the exercise. The method of any one of claims 1 to 5, further comprising receiving sensor input from an exercise sensor providing exercise information about the current exercise, the exercise sensor being associated with exercise equipment being used by the user to perform the current exercise . 6. The method of claim 1, further comprising receiving a manual user input regarding at least one of the current exercise or the target breathing pattern, and wherein determining the target breathing pattern is based on the received manual user input. The method of any one of claims 1 to 5, further comprising the step of receiving context information indicative of a context in which the user is performing the current exercise, and wherein determining the target breathing pattern is further based on the received context information. The method of claim 1 , wherein the target breathing pattern is based on at least one of a user's body type, health goals, or experience level in performing the current exercise. A method according to any one of claims 1 to 5, wherein the step of determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user includes a step of comparing the current breathing pattern of the user with at least one of an already determined breathing rate, rhythm or quality of the user when the user performed the current exercise. The method of claim 1 , wherein the current breathing pattern of the user includes at least one of breathing rate, rhythm, or quality of respiratory movements. 6. The method of claim 1 , wherein providing the user with information regarding the determined difference includes notifying the user through at least one of a visual, an audio, or a tactile alert. The method of any one of claims 1 to 5, wherein the current exercise is determined based on the information regarding the determined difference between the target breathing pattern appropriate for exercise equipment used by the user and the current exercise being performed by the user and the current breathing pattern of the user, and the current breathing pattern of the user is provided to the user through feedback from the exercise equipment. A user equipment (UE),
A user interface;
a processor coupled to the user interface,
Determining a current exercise being performed by a user;
receiving user physical movement information from an exercise sensor indicating whether the user is currently performing a first portion or a second portion of the current exercise;
determining a target breathing pattern appropriate for the current exercise being performed by the user , the target breathing pattern including a first breathing pattern associated with the first portion of the current exercise and a second breathing pattern distinct from the first breathing pattern and associated with the second portion of the current exercise;
monitoring a current breathing pattern of the user while performing the current exercise based on input from a respiration sensor;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user , comprising determining a difference between the target breathing pattern appropriate for the first and second portions of the current exercise and the current breathing pattern of the user during the first and second portions of the current exercise;
providing the user via the user interface information regarding a determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user, comprising providing the user with information regarding a difference between the target breathing pattern appropriate for the first and second portions of the current exercise and the current breathing pattern of the user during the first and second portions of the current exercise;
A UE comprising: a processor that stores processor-executable instructions for performing the above . A user equipment (UE),
A user interface;
a processor coupled to the user interface,
Determining the current exercise being performed by the user;
determining a target breathing pattern appropriate for the current exercise being performed by the user;
monitoring a current breathing pattern of the user while performing the current exercise based on input from a respiration sensor;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
providing to the user via the user interface information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
determining an alternative target breathing pattern for the user to achieve in response to the current breathing pattern exceeding a normal breathing pattern threshold;
Providing the user with additional information regarding the alternative target breathing pattern
a processor and a processor-executable instruction storage unit for storing processor-executable instructions for
A UE equipped with the above. A user equipment (UE),
A user interface;
a processor coupled to the user interface,
Determining the current exercise being performed by the user;
determining a target breathing pattern appropriate for the current exercise being performed by the user;
activating a respiratory sensor configured to monitor the current breathing pattern of the user while performing the current exercise in response to determining that the current exercise is being performed by the user;
monitoring a current breathing pattern of the user while performing the current exercise based on input from a respiration sensor;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
providing the user via the user interface information regarding a determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
a processor and a processor-executable instruction storage unit for storing processor-executable instructions for
A UE equipped with the above. A user equipment (UE),
A user interface;
a processor coupled to the user interface,
Determining the current exercise being performed by the user;
determining a target breathing pattern appropriate for the current exercise being performed by the user;
monitoring a current breathing pattern of the user while performing the current exercise based on input from a respiration sensor;
activating an additional sensor in response to the current breathing pattern of the user exceeding a normal breathing pattern threshold;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
providing the user via the user interface information regarding a determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
a processor and a processor-executable instruction storage unit for storing processor-executable instructions for
A UE equipped with the above. A user equipment (UE),
A user interface;
a processor coupled to the user interface,
Determining a current exercise being performed by a user;
determining a target breathing pattern appropriate for the current exercise being performed by the user;
monitoring a current breathing pattern of the user while performing the current exercise based on input from a respiration sensor;
determining a first range of physical movement by the user attributable to the determined current exercise separately from respiration, the current breathing pattern of the user being associated with a second range of physical movement by the user attributable to the respiration and separate from the first range of physical movement;
determining a difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
providing the user via the user interface information regarding the determined difference between the target breathing pattern appropriate for the current exercise being performed by the user and the current breathing pattern of the user;
a processor storing processor-executable instructions for performing
A UE equipped with the above. The processor,
receiving a sensor input from an exercise sensor providing information regarding a user's physical activity;
The UE of any one of claims 16 to 20 , further storing processor -executable instructions for determining the current exercise based on the sensor input received from the exercise sensor. The processor,
The UE of any one of claims 16 to 20, further storing processor-executable instructions for receiving sensor input from an exercise sensor that provides exercise information related to the current exercise, the exercise sensor being associated with exercise equipment being used by the user to perform the current exercise. The processor,
receiving a manual user input regarding at least one of the current exercise or the target breathing pattern;
The UE of any one of claims 16 to 20 , further storing processor -executable instructions for determining the target breathing pattern further based on the received manual user input. The processor,
receiving context information indicative of a context in which the user is performing the current exercise;
The UE of any one of claims 16 to 20 , further storing processor executable instructions for determining the target breathing pattern further based on the received context information. The processor,
determining an alternative target breathing pattern for the user to achieve in response to the current breathing pattern exceeding a normal breathing pattern threshold;
The UE of any one of claims 16 to 20 , further storing processor -executable instructions for providing the user with additional information regarding the alternative target breathing pattern. A non-transitory processor-readable storage medium having stored thereon processor-executable instructions for causing a processor of a user equipment (UE) to perform a method according to any one of claims 1 to 15 to provide information regarding a user's breathing pattern during exercise .

Images