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WO2019043147A1 - Tissu de vêtement pour lire et écrire une activité musculaire - Google Patents

Tissu de vêtement pour lire et écrire une activité musculaire Download PDF

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Publication number
WO2019043147A1
WO2019043147A1 PCT/EP2018/073452 EP2018073452W WO2019043147A1 WO 2019043147 A1 WO2019043147 A1 WO 2019043147A1 EP 2018073452 W EP2018073452 W EP 2018073452W WO 2019043147 A1 WO2019043147 A1 WO 2019043147A1
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WO
WIPO (PCT)
Prior art keywords
emg
ems
electrodes
electrode
muscle
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/EP2018/073452
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English (en)
Inventor
Paul STROHMEIER
Sebastian Boring
Kasper HORNBÆK
Jarrod Knibbe
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Københavns Universitet
Original Assignee
Københavns Universitet
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Publication of WO2019043147A1 publication Critical patent/WO2019043147A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/02—Details
    • A61N1/04—Electrodes
    • A61N1/0404—Electrodes for external use
    • A61N1/0408—Use-related aspects
    • A61N1/0452—Specially adapted for transcutaneous muscle stimulation [TMS]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/389—Electromyography [EMG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/02—Details
    • A61N1/04—Electrodes
    • A61N1/0404—Electrodes for external use
    • A61N1/0472—Structure-related aspects
    • A61N1/0476—Array electrodes (including any electrode arrangement with more than one electrode for at least one of the polarities)
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/02—Details
    • A61N1/04—Electrodes
    • A61N1/0404—Electrodes for external use
    • A61N1/0472—Structure-related aspects
    • A61N1/0484—Garment electrodes worn by the patient
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/36003—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation of motor muscles, e.g. for walking assistance
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/36014—External stimulators, e.g. with patch electrodes

Definitions

  • the present invention relates to a wearable garment fabric for electric muscle stimulation (EMS), a circuit for multiplexing EMG and EMS signals from an array of electrodes, a method for calibrating EMS for a muscle(s) pose, and a computer implemented method for providing an EMS input to a wearable fabric.
  • EMS electric muscle stimulation
  • HAI human-computer interaction
  • Electric muscle stimulation also known as functional electric stimulation (FES) or muscle writing
  • FES functional electric stimulation
  • the principle is that a current is applied to a target muscle, which then results in an activation and movement of the target muscle.
  • the muscle activity generated will depend on the characteristics of the impulse, as well as the location of the impulse on the target muscle.
  • EMS is receiving increasing interest due to the potential application for rehabiliation of immobilized body parts and patients, as learning tool and training tool for athletes, and for virtual reality and augmented reality, since EMS can enable mobile force feedback, support pedestrian navigation, and confer object affordances.
  • the EMS system may further be easily portable, such as implemented in a wearable garment as multiple electrodes strategically placed.
  • the current EMS applications are limited by two interlinked problems: (1 ) EMS is low resolution, achieving only coarse movements, such as the flexing of a hip, knee, ankle, or arm, and (2) EMS requires time consuming, expert calibration.
  • the challenge surrounding resolution stems from two factors that make targeting desired muscles difficult. Firstly, the anatomy of most gestures, e.g. gestures performed with a muscle or muscle groups in the forearm, is complex, with muscles both tightly packed and layered. Secondly, trans-cutaneous stimulation disperses unpredictably into the underlying tissue and muscle. Higher resolution may be obtained by invasive needle-based stimulation, however this results in reduced comfort and control of muscle fatigue. Higher resolution may also be obtained by multiple skin electrodes placed with a high-density around the target muscle(s), and by uniquely shaped electrodes. Thus, stimulation of more precise movements may be obtained, and simultaneously the range of possible motions may be increased.
  • calibration is meant the process to determine the positioning of the electrodes on the skin or muscle (spatial calibration), and the tuning of the electric stimulation parameters (signal calibration, including amplitude, pulse width, and frequency), to obtain a target movement or gesture, while minimizing discomfort to the skin of the user.
  • EMS must be calibrated individually to each user, since parameters such as muscle size, depth of fat, and skin resistance will vary from person to person.
  • calibration is typically time-consuming and not applied in real-time, i.e. carried out as a separate step, or as separate iterations, before the EMS can be applied correctly.
  • the issues with resolution and calibration are further conflicting in nature. Improved stimulation resolution may be obtained by increasing the number of electrodes, e.g. by forming an array or grid of electrodes. However, as the number of electrodes increases, the calibration complexity increases exponentially due to the increased number of variables combinations.
  • Conventional EMS requires time-consuming, per-user calibration. The calibration involves both spatial calibration, correctly positioning the electrodes, and signal calibration, tuning stimulation parameters, to target correct muscle depths and minimize discomfort.
  • a typical calibration process may proceed as follows: the EMS-designer first determines their target gesture and from there identifies the required muscles. They may choose to do this anatomically, such as by using muscle diagrams, or through visual or tactile inspection of arm-surface deformations during muscle contractions (e.g., palpation).
  • Electrodes and higher resolution may be obtained using an EMS array or grid.
  • the electrodes are fixed relatively to each other within the array or grid, and the spatial calibration thus relates to which electrodes in the array to employ or activate.
  • the multiple electrodes may then be selected and coordinated to provide stimulation.
  • the available permutations of electrode combinations and thus also the complexity of spatial-calibration increases exponentially with the number of electrodes comprised in the array.
  • the potential resolution for an array will depend on the number of electrodes, the shape and coverage degree of the electrodes, as well as the spacing between the electrodes.
  • EP3184143 [1 ] discloses a sock comprising an array of skin electrodes, where a subset of electrodes in the array is EMS activated, and where the activated subset electrodes is selected, or calibrated, based on e.g. a simple impedance measurement.
  • WO 2012/003451 [2] discloses a wearable garment comprising an array of electrodes.
  • the system is a multi-channel, closed-loop FES system, where a first muscle response is generated by a first FES signal and then detected by electromyography (EMG). The detected EMG signal is then applied directly to adjust the second FES signal in realtime, and the process may be repeated in a closed-loop.
  • EMG electromyography
  • the present disclosure provides devices and methods facilitating a higher resolution of muscle activity with EMS, thus enabling finer motor control, and potentially enabling a muscle resolution being suitable for playing a musical instrument such as the piano.
  • the present disclosure further provides methods and devices configured for faster and real-time calibration of an electrode array for EMS. This is obtained by using electromyography (EMG) to auto-calibrate the EMS array, where the EMG data is further processed to facilitate higher muscle resolution.
  • EMG electromyography
  • the EMS array is high-density, i.e. has a high density of electrodes, and optionally heuristics or automated procedures are further included to enable faster calibration.
  • the present disclosure provides auto-calibration, and real-time calibration and real-time writing of muscle(s) activity or muscle(s) poses.
  • the invention was further seen to provide improved accuracy of a muscle(s) activity, when e.g. replaying a predefined gesture.
  • the invention further provides improved resolution, including finer motor control, e.g. by reading/writing combined agonist and antagonist muscles.
  • the present disclosure further provides improved resolution for HCI (human-computer- interaction).
  • a first aspect of the invention relates to a wearable garment fabric for electric muscle stimulation (EMS) comprising: an array of electrodes, wherein the electrodes are configured for multi-channel electromyography (EMG) and multi-channel EMS pulses,
  • EMG electromyography
  • EMG multi-channel electromyography
  • an EMG control system configured for collecting EMG data within the electrode array when the fabric wearer makes a muscle(s) pose
  • an EMS control system configured for generating EMS pulses within the electrode array to replay the muscle(s) pose, wherein the EMS pulses are calibrated based on the collected and processed EMG data.
  • a second aspect of the invention relates to a circuit for multiplexing EMG and EMS signals from an array of electrodes, comprising:
  • At least one EMS unit for controlling EMS amplitude, pulse width and frequency, one or more switching boards for switching between electrodes,
  • At least one switch board for switching between EMG and EMS mode.
  • a third aspect of the invention relates to a method for calibrating EMS for a muscle(s) pose, comprising the steps of:
  • a fourth aspect of the invention relates to a computer implemented method for providing an EMS input to a wearable fabric according to the first aspect of the invention, comprising the steps of:
  • a fifth aspect of invention relates to a computer system, such as a mobile device, comprising a processor and a memory and being adapted to carry out the method according to the fourth aspect of the invention.
  • Figure 1 A shows an embodiment of the invention, where the garment fabric is a cotton sports compression sleeve worn around the forearm of a user.
  • the fabric comprises an array of 60 skin electrodes sewn into the inner surface of sleeve in a 6 x 10 grid.
  • the grid is also visible on the outside of the sleeve, since the electrodes interface electrically to the outside of the sleeve with metal poppers.
  • the sleeve and the electrodes are connected to a circuit, exemplified as a switching circuitry in Figure 1A, by a ca. 1 .5 m of cable.
  • the circuit is also wearable, e.g. by mounting the components of the circuit to a surface of a fabric.
  • Figure 1 B shows embodiments of muscles poses, or gestures, performed with a muscle or muscle groups placed in the forearm.
  • the gestures are: wrist extension (top image), wrist flexion (second image from top), lift index finger (third image from top), and squeeze fingers (bottom image).
  • the gestures may either be performed by the user while wearing the garment fabric for real-time calibration or the gestures may be generated by EMS following the calibration.
  • Figure 2 shows a further embodiment of the invention.
  • Figure 2A shows an
  • FIG. 2B-D shows an embodiment of the process of EMG calibration for EMS.
  • the user puts on the sleeve as illustrated in Figure 2B, and as exemplified in Figure 2B, the sleeve may be equipped with a zipper for easy mounting on the forearm.
  • the user then performs a desired, or target, pose, e.g. wrist extension as illustrated in Figure 2C, whilst EMG data is gathered within, or across, the electrode array.
  • an EMS stimulation pattern is calculated from the EMG data, and the pose may be replayed, or written, by EMS as illustrated in Figure 2D.
  • the sleeve and the electrodes are connected to a control circuit, exemplified as a switching circuitry in Figure 1 A, by a ca. 1 .5 m of cable.
  • a control circuit exemplified as a switching circuitry in Figure 1 A
  • the sleeve and circuit may also be fully wearable, e.g. achieving miniaturization through surface mount components, which would enable a more independent use, e.g. when using the array on a tennis court, or when using the array when moving around the house, whilst cooking.
  • the control circuit may be wearable, e.g. by mounting the components of the circuit to a surface of a wearable fabric.
  • the electrodes are skin electrodes.
  • the electrode array configuration further influences on the user's comfort during application. For example, an electrode array comprising few electrodes, or electrodes with a small size or with a small inter-electrode spacing, may result in a burning sensation on the skin of the user due to the current density. However, a higher number of electrodes, bigger sizes and spacing increases the complexity of resolution and trans-cutaneous dispersion.
  • a fabric comprising an electrode array covering a high degree of the fabric, and inherently a high degree of the limb or muscle(s) groups to be covered by the fabric, and where the number of electrodes are above 10, and/or where the electrodes are placed in the pattern of rows, and/or the size of each electrode is between 1 to 10 cm 2 , and/or the distance between neighbouring electrodes is between 5-30 mm.
  • the contact surface area of the electrodes cover the fabric with a coverage degree between 10 to 99%, more preferably between 50 to 90%, and most preferably between 60 to 80%.
  • the array of electrodes comprises above 10 electrodes, more preferably between 20 to 80 electrodes, such as 60 electrodes, and most preferably above 100 electrodes.
  • the arrays of electrodes are placed in one or more rows thereby forming a grid, such as six rows where each row comprises ten electrodes.
  • the contact surface area of each electrode is between 0.4 to 10 cm 2 , more preferably between 0.5 to 5 cm 2 , and most preferably is between 0.8 to 4 cm 2 , such as 1 or 3 cm 2 .
  • the distance between neighbouring electrodes is between 5 to 30 mm, more preferably between 10 to 20 mm, and most preferably between 10 to 15 mm.
  • the resolution and muscle selectivity, and degree of trans-cutaneous dispersion and discomfort, will also be affected by the contact degree between the electrode surface and the surface of the user, e.g. the surface skin of the user. Poor contact may for example be due to poor electrode adhesion along the edges, and the decreased contact will result in an effectively smaller contact surface and uneven current distribution.
  • the electrodes are made of materials that are easily adhered to the skin, and which have shapes and sizes facilitating contact along the edges.
  • the electrodes comprise a conductive fabric.
  • the shapes of the electrodes are selected from the group of: rectangular, circular, oval, squared shaped, and stud shaped, and most preferably is rectangular shaped or stud shaped.
  • the size of the electrodes correspond to a rectangular electrode with a first length between 10 to 30 mm, such as 20 mm, and a second length between 10 to 30 mm, such as 15 mm.
  • the contact degree between user and electrode surface may further be improved by the application of a conductive gel.
  • the gel may serve to distribute the stimulation across a wider area, decrease between-/inter-electrode effects, and improve the resolution.
  • a layer of electrode hydrogel such as AxelGaard's AG635 'Sensing' Hydrogel, ensures a good or complete connection between the conductive fabric and the skin.
  • the gel may be cut into per-electrode pieces, and applied to each electrode individually. Alternatively, one large sheet of electrode gel can be applied.
  • the fabric further comprises an electric gel, such as an electrode hydrogel.
  • an electric gel such as an electrode hydrogel.
  • the electric gel is configured to be applied to each electrode individually or applied as a single unit.
  • a zip may be added to the side of the sleeve.
  • the sleeve can be put on and removed by the wearer.
  • the design of the sleeve is such that the zip is worn down the center of the inner forearm, as the wearer can hold the top of the zip with their wearing-hand, while pulling the zipper with their other hand.
  • the zipper supports a one-time calibration process.
  • one-time calibration is meant that the fabric can be mounted and dismounted any number of times for a given user, and be continuously calibrated without the need of re-calibration every time the fabric is mounted. This is facilitated by the configuration of the electrodes, particularly the size of the electrodes and the multiple-electrode patterns, which enables that the re-applied array of electrodes may be closely aligned with their initially calibrated position.
  • the one-time calibration process may be further improved by further tailored designs, which indicate the positioning of certain muscle groups and/or body parts, such as the use of a "thumb loop" and/or clear “elbow patch".
  • the fabric further comprises a zipper. In a further embodiment, the fabric comprises a thumb loop and/or elbow patch.
  • the array and fabric are integrated such that high flexibility during mounting, use, and maintenance is obtained.
  • this may be obtained by wearable electronics, e.g. by wiring integrated into the wearable, with small electronic control box mounted onto exterior of fabric.
  • the fabric is configured as a stretchable compression garment form factor (i.e. without zip) that can be simply pulled on.
  • the fabric is configured to have multiple form factors, e.g. both sleeves and leg tights form factors.
  • the array and fabric are configured to be machine washable.
  • a conventional array applies pair-wise calibration, where the electrodes are pre- designated and fixed as anode and cathode.
  • the complexity or number of combinations are eliminated, since the reading and writing occurs as a simple pre-fixed 1 :1 (anode:cathode).
  • any electrode may act as anode or cathode, and thus any electrode acting as anode may act as anode for a multiple of cathode electrodes.
  • the number of electrode combinations described above is based on bipolar EMG configuration, i.e. that the EMG data are collected bipolarly between two electrodes, an anode and a cathode.
  • EMG data may be gathered from an individual electrode, i.e. monopolar configuration.
  • a complete EMG mapping involves only a reading for each n electrode.
  • monopolar EMG requires additional data processing, and monopolar EMG may produce improved accuracy compared to bipolar configuration.
  • monopolar or bipolar EMG configurations may be preferred. Both bipolar and monopolar EMG mapping may involve a reference electrode.
  • the EMG control system is configured to collect the EMG data across, or within, the electrode array in a monopolar manner.
  • bipolar EMG is advantageously used to read muscle action potentials during muscle actuation, such as while performing and/or maintaining a gesture.
  • the optimal configuration for the EMG electrodes may be above and below the center of the muscle and then downwards along the muscle fiber, e.g. placed 10-30mm apart.
  • not all muscle fibers tend downwards, for example pennate muscles, such as the flexor carpi ulnaris in the forearm.
  • Figure 4 shows an embodiment of how the EMG reading may be obtained across a cluster of neighboring electrode pairs.
  • readings are taken between each electrode and the 3 closest electrodes in the next two rows for a total of 306 unique pairings.
  • the reading starts from the top of the sleeve, nearest the shoulder, and continues downwards towards the wrist, following the muscular anatomy of the forearm.
  • Reference electrodes may be placed on the biceps brachii.
  • the EMG control system is configured to collect bipolar EMG readings between each electrode and six neighbouring electrodes. In a further embodiment, the EMG control system is configured to collect bipolar EMG readings between each electrode and the three closest electrodes in two adjacent rows. In a further embodiment, the EMG control system is configured to collect bipolar EMG readings between each electrode assigned as anode and six neighbouring cathodes.
  • the EMG control system may be in the form of a circuit, where the circuitry uses relays to select between different electrode pairs.
  • the process of switching EMG signals between electrodes may add a spike to the EMG signal.
  • each EMG pair may be read for 220 ms and only the data from the last 20ms is used.
  • switching EMG signals between electrodes may be obtained by more than one EMG unit.
  • two EMG devices may be used concurrently, where a full reading cycle may take ca. 45seconds (for 306 unique electrode pairs in a 60 electrode array).
  • the reading time is shortened by combinations of (a) customized EMG hardware allowing signal rectification in code not hardware, (b) using more EMG channels simultaneously, however, this introduces additional hardware complexity, and/or (c) using feature vector patterns from dynamic gesture data.
  • the EMG data may be corrected by a baseline pose. This may be obtained if the user puts on the sleeve and EMG data for the initial "rest" pose is read as a baseline from which to normalize future poses.
  • EMG data is collected for the calibration.
  • RMSQ root mean square
  • standard deviation and signal peak maximum may be calculated for each electrode pairing. These values may be standardized against the corresponding values from the rest pose.
  • the electrodes in each pair is labeled respectively anode and cathode, and then sorted into 3 groups using k-means clustering.
  • the three clusters are 1 ) inactive, 2) low potential, and 3) high potential.
  • the clustering may be based on the use of two stimulation channels. Both the anode and cathode electrodes are added to the calculated cluster.
  • each anode is paired with six cathodes, as illustrated in Figure 4, it is possible that any one electrode can be placed in multiple clusters (inactive, low, or high potential).
  • the electrode in the highest cluster is prioritized (where high potential > low potential > inactive).
  • the electrode pairs are sorted by RMSQ magnitude. Electrodes are finally selected as anode, cathode, or 'off' based on their highest cluster and highest magnitude pairing. This electrode assignment is subsequently used for EMS.
  • An amplitude ratio between the stimulation channels may be automatically calculated from the average RMSQ of each cluster. This ratio is balanced with the number of electrodes in each cluster as the current per electrode decreases with increasing electrode count.
  • the stimulation pattern may be presented to the user through a GUI, and the system may automatically maintain the amplitude ratio between the EMS channels.
  • the user can modify the amplitude, pulse width and frequency of the pattern either through keyboard shortcuts or with the mouse.
  • the EMG control system is configured to cluster each electrode pair using k-means clustering.
  • the method of the current embodiment includes reading between each electrode and its six neighboring electrodes. This is in order to improve reading accuracy along muscles that do not tend directly down the arm (pennate muscles, for example). This adds a complexity to our mapping procedure, since at any given electrode location, we do not know which electrode pair to favor. While we assume that electrodes directly down the muscle body will provide the highest readings, this is a potential source for noise and error. Since the muscle structure under the electrodes cannot be determined, it may be beneficial to move from a bipolar EMG configuration to a monopolar configuration (gathering EMG data from individual electrodes). This has recently been shown to offer increased accuracy over a bipolar approach when processing data from the 5th principle component.
  • the electrode array of the current invention is a multi-functional EMG reading and EMS writing system.
  • the same complex patterns of electrodes, or electrode combinations, may be used for EMS as for EMG.
  • the number of electrode configurations is also p:q electrode configurations, where p, q ⁇ 1 .
  • the EMS is also multi-channel and multi-amplitude, thus forming electrodes of arbitrary shape and size.
  • Multi-channel EMS enables primary and secondary stimulation patterns, where the primary actuation is controlled by one channel and causes the principle motion, with a second channel building upon or subtracting from this motion. For example, the primary electrodes may pull the hand up at the wrist, whilst the secondary electrodes provide small alterations to finger positions.
  • agonist (primary) and antagonist (counter) muscles can be targeted separately.
  • Combining electrodes also serves to distribute the stimulation signal across a larger surface area. As a result of this, the user may choose to increase the EMS amplitude beyond that typical if using a pairwise configuration.
  • the multi-channel and multi-amplitude EMS map for a posed gesture is advantageously obtained based on the collected and processed EMG map across the same electrode array.
  • the EMS control system is configured to generate EMS pulses based on the clustered EMG data.
  • the EMS map required to produce or replay the same given gesture may be the same or different from the EMG map read.
  • the EMS map required to produce a given gesture over a certain amount of time may vary. For example, when holding a pose, co-activation can cause EMG potentials across the two muscle compartments. However, where agonist muscle potentials increase over time, antagonist muscles do not. Thus, the agonist-antagonist behavior may include changes in certain electrodes over time.
  • the EMS control system is configured to generate EMS pulses that are multi-channel, multi-amplitude, and/or variable over time.
  • At least one switch board for switching between EMG and EMS mode.
  • the number of components for the circuit is advantageously kept to a minimum to facilitate portability and miniaturization of the circuit.
  • the circuit comprises two EMG units and one EMS unit.
  • the circuit comprises between 2-100 EMG units, and/or 2-100 EMS units, more preferably between 10-80 EMG units and 10-80 EMS units, such as 60 EMG units and 60 EMS units.
  • the circuit is configured to be used as the EMG and/or EMS control system for the fabric or array of the current invention.
  • the EMG and EMS units are off-the shelf units, such as EMG devices from Backyard Brains, Muscle Spiker shields, and an EMS device from Med-Fit 1 , dual channel Tens machine.
  • This EMS device may provide control of signal amplitude, pulse width and frequency.
  • the parameters may be controlled through 2 digital potentiometers (DS1803-050, 2 channel, 256-step, 50kQ).
  • the amplitude may also be manually controlled through two 20kQ potentiometers, thus having 102-steps of amplitude resolution control.
  • the circuit includes custom PCBs to control the signal-electrode switching.
  • Each signal switching board routes the signals, in any combination, to 6 electrode connectors (for one row of the embodied sleeve).
  • the signals are routed through an array of 24 solid-state relays (2 per channel per electrode, CPC1218Y1 ).
  • the relays are controlled through 3 chained 8-bit shift registers (SN74HC595N).
  • SN74HC595N 3 chained 8-bit shift registers
  • NO relays normally open ensure no stimulation signal connection to the wearer, should an error occur or the switching board power fail.
  • the solid state relays are rated to 60V. While the EMS device provides 40V maximum at 500 Ohm, the current driven signal can exceed 60V at skin-level resistance. This high-level voltage only occurs in brief voltage spikes.
  • a relay with a higher maximum voltage may be applied for safety, such as the
  • the custom signal switching boards and circuitry are driven through an Engineering Automation Network (ALE) (requiring 56 digital pins and 2 analog pins).
  • An additional 5V power supply is used to support the current requirements of the switching boards.
  • the Engineering may be interfaced with Python, to provide a GUI for control.
  • Example 1 shows an embodiment of the schematics for a control source code.
  • the circuit is configured to perform the methods, according to the third and fourth aspects of the invention.
  • the circuit is configured to perform the parts of the methods comprising the steps of:
  • the circuit is configured to be used as an EMG and/or EMS control system.
  • the circuit is configured to carry out the method according to the fourth aspect of the invention.
  • the EMS pulses may be evaluated by the user, and the user may provide input to the system, such as rating the EMS pulses.
  • the circuit further comprises a user interface, such as a GUI (graphical user interface) configured for receiving input for modifying the EMS pulses.
  • a user interface such as a GUI (graphical user interface) configured for receiving input for modifying the EMS pulses.
  • the system includes a computer system, such as a mobile device, comprising a processor and a memory and being adapted to carry out the method according to the fourth aspect of the invention.
  • the current invention may be used for any EMS application.
  • the system of the present invention is particularly suitable for being portable and for being integrated into a wearable garment.
  • the applications include rehabiliation of immobilized body parts and patients, as learning tool and training tool for athletes and for personal activities, and for virtual reality and augmented reality.
  • the wearable fabric sensor may be embodied in a sleeve form.
  • the wearer must perform the task themselves. Having learned the muscle patterns for the activity, the sleeve can subsequently cause the wearer to continue to perform the task without their express concentration. For example, you do only the first stir of your cake mix, before the sleeve takes over and makes you stir whilst you concentrate on something else.
  • the invention is especially well-suited to sports clothing,
  • the system may be incorporated into any sports compression clothing, including shirts, shorts, full leg tights, socks, sleeves, etc.
  • the same technique as described for stirring a cake mix may be applied to golf.
  • the user may perform 5 manual golf swings and rate each swing.
  • the fabric sensor can monitor the muscle recruitment and correct the movement towards an optimal swing.
  • This same concept can be applied across a breadth of sports or other physical tasks.
  • the same technique also allows us to monitor muscle usage during performance. For example, during endurance running, a person's muscle usage slowly weakens as the person become tired. However, a person's ability to use muscle degrades faster than the actual muscles are capable of.
  • the system of the current invention enables to monitor muscle use in real time and provide a performance boost to keep athletes performing harder for longer.
  • Example 1 Method of using EMG to auto-calibrate a high-density EMS array
  • the EMS calibration was based on EMG data gathered from the high-density electrode array.
  • a flow diagram of the process is shown in Figure 7.
  • Example 2 Proof-of-concept by auto-calibrating a sixty electrode EMS array with EMG An array comprising 60 electrodes was used for spatial calibrating EMS with EMG. The calibration involved the multi-electrode patterns for EMS, stimulating between any number of anodes and cathodes with two signal sources.
  • the EMG based auto-calibration of an electrode array was focused on gestures typically used in the HCI EMS literature.
  • gestures previously used in the EMS literature, plus an additional rest gesture for EMG signal base-lining. These gestures include: wrist flexion (wrist-down), wrist extension (wrist-up), radial deviation (hand rotation towards the thumb, hand-left), ulnar deviation (hand rotation towards the little finger, hand-right), squeeze-fingers, and lift index finger. The gestures are also shown in Figure 5. The order of the gestures was counterbalanced across participants.
  • Participants were standing during the study and wore the sleeve on their dominant forearm. The participants were instructed to hold their hand over a table in front of them, with their elbow bent at -90 degrees. While this may introduce some constant muscle tension, the effects of this would be removed by the normalization step in the EMG reading process.
  • the use of the keyboard allowed fine-grained control of each parameter and provided a quick method to disable the stimulation (by pressing the spacebar).
  • the participants were free to spend as long as they wished exploring the parameters.
  • the participants' wrist, back of hand, and fingers were tracked with an OptiTrack motion tracking camera setup (8 Prime13 cameras, 240fps).
  • Data was captured at the end of every complete line of reading (EMG), and after every 5th step of stimulation amplitude increase (EMS). This resulted in 18 frames of data per pose during the reading phase, and 24 frames per pose (on average) during the writing phase.
  • the captured data was automatically inspected after each participant completed the study.
  • the motion tracking data was used to calculate orientation and position changes of the back of the hand and the individual fingers during poses (manual and stimulated).
  • the target gestures were grouped into pairs based on shared muscle compartments: wrist-up and wrist-down, hand-left and hand-right, squeeze-fingers and index-point.
  • the extensor carpi ulnaris (on the top of the forearm), among other muscles, contracts to extend the wrist. In this case, it is an agonist muscle.
  • the antagonist muscles such as the flexor carpi ulnaris (on the bottom of the forearm), relax to enable wrist extension. When flexing the wrist, however, the role of these muscles is reversed. When holding a pose, co-activation of both agonist and antagonist muscles can occur , producing discernible signals for our EMG devices. Therefore, we pair gestures in our analysis to explore the correct identification of active muscle compartments. Results
  • the results are summarised in Figure 6 in the form of a confusion matrix.
  • Wrist-down and Hand-right were the most accurately reproduced poses, with 89% accuracy. This means that, at some time during exploration of the EMS pattern, the back of hand and/or fingers were stimulated to move in the target direction. For both of these poses, the error case moved in the direction of the target's opposing movement, Wrist-up and Hand-left, respectively.
  • EMS in HCI is currently restricted by two challenges. First, it is low resolution, supporting only coarse movements across a limited range of gestures and preventing opportunities for complex interaction techniques. Second, it requires expert calibration to determine correct electrode positioning and signal parameters. High density electrode arrays can both increase stimulation resolution, better supporting finer movements, and improve comfort and reduce fatigue. But they are complex to calibrate and are yet to be adopted in HCI.
  • EMG as a method of auto-calibrating EMS arrays.
  • the relatively high accuracy of the index-point gesture demonstrates that calibration of advanced poses can be achieved with the EMG-calibration technique with no increase in calibration time.
  • the participants did not vary the pulse widths and frequencies per channel, but instead used the pre-defined values (55Hz and 200 ⁇ 8). As varying parameters can target different muscle depths, this can result in increased accuracies for given stimulation patterns. Automatically determining stimulation frequencies from the EMG data is a prospect, but requires higher sampling rate than what is achieved in the current study.
  • the accuracy of the calibration process results from the accuracy of the EMG data.
  • the EMG data In our prototype, there is a distance of approximately 1 .5m between the EMG source and the signal amplification circuitry.
  • By moving the amplifiers closer to the source of the signal e.g. by embedding them into the sleeve itself, an improved EMG data resolution may be obtained.
  • Higher resolution, data rate, and calibration accuracy may also be obtained by using alternative hardware to the electrician Mega, such as a 5kHz EMG and a 16-bit analog to digital converter (ADC). Improving these factors would increase our EMG resolution and enable higher calibration accuracy.
  • the calibration time represents an improvement over existing techniques, 1 minute-per-pose is not the lowest time bound for this technique.
  • the method of the current invention includes reading between each electrode and its six neighboring electrodes. This is in order to improve reading accuracy along muscles that do not tend directly down the arm (pennate muscles, for example). This adds a complexity to our mapping procedure, as at any given electrode location, we do not know which electrode pair to favor.
  • the calibration approach of the present invention is a "per-pose" technique.
  • the electrodes are individually sewn into the sleeve and are constructed from conductive fabric.
  • the electrodes interface to the exterior of the sleeve with metal poppers.
  • the metal poppers are individually connected to the circuitry (as can be seen in Figure 1 , left).
  • the circuitry is controlled by a micro-controller.
  • Figure 7 details a high- level overview of the control process.

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Abstract

L'invention concerne un tissu de vêtement pouvant être porté pour la stimulation musculaire électrique (EMS) comprenant : - un réseau d'électrodes, où les électrodes sont configurées pour une électromyographie multicanal (EMG) et des impulsions EMS multicanaux ; - un système de commande EMG conçu pour collecter des données EMG dans le réseau d'électrodes quand le porteur du tissu fait une pose musculaire, et - un système de commande EMS conçu pour générer des impulsions EMS dans le réseau d'électrodes pour reproduire la pose musculaire, où les impulsions EMS sont étalonnées sur la base des données EMG collectées et traitées.
PCT/EP2018/073452 2017-08-31 2018-08-31 Tissu de vêtement pour lire et écrire une activité musculaire Ceased WO2019043147A1 (fr)

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WO2021248007A1 (fr) * 2020-06-06 2021-12-09 Battelle Memorial Institute Neuro-orthèse de préhension manuelle, portative et à porter sur soi
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FR3106037A1 (fr) 2020-01-09 2021-07-16 Intelinnov Survêtement multi électrodes de stimulation musculaire
EP4616805A3 (fr) * 2020-05-14 2025-11-05 Battelle Memorial Institute Étalonnage de cartographie électrode-muscle de stimulation électrique fonctionnelle
WO2021248007A1 (fr) * 2020-06-06 2021-12-09 Battelle Memorial Institute Neuro-orthèse de préhension manuelle, portative et à porter sur soi
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US12433529B1 (en) 2021-08-13 2025-10-07 Meta Platforms Technologies, Llc Wearable device with a band portion for determining gestures using differential neuromuscular sensors and an inertial measurement unit, and methods of use thereof
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CN115859140A (zh) * 2021-09-24 2023-03-28 苹果公司 用于手势识别的电极
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WO2023158850A1 (fr) * 2022-02-18 2023-08-24 Meta Platforms Technologies, Llc Configurations d'électrodes pseudomonopolaires pour détection d'emg
US12533504B2 (en) 2023-07-27 2026-01-27 Battelle Memorial Institute Portable and wearable hand-grasp neuro-orthosis

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