Electrode for physiological signal recognition

Abstract

The invention discloses an electrode for physiological signal recognition. Electrodes useful for determining a first type of physiological signal and a second type of physiological signal are disclosed. The first type of physiological signal may be an electromyogram (EMG) signal generated by activity of muscles and tendons. Gesture detection circuitry, such as an inertial measurement unit (IMU), may be used to supplement the identification of hand movement. The EMG signals may be processed to identify hand movements and identify gestures associated with those hand movements. The second type of physiological signal may be an electromyogram (ECG) signal generated by the heart. The electrodes may be used to detect EMG and ECG signals according to a current configuration of the sensing circuit. The electrode may be used to determine a measurement quality associated with the EMG signal.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of U.S. Provisional Application No. 63 / 581,965, filed on September 11, 2023, and U.S. Patent Application No. 18 / 824,712, filed on September 4, 2024, the contents of both applications are incorporated herein by reference in their entirety for all purposes. Technical Field

[0003] The present disclosure relates generally to gesture recognition and heart rate detection, and more particularly to electrodes for detecting gestures and for heart rate detection. Background Art

[0004] Many types of inputs may be provided for performing operations in a computing system, such as buttons or keys, a mouse, a trackball, a joystick, a touch sensor panel, a touch screen, and the like. In addition, other types of inputs, such as audio input (e.g., voice commands), accelerometer input (e.g., device motion, oscillation, and the like), and user gestures may also be provided as inputs. Specifically, a person's body motion (such as eye gaze, body movement, and the like) may be detected and tracked over time as input to a computing system. Specifically, hand gestures may be detected by touch or proximity sensors in a touch sensing panel. However, these sensors typically have a limited detection range, and therefore hand gestures must be performed close to the panel. Some computing systems may include circuits for detecting cardiac characteristics of a user of the computing system. In addition to detecting cardiac characteristics, attempts to integrate circuits to sense hand gestures typically require the manufacture of complex and bulky computing systems. Summary of the invention

[0005] Examples of the present disclosure relate to electrodes that can be formed in the back side of a device, which can be configured to detect hand gestures and movements of a user of the device and can be configured to detect the heartbeat of the user. In some examples, the device can configure the sensing circuit to measure the electrode to detect an electromyogram (EMG) signal, which is an electrical activity generated by muscle contraction. In some examples, the device configures the electrode to detect an EMG signal, which is generated by the activity of the flexor and extensor muscles and flexor and extensor tendons of the user's forearm, wrist and / or hand. The EMG signal can be routed to a processing circuit in the housing of the wrist-worn device. These EMG signals can be processed to identify hand movements, such as hand flexion, extension, internal rotation, external rotation, radial deviation, ulnar deviation, finger pinching and finger movement, and identify gestures and / or postures associated with those hand movements. In some examples, the device can be configured to detect an electrocardiogram (ECG) signal, which is an electrical activity generated by the palpitations of the user's heart. In some examples, the device configures the sensing circuit to measure the electrode to detect an ECG signal generated by the activity of the heart of the user. The ECG signal can be routed to a processing circuit contained in the device to determine the heart rate (HR) of the user. In some examples, the device also includes a posture detection circuit, such as one or more inertial measurement units (IMUs). The IMU can be configured to supplement the posture and / or movement detection determined using the EMG signal. In some examples, the device can detect the quality of the measurement associated with the EMG signal, such as the conductance between the electrodes detecting the EMG signal and / or the amount of noise coupled to the EMG signal. In some examples, when the quality of the measurement is not up to the optimal standard, the device can use the signal detected by the posture detection circuit to detect postures and / or gestures, and abandon the consideration of the EMG signal when the posture and / or gesture is detected. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Figure 1 Various hand movements that may be performed as part of hand gestures according to some examples of the present disclosure are illustrated.

[0007] Figure 2 Some examples of the present disclosure are illustrated which can be activated to perform Figure 1 The various muscles and tendons that are involved in various hand movements.

[0008] Figure 3 Example devices are illustrated in which electrodes may be configured to measure different types of physiological signals according to some examples of the present disclosure.

[0009] Figure 4 A block diagram of an example computing system illustrating one specific implementation of physiological signal capture and processing according to some examples of the present disclosure is illustrated.

[0010] Figure 5A Three representative electrodes and a simplified circuit of a device in a first configuration for measuring a first type of physiological signal according to examples of the present disclosure are illustrated.

[0011] Figure 5B Three representative electrodes and a simplified circuit of a device in a second configuration for measuring a second type of physiological signal according to examples of the present disclosure are illustrated.

[0012] Figure 6 Example configurations for detecting postures and gestures using one or more types of detection circuits included in an electronic device according to examples of the present disclosure are illustrated.

[0013] Figure 7 An example configuration of a circuit configured to detect a suboptimal physiological signal measurement condition according to an example of the present disclosure is illustrated. DETAILED DESCRIPTION

[0014] In the following description of the examples, reference is made to the accompanying drawings which form a part of the following description and in which are shown by way of illustration specific examples that can be practiced. It should be understood that other examples can be used and structural changes can be made without departing from the scope of the disclosed examples.

[0015] Examples of the present disclosure relate to electrodes that can be formed in a device (such as the back side of the device), which can be configured to detect hand gestures and movements of a user of the device and can be configured to detect the heartbeat of the user. In some examples, the device can configure the sensing circuit to measure the electrode to detect an electromyogram (EMG) signal, which is an electrical activity generated by muscle contraction. In some examples, the device configures the electrode to detect an EMG signal, which is generated by the activity of the flexor and extensor muscles and flexor and extensor tendons of the user's forearm, wrist and / or hand. The EMG signal can be routed to a processing circuit in the housing of the wrist-worn device. These EMG signals can be processed to identify hand movements, such as hand flexion, extension, internal rotation, external rotation, radial deviation, ulnar deviation, finger pinching and finger movement, and identify gestures and / or postures associated with those hand movements. In some examples, the device can be configured to detect an electrocardiogram (ECG) signal, which is an electrical activity generated by the palpitations of the user's heart. In some examples, the device configures the sensing circuit to measure the electrode to detect an ECG signal generated by the activity of the heart of the user. The ECG signal can be routed to a processing circuit contained in the device to determine the heart rate of the user. In some examples, the device also includes a posture detection circuit, such as one or more inertial measurement units (IMUs). The IMU can be configured to supplement the posture and / or movement detection determined using the EMG signal. In some examples, the device can detect the quality of the measurement associated with the EMG signal, such as the conductance between the electrodes detecting the EMG signal and / or the amount of noise coupled to the EMG signal. In some examples, when the quality of the measurement is not up to the optimal standard, the device can use the signal detected by the posture detection circuit to detect postures and / or gestures, and abandon the consideration of the EMG signal when the posture and / or gesture is detected.

[0016] Figure 1 Various hand movements that can be performed as part of a hand gesture according to some examples of the present disclosure are illustrated. For example, the hand 100 can perform one or more of wrist flexion 102, extension 104, radial deviation 106, ulnar deviation 108, internal rotation 110, or external rotation 112. Any of these movements or a combination of these movements can be performed as a gesture. In some examples, the hand 100 can perform a gesture while maintaining a wrist position. For example, the hand 100 can perform one or more gestures using one or more fingers. Additionally, the hand 100 can maintain one or more gestures performed by one or more fingers and / or a wrist corresponding to the user's hand 100. In some examples, the hand 100 can maintain a posture. For example, the hand 100 can maintain a pointing of one or more fingers, a fisting posture including curling of one or more fingers, and / or a pinching posture including contact between one or more fingers.

[0017] Figure 2 Some examples of the present disclosure are illustrated which can be activated to perform Figure 1 The various muscles and tendons that move the various hand 200. The forearm 214 includes the forearm extensor muscles 216 and flexor muscles 218, and the wrist extensor tendons 220 and flexor tendons 222. When these muscles and tendons contract or extend to perform Figure 1 When the hand 200 moves, electrical signals can be detected. Electromyography (EMG) can be used to measure the electrical activity generated by the contraction of the extensor muscles 216, the flexor muscles 218, the extensor tendons 220, and the flexor tendons 222. Based on the electrical activity, Figure 1 The various hand movements and gestures shown can be detected and used to initiate or perform various functions. Additionally, EMG can be used to detect muscle movement and tendon movement, the posture of one or more fingers and / or arms of the user and / or the muscle tension corresponding to the intensity of the posture (e.g., the pinching force applied by the muscles forming a pinching gesture).

[0018] The wrist is a common and socially acceptable location for housing electronics (e.g., smart watches, fitness trackers), and the muscles and tendons at this location can provide the electrical activity needed to detect hand movement and identify hand gestures and postures being performed. The wrist is also a common body contact point for determining a user's heart rate. Some examples of the present disclosure relate to devices that can perform both hand gesture and / or posture detection and heart rate detection of a user using a shared set of circuits (e.g., electrodes), thereby simplifying the bill of materials associated with such devices and thus reducing the cost and design complexity required to separately include circuits that perform both such functions.

[0019] Figure 3Example devices are illustrated in which electrodes may be configured to measure different types of physiological signals. In some examples, the wearable device includes multiple electrodes that may alternatively be configured to measure a first type of physiological signal (such as a signal for detecting a heart rate of a user of the wearable device during a first time period), or configured to measure a second type of physiological signal (such as a signal for detecting one or more gestures of the user). For example, electronic device 300 illustrates the back side of a wrist-worn wearable device (such as a smart watch) including a first electrode (electrode 302) and a second electrode (electrode 304). In some examples, electrode 302 and / or electrode 304 are "dry" electrodes that can directly contact the user's skin without requiring a dielectric medium (such as a dielectric gel) to improve coupling between electrode 302 and the user's skin and / or between electrode 304 and the user's skin. In some examples, as further described herein, characteristics of the electrodes (such as the material, size, one or more dimensions, shape, and / or placement of the electrodes) are configured to optimize physiological measurement of multiple types of physiological signals (such as signals associated with determining a user's heart rate, signals associated with detecting gestures performed by a user), and / or detecting a maintained posture of a portion of a user's body.

[0020] In some examples, the electronic device 300 includes circuits and / or software stored in a memory circuit, and the circuits and / or software stored in the memory circuit are configured to perform one or more operations of switching between a first operating mode or a second operating mode. For example, the electronic device 300 in the first operating mode is configured to detect the heart rate of the user. In some examples, the electronic device includes a display, such as a touch-sensitive display or a non-touch-sensitive display embedded in the housing of the electronic device 300. In some examples, the electronic device 300 is worn on the user's dominant hand. In some examples, the electronic device 300 displays a prompt in a user interface via a display, requesting the user to contact a position (such as the crown 306) included in the electronic device 300 with a non-dominant hand in order to perform an electrocardiogram measurement. Figure 3The crown 306 is included as a location included in the electronic device 300, however the example is not so limited. For example, other locations may include a bezel, a dedicated location on the housing of the electronic device 300, a location on the display of the electronic device 300, a band coupled to the electronic device 300, etc. Palpitations of the user's heart may cause electrical pulses to propagate outward from the heart, resulting in voltage (e.g., potential) differences along the user's skin. In some examples, these potentials may be detected by circuits (such as electrodes 302, 304) and / or locations included in the electronic device 300 (e.g., the crown 306), and the potentials may be processed and / or analyzed to determine the heart rate and other aspects of the user's physiological signals, such as an electrocardiogram (ECG). It should be understood that the examples of the present disclosure involving the use of the crown 306 to detect physiological signals may be additionally or alternatively implemented by detecting physiological signals via one or more of the locations included in the electronic device 300 described herein.

[0021] In this example, the electronic device 300 configures the multiplexer 308 to differentially couple the signals between the electrodes 302 and 304 to the ECG circuit 310, and to couple the crown 306 to a sensing circuit (e.g., included in or separate from the ECG circuit). For example, the multiplexer 308 includes one or more switches that couple the electrodes 302 and / or 304 to one or more amplifiers (e.g., a shared amplifier, such as an instrumentation amplifier), and / or one or more switches that couple the crown 306 to a circuit (e.g., a buffer and / or a filter). It should be understood that the ECG circuit 310 may include one or more amplifiers, passive circuits (e.g., including resistors, capacitors, inductors, etc.), active components (e.g., amplifiers and / or buffers), analog-to-digital converters (ADCs), additional or alternative circuits suitable for supplying analog signals and / or digital signals to the electronic device 300 for further processing to determine the user's heart rate.

[0022] In some examples, based on determining that the electronic device detects that contact between electrodes 302, electrodes 304, and / or crown 306 and the user's body satisfies one or more criteria, the electronic device 300 continues to perform an electrocardiogram (ECG) measurement. For example, one or more criteria include criteria that are satisfied when physical contact with the wrist of the dominant hand is sufficient to obtain a signal with a signal-to-noise ratio (SNR) above a first threshold, and / or criteria that are satisfied when physical contact with one or more body parts (such as fingers and / or palms of the non-dominant hand) is sufficient to obtain a signal with an SNR above a second threshold (the same or different from the first threshold). If one or more criteria are met, the electronic device 300 continues to detect physiological signals to perform ECG measurements. In some embodiments, before the electronic device 300 performs ECG measurements, meeting one or more criteria is mandatory, optional, or completely abandoned.

[0023] To measure physiological signals, crown 306 may serve as a measurement electrode, and electrodes 302 and 304 may serve as reference electrodes and / or ground electrodes, respectively (or vice versa) to perform ECG measurements. For example, physiological characteristics caused by the electrical activity of the user's heart may be measured via crown 306 (e.g., on the user's non-dominant hand that is not wearing electronic device 300). When the user's body is contacting crown 306, a conductive path may be created through a physiological signal source (e.g., the user's heart and / or other suitable tissue in the middle of the electrical path between crown 306 and electrodes 302 and / or 304).

[0024] The EKG / HR application 314 corresponds to software, such as one or more instructions stored in the memory of the electronic device 300, which is configured to convert one or more ECG measurements into an estimated value of the heart rate. In some embodiments, one or more ECG measurements are performed to provide multiple measurements of physiological signals to the EKG / HR application 314 to determine a set of measurements (e.g., averaging), thereby improving the confidence in determining the user's heart rate. In some examples, such signals are discarded based on determining that one or more signals correspond to erroneous measurements. In some examples, one or more signals provided to the EKG / HR application 314 are used to determine that the user's heart rate is abnormal, such as arrhythmia and / or an abnormally high or abnormally low heart rate. Thereafter, the EKG / HR application 314 may cause a display indicating such an abnormality, such as a warning display, via the display of the electronic device 300, and / or cause the generation of an auditory warning and / or a tactile warning, such as a ringtone, a whistle, and / or one or more vibrations of the electronic device 300.

[0025] Although examples and applications of electronic devices and methods are described in the context of generating a complete ECG waveform, it should be understood that the same or similar devices and methods can be used to collect and process data from multiple measurement electrodes, and ECG waveforms may or may not be generated. For example, signals from electrodes 302 and 304 may facilitate monitoring of certain cardiac characteristics (e.g., heart rate, arrhythmias, changes due to medications or surgery, function of pacemakers, heart size, etc.) and / or ECG waveform characteristics (e.g., timing, intervals, and complexes of ECG waveforms of certain waves) by a digital signal processor without generating a complete ECG waveform. In some examples, a controller may generate a subset of an ECG waveform (e.g., one or more of a P wave, a QRS complex wave, a PR interval, a T wave, and a U wave). In addition, examples of the present disclosure include contact detection and processing devices and methods configured for other types of physiological signal measurements (including but not limited to EEG measurements, EMG measurements, and / or optical determination results of heart rate).

[0026] Returning to the operating modes, the electronic device 300 may be configured to detect one or more gestures and / or postures of a portion of the user's body in the second operating mode. For example, in the second operating mode, the electronic device 300 may couple the electrode 302 and / or the electrode 304 to the EMG circuit 312 instead of the ECG circuit 310 via the multiplexer 308. It should be understood that the ECG circuit 310 and the EMG circuit 312 may optionally include a set of shared circuits (e.g., may share one or more amplifiers, passive components, analog-to-digital converters, filters, and / or other suitable circuits), and coupling to the ECG circuit 310 "instead of" coupling to the EMG circuit 312 may include coupling the electrode 302 and / or the electrode 304 to at least partially different circuits (e.g., different amplifiers, passive components, analog-to-digital converters, filters, and / or other suitable circuits) so as to be coupled to different signal lines, and vice versa. During the second operating mode, the EMG circuit 312 may condition and / or convert physiological signals (e.g., differential signals between the electrodes 302 and 304) to provide one or more signals indicating the current posture and / or movement of the user's hand (such as the dominant hand wearing the electronic device 300) to the gesture application 316. Figure 2 Gesture and / or posture detection of electronic device 300 is further described, and for the sake of brevity, further description of such detection is omitted herein. In some examples, crown 306 is not connected, terminated with a load, and / or measurement of crown 306 may be abandoned during the second operating mode. Therefore, during the second operating mode, electronic device 300 may reuse electrodes 302 and electrodes 304 to perform gesture and / or posture detection of the user. Therefore, electronic device 300 may selectively switch between heart rate detection and gesture detection using the same set of electrodes 302 and 304 during different operating modes. Configuring the electrodes to perform two different types of physiological measurements reduces the need to include additional or alternative electrodes, thereby potentially reducing the amount of material and / or manufacturing complexity required to include multiple electrodes configured to respectively implement different types of physiological measurements.

[0027] In some examples, during the second operating mode, one or more postures and / or gestures performed by the user's body (such as the dominant hand of the user wearing the electronic device 300) are determined. A hand movement "signature" consisting of various expected electrode measurements captured at certain times may be stored or determined empirically during product development or because the device is "trained" after the user performs a series of requested hand movements. During actual user hand movements, physiological measurements may be captured at electrodes 302 and 304 over a period of time and compared to known hand movement "signatures" by a processor included in the electronic device 300. If the captured data matches a specific hand movement "signature" or a series of signatures, the processor may identify the hand movement, gesture, and / or posture maintained. The number of electrode measurements to be taken may depend on the operating mode. For example, if only rough gesture recognition is needed (e.g., only a fist gesture, an open hand gesture, and / or a pinch gesture need to be detected), the electronic device 300 may only need to detect a first set of measurements (e.g., one, two, three, or four measurements) to generate three or four channels of data to detect muscle activity that matches the identification features of those gestures. However, if more gestures and / or more complex gestures are desired to be detected, additional measurements may need to be monitored.

[0028] In some examples, electronic device 300 includes a case, housing, or watch body that includes electrodes 302 and 304 and / or includes a device such as a strap for mechanically coupling electronic device 300 to the user's body. In some examples, electrodes 302 and / or 304 are embedded in the strap, and electrical measurements of physiological signals are coupled and transmitted to electronic device 300. Figure 3 In examples of, one or more wireless communication modules (e.g., Bluetooth low energy radio modules, Zigbee modules) may be required to facilitate transmission and / or reception of electrode signals to a separate device (e.g., a smartphone or other handheld or wearable device) for processing. In some examples, the electronic device 300 is a glove 336 having a flexible cuff (e.g., for AR / VR applications) that includes electrodes 302 and / or 304 electrically coupled to and / or communicatively coupled to the electronic device 300. It should be understood that the precise form of the electronic device 300 described herein is merely exemplary, and additional or alternative devices are contemplated without departing from the scope of the present disclosure.

[0029] Figure 4A block diagram of an example computing system 438 illustrating one specific implementation of physiological signal capture and processing according to some examples of the present disclosure is illustrated. Portions of the computing system 438 may be included, for example, in the electronic device 300 and / or any stand-alone mobile computing device or non-mobile computing device, wearable computing device, or non-wearable computing device for physiological signal analysis and / or display. The computing system 438 may include: one or more physiological electrodes 430 (e.g., EMG / ECG electrodes) for measuring electrical signals (e.g., EMG / ECG signals) from a person contacting the EMG / ECG electrodes; a data buffer 440 (or other volatile or non-volatile memory or storage device) for temporarily (or permanently) storing physiological signals from the physiological electrodes 430; a digital signal processor (DSP) 442 for analyzing and processing physiological signals; a host processor 444; a program storage device 446; and (in some examples) a touch screen 448 for performing display operations (e.g., for displaying real-time EMG / ECG signals or providing user alerts). In some examples, the touch screen 448 may be replaced by a non-touch-sensitive display.

[0030] The host processor 444 may be electrically coupled to a program storage device 446 (e.g., a non-transitory computer-readable storage medium) to execute instructions stored in the program storage device 446. The host processor 444 may, for example, provide control and data signals to generate display images, such as display images of a user interface (UI), on the touch screen 448. The host processor 444 may also receive outputs (e.g., EMG / ECG signals) from the DSP 442 and perform actions based on these outputs (e.g., display EMG / ECG signals, play sounds, provide tactile feedback, etc.). The host processor 444 may also receive outputs (touch inputs) from the touch screen 448 (or a touch controller, not shown). Such output from the DSP 442 may be used by a computer program stored in the program storage device 446 to perform actions, which may include, but are not limited to: moving an object (such as a cursor or pointer), scrolling or panning, adjusting a control setting, opening a file or document, viewing a menu, making a selection, executing an instruction, operating a peripheral device connected to the host device, answering a phone call, placing a phone call, terminating a phone call, changing volume or audio settings, storing information related to phone communications (such as addresses, frequently dialed numbers, received calls, missed calls), logging onto a computer or computer network, allowing authorized individuals to access restricted areas of a computer or computer network, loading a user profile associated with a preferred arrangement of a user's computer desktop, allowing access to web page content, launching a particular program, encrypting or decoding a message, etc. It should be understood that the output from the DSP 442 may be used to perform one or more operations at the electronic device 300 and / or at an additional or alternative device in communication with the electronic device 300 (such as other wearable (e.g., head-mounted) devices, laptop computers, desktop computers, media set-top boxes, etc.). The host processor 444 may also perform additional functions that may not be related to touch processing and display.

[0031] It is noted that one or more of the functions described herein, including the processing of physiological signals, may be performed by firmware stored in memory (e.g., in DSP 442) and executed by one or more processors (in DSP 442), or stored in program storage device 446 and executed by host processor 444. The firmware may also be stored and / or transmitted in any non-transitory computer-readable storage medium for use by or in conjunction with an instruction execution system, device, or apparatus (such as a computer-based system, a system containing a processor, or other system that can obtain instructions from an instruction execution system, device, or apparatus and execute the instructions). In the context of this document, a "non-transitory computer-readable storage medium" may be any medium (excluding signals) that can contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. The computer-readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared or semiconductor system, apparatus or device, a portable computer disk (magnetic), a random access memory (RAM) (magnetic), a read-only memory (ROM) (magnetic), an erasable programmable read-only memory (EPROM) (magnetic), a portable optical disk (such as a CD, CD-R, CD-RW, DVD, DVD-R or DVD-RW), or a flash memory (such as a compact flash card, a secure digital card, a universal serial bus (USB) memory device, a memory stick, etc.).

[0032] The firmware may also be transmitted in any transmission medium for use by or in conjunction with an instruction execution system, device, or apparatus (such as a computer-based system, a system including a processor, or other system that can obtain instructions from an instruction execution system, device, or apparatus and execute the instructions). In the context of this document, a "transmission medium" may be any medium that can convey, propagate, or transport the program for use by or in conjunction with an instruction execution system, device, or apparatus. The transmission medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, or infrared wired or wireless transmission media.

[0033] It should be understood that the computing system 438 is not limited to Figure 4 Rather, other or additional components (or components omitted) may be included in a variety of configurations according to various examples. For example, an analog-to-digital converter (ADC) may be added between the physiological electrodes 430 and the DSP 442 to convert the signals to the digital domain, or the touch screen 448 may be omitted, and the analysis and processing of the resulting EMG / ECG signals or other information may be relayed to another device (e.g., a tablet, laptop, smart phone, computer, server, etc.) via a wired or wireless connection, which may include a display or other feedback mechanism for outputting a visual representation of data or other notifications or information. Additionally, the components of the computing system 438 may be included within a single device, or may be distributed among multiple devices.

[0034] Figure 5A Three representative electrodes and a simplified circuit of a device in a first configuration for measuring a first type of physiological signal according to an example of the present disclosure are illustrated. Figure 5A In the embodiment, the differential measurement circuit 560 may be located in a device (e.g., Figure 3 The electronic device 300 may be in a housing and may include a processor 580 and analog front ends 582 and 583.

[0035] In some examples, during the first operating mode, differential measurement circuit 560 is configured to detect one or more physiological signals to determine the heart rate of the user of the device. For example, the user's non-dominant hand (e.g., the hand not wearing the device) contacts electrode 506, and differential measurement circuit 560 is configured to operate in the first operating mode. In the first operating mode, multiplexer 502 (e.g., corresponding to the embodiment of the present invention) Figure 3 The multiplexer 308 described herein optionally includes one or more switches to couple electrodes 530 and 564 (eg, corresponding to electrodes included in the crown 306, and Figure 3 The multiplexer 502 may be configured as a plurality of electrodes 502, 504, or electrodes 302, 3 ... In some examples, networks 570 and 572 may include circuit components (e.g., resistors, capacitors, inductors, amplifiers and / or buffers, and / or diodes) and / or may include impedances inherent in the signal path (e.g., routing impedances, parasitic impedances, etc.). In some examples, networks 570 and 572 may provide electrostatic discharge (ESD) protection for differential measurement circuit 560 and / or provide safety by limiting or preventing current from being applied to the user's skin and / or preventing unintended or unintentional external signals from entering the device and causing damage. Networks 570 and 572 are therefore configured to condition the signal indicative of the physiological measurement provided by physiological signal source 568, thereby feeding the signal back to amplifier 584.

[0036] In some examples, the analog front end 583 includes an amplifier 584 and an analog-to-digital converter (ADC) 586. An electrocardiogram (ECG) waveform may be generated based on the electrical activity of the heart during each heartbeat measured differentially between the electrode 530 and the electrode 564. In some examples, the amplifier 584 may output an amplified differential signal, and the ADC 586 may convert the amplified differential signal into a digital signal. In some examples, the amplifier 584 may output an amplified single-ended output. In some examples, the output of the ADC 586 may be a multi-bit signal (e.g., 8 bits, 12 bits, 24 bits, etc.) electrically coupled to the processor 580. The multi-bit signal may be transmitted serially or in parallel from the analog front end 583 to the processor 580. In some examples, the ADC 586 may be a differential ADC that converts a differential analog input into a digital output. In some examples, the ADC 586 may be a single-ended ADC that converts a single-ended analog input into a digital output. In some examples, differential amplifier 584 may be implemented using two single-ended amplifiers, and ADC 586 may be implemented using two ADCs, each electrically coupled to an output of one of the single-ended amplifiers. In a first mode of operation, multiplexer 504 is configured to couple one or more outputs of ADC 586 to processor 580 for further processing, such as via one or more switches, to determine a heart rate of the user.

[0037] As described above, electrodes 530 and 564 may come into contact with the user's body. When electrodes 530 and 564 contact the user's body (e.g., contact a portion of the non-dominant hand and / or the wrist of the dominant hand, respectively), the electrodes may receive a first type of physiological signal indicating a heart rate from the user. Figure 5A , the first type of physiological signal is represented as physiological signal source 568. In some examples, when the user touches electrode 530, a path from electrode 530 to electrode 564 can be created through physiological signal source 568. In some examples, contacting electrode 530 can cause differential measurement circuit 560 to measure the physiological signal from physiological signal source 568, which is then used to determine the user's heart rate, as shown in FIG. Figure 3 Further described.

[0038] Figure 5BThree representative electrodes and simplified circuits of a device in a second configuration for measuring a second type of physiological signal according to examples of the present disclosure are illustrated. In some examples, during the second operating mode, the differential measurement circuit 560 is configured to detect one or more physiological signals in the second configuration, the one or more physiological signals indicating a maintained posture and / or gesture of one or more body parts of a user of the device. For example, in the second operating mode, a physiological source 569 is coupled to electrodes 564 and 506, the physiological source representing electrical pulses caused by movement of tendons, muscles, and / or other tissues in the user's hand and / or arm. Electrodes 564 and 506, as previously described, optionally correspond to Figure 3 302 and 304. In such examples, electrode 530 is optionally not used (e.g., disconnected, terminated with a load, and / or ignored for purposes of EMG determination). In some examples, electrode 506 is coupled to multiplexer 502 via network 516 having one or more features similar or identical to the features described with reference to networks 570 and / or 572. In some examples, electrode 564 is also coupled to multiplexer 502, similar or identical to that described with reference to the first operating mode. However, in comparison to the first operating mode, multiplexer 502 is configured to provide a signal path from electrode 564 to amplifier 576 via one or more switches included in multiplexer 502 when configured in the second configuration. In some examples, electrodes 564 and 506 are configured as differential inputs to amplifier 576, similar or identical to that previously described with reference to electrodes coupled to amplifier 584, as previously described with reference to Figure 5A As described. In such examples, the analog front end 582 provides amplification of one or more outputs from the amplifier 576, thereby amplifying one or more physiological signals indicating the movement and / or posture of the user. Similar to the ADC 586, the ADC 578 is coupled to an amplifier (e.g., the amplifier 576), and optionally quantizes the analog output from the amplifier, thereby providing a digital representation of the value of the analog output to the multiplexer 504. During the second operating mode, the multiplexer 504 is configured to couple one or more outputs of the ADC 578 to the processor 580, thereby supplying the processor 580 with digital measurements of the movement and / or posture of the user. In some examples, the differential measurement circuit 560 is configured to share the ADC between the outputs of the amplifiers 584 and 576. For example, the multiplexer 504 is optionally coupled to the outputs of the amplifiers 584 and 576, and selectively couples the output of the amplifier 584 or 576 to the shared ADC when operating in the first operating mode or the second operating mode.

[0039] Figure 6Example configurations for detecting postures and gestures using one or more types of detection circuits included in an electronic device according to some examples of the present disclosure are illustrated. In some examples, an electronic device (e.g., a wearable electronic device) may be configured to detect postures and gestures of a user's body using one or more types of posture and gesture detection circuits, either alone or in some combination. For example, the electronic device 600 includes a plurality of gesture detection modules, which correspond to the gesture detection modules included in the electronic device. Figure 3 The circuits and / or software and / or instructions in the electronic device 300 of the embodiment of the present invention. It should be understood that the gesture detection module may refer to circuits and / or software instructions that are configured to detect postures and gestures. The gyroscope module 644, for example, optionally includes one or more gyroscopes that are configured to detect the orientation and / or movement of the electronic device 600 and / or the housing of the electronic device. In some examples, the gyroscope module 644 includes one or more micro-electromechanical systems (MEMS) devices (e.g., accelerometers, magnetometers, and / or gyroscopes, such as one or more inertial measurement units (IMUs)), which are configured to detect the movement and / or orientation of the electronic device 600. In some examples, the gyroscope module 644 can be used to detect the movement of the electronic device (such as the translation of the device, the rotation along one or more axes of the device, and / or the maintenance of the electronic device at a specific orientation and / or position), thereby providing information and / or data for further processing. The information and / or data obtained from the gyroscope module 644 is provided to the software included in the electronic device 600 via one or more data channels so as to be provided to the model module 654. In some examples, as further described herein, the model module 654 includes one or more algorithms and / or machine learning models configured to process and / or refine data associated with the movement and / or posture of the body (e.g., arm, hand, and / or finger) of the user wearing the electronic device 600. In some examples, multiple model modules are included in the electronic device 600. For example, the gyroscope module 644, the optical module 648, and / or the EMG module 650 are respectively communicatively coupled to the corresponding model module. The corresponding model module may have similar or identical features as described with reference to the model module 654. Additionally, the corresponding model module may be configured to detect, adjust, process, analyze, and / or otherwise manipulate information and / or data received by its corresponding gesture detection module (e.g., the gyroscope module 644, the optical module 648, and / or the EMG module 650). For example, the corresponding model module is optimized to perform operations based on characteristics of data and / or information obtained from its corresponding gesture detection module, such as being optimized to perform operations with respect to EMG data obtained from EMG module 650, but not necessarily optimized to perform operations with respect to optical module 648.

[0040] In some examples, the electronic device 600 includes an optical circuit configured to detect features of the user's vascular system. For example, the optical module 648 optionally represents a circuit configured to perform volume tracing. As an example, the optical module 648 optionally includes one or more light sources (e.g., light emitting diodes (LEDs)) configured to generate light and / or detect transmission absorption and / or reflection incident on the user's tissue. Such one or more light sources can be used to detect pulse oximetry as a supplement or alternative to detecting a heart rate estimate of the user. In some examples, the optical module 648 optionally uses one or more light sources to detect an indication of movement, such as blood flowing into and out of the tissue in response to muscle and / or tendon contraction of the user's body. In some examples, similar to as described with reference to the gyroscope module 644, the electronic device 600 detects a signal via the optical module 648 and converts the signal into information and / or data supplied to the model module 654.

[0041] In some examples, the electronic device 600 includes an EMG module 650. The EMG module includes one or more circuits and / or references. Figures 3 to 5B For the sake of brevity, further description of the EMG circuit is omitted.

[0042] In some examples, the electronic device 600 communicates information and / or data obtained via the gyroscope module 644, the optical module 648, and / or the EMG module 650 to the model module 654 via one or more data channels, respectively configured to carry data from the modules to the model module 654, and through the multiplexer 652. For example, the multiplexer 652 may represent hardware switching circuitry and / or software that includes instructions configured to select or combine signals and / or data received via one or more data channels and provide the data to the model module 654. The model module 654 may be stored in a memory of the electronic device 600 and may include instructions for performing operations (e.g., running algorithms to analyze data, and / or applying one or more machine learning models) based on data from the various modules described herein.

[0043] In some examples, the electronic device 600 applies the information and / or data obtained from the model module 654 to the fusion module 656. Similar to the model module 654, the fusion module 656 may be stored in the memory of the electronic device 600, and may include instructions for performing operations (e.g., running an algorithm for analyzing data, and / or applying one or machine learning models) to synthesize information and data indicating the movement and / or posture of the user's body. For example, the fusion module 656 may be configured to estimate the kinematic state of the user's body. As an example, the fusion module 656 may use the data and / or information involved in the model module 654 as an indication of the user's posture and movement to determine the previous state, current state, and / or possible state of the user's arm, hand, and / or finger. In some examples, the fusion module 656 may use one or more Karlman filters to recursively identify the current posture and / or gesture based on the previously identified posture and / or gesture. Additionally or alternatively, the fusion module 656 may use one or more machine learning and / or deep learning models (including but not limited to Bayesian networks, convolutional neural networks (CNNs), and / or other suitable techniques) to ascertain the relative weights and / or confidences of one or more data sources (e.g., modules described herein) in determining the current and / or future postures and / or movements of the user's body. For example, as further described below, when it is determined that the measurement environment in which the EMG data is obtained is not up to the optimal standard, the EMG data may be discarded. In some examples, the fusion module 656 provides information and / or data indicating the current and / or future postures and / or movements of the electronic device 600 to the gesture event module 658. The gesture event module 658 may use such information and / or data to perform one or more operations further described herein (e.g., navigating a user interface, answering a call, causing a cursor to move, etc.). In some examples, the model module 654 and the fusion module 656 are combined into a single model module. It should be understood that such a combined model module may have one or more features similar or identical to the features described with reference to the constituent modules of this article.

[0044] Figure 7 An example configuration of a circuit configured to detect a suboptimal physiological signal measurement condition according to an example of the present disclosure is illustrated.

[0045] In some examples, the electronic devices described herein are configured to detect suboptimal measurement conditions. For example, when attempting to obtain EMG data, the electronic device may detect that excessive moisture and / or dirt has accumulated between the user's skin and the measurement electrodes, and / or excessive noise is coupled to the EMG signal, thereby causing erroneous EMG data, thereby (e.g., when at least partially relying on the EMG signal) adversely affecting the determination of hand posture and / or movement. In some examples, when the conductance between electrodes 702 and 704 exceeds a threshold value (e.g., or ) and / or when the noise level exceeds a threshold noise level (e.g., 500 μV, 750 μV, 1000 μV, 2000 μV, 3000 μV, 4000 μV, or 5000 μV), a suboptimal measurement environment is determined. For example, the electronic device optionally grounds the first electrode 704 and uses the second electrode 702 (e.g., corresponding to Figure 3 Conductivity measurement is performed on the electrodes 302 and / or 304 of the amplifier 700. In some examples, the electronic device 700 includes a stimulation circuit 720, such as including a stimulation and / or waveform generator 722, which is coupled to inject a signal via a digital-to-analog converter (DAC) 724 at a node 719 (where the second electrode is fed into the input of the amplifier 721) (e.g., injecting a signal at a location where the second electrode 702 is coupled to the input of the amplifier 721 via one or more filters, signal conditioning circuits (such as an impedance divider), and / or a buffer included in the signal conditioning circuit 718). In some examples, the node 719 is coupled to a first input of the amplifier 721 (e.g., a non-inverting input), and a second input of the amplifier 721 (e.g., an inverting input) is coupled to the output of the amplifier 721 to provide negative feedback. In some examples, the output of the amplifier 721 is coupled to a filter 726 (e.g., an electromagnetic interference filter). In some examples, the filter 726 is coupled (e.g., differentially) to another amplifier 728 (such as a variable gain amplifier), and / or to a low pass filter. The output of the other amplifier 728 and / or the low pass filter may optionally be coupled to an analog-to-digital converter (ADC) 730, and one or more outputs of the ADC are optionally coupled to additional signal conditioning circuits (e.g., a high pass filter 732 and a decimation filter 734, and / or a filter and IQ demodulator 736 and / or an impedance calculator 738) to obtain information and / or data to obtain an indication of the impedance and / or conductance between the first electrode 704 and the second electrode 702, respectively.

[0046] In some examples, when the conductance is determined to be greater than a threshold level of conductance (e.g., or ), the electronic device 700 determines that the EMG measurement data may be unreliable, and therefore may reduce the priority of EMG data that could otherwise be used to detect the user's body movement and / or gesture or discard the EMG data. In some examples, conductance and / or noise thresholding is evaluated simultaneously or separately. In some examples, the conductance and / or noise values ​​are determined within a sliding time period. For example, the electronic device 700 optionally compares the conductance and / or noise values ​​with corresponding thresholds, where the values ​​are periodically determined within 0.05 seconds, 0.1 seconds, 0.5 seconds, 1 second, 1.5 seconds, 2 seconds, 3 seconds, or 5 seconds of determining the current conductance and / or noise sample. In some examples, the electronic device 700 configures the stimulation circuit 720, the switching circuit, and / or the electrodes 702 and 704 to detect conductance and / or detect noise based on determining that a posture and / or gesture will be or is being provided by the user. For example, an operating system included in the memory of the electronic device 700 optionally indicates that an application hosted by the electronic device 700 will need to move, and before detecting a posture and / or movement, the electronic device 700 is configured to determine the quality of the measurement environment. Additionally or alternatively, the fusion module 656 optionally provides data and / or information that indicates that the data obtained from the EMG module 650 indicates that the user's current posture and / or movement is a first posture and / or movement, and the gyroscope module 644 and / or the optical module 648 indicate that the user's current posture and / or movement is a different second posture and / or movement. In order to verify the data obtained from the EMG module 650, the electronic device 700 may actively perform the measurement quality detection described herein, and / or update the fusion module 656 with information to determine the reliability and / or weight of the information and / or data derived from the EMG module 650. It should be understood that the examples described herein are merely exemplary, and additional or alternative events may lead to measurement quality assessments.

[0047] In some examples, when one or both of the conductance and / or noise level exceeds their respective threshold levels, the electronic device may reduce the priority of EMG data used to detect movement and / or posture of the user's body or discard the EMG data. Therefore, in addition to detecting EMG and / or ECG signals, the electrodes can also be used to determine that there are suboptimal measurement conditions for detecting physiological signals (e.g., EMG signals). Therefore, in some examples, based on determining that the quality of the measurement environment meets one or more criteria, the electronic device may perform physiological measurements to detect postures and / or gestures of the user's body (e.g., fingers, hands, and / or arms wearing the electronic device). In some examples, one or more criteria include: a criterion satisfied when the conductance level between the electrodes is greater than a conductance threshold level, and a criterion satisfied when the noise level included in one or more physiological signals (e.g., EMG signals) is greater than a noise threshold level.

[0048] For the purpose of explanation, the foregoing description is described by reference to specific embodiments. However, the above exemplary discussion is not intended to be exhaustive or to limit the present invention to the disclosed precise form. According to the above teachings, many modifications and variations are possible. The selection and description of the embodiments are in order to best illustrate the principles of the present invention and its practical application, so that other persons skilled in the art can best use the present invention and the various described embodiments with various modifications suitable for the specific purposes contemplated.

[0049] As described above, one aspect of the present technology is to collect and use data available from various sources to improve the user experience. The present disclosure contemplates that, in some instances, the collected data may include personal information data that uniquely identifies or can be used to contact or locate a specific person. Such personal information data may include demographic data, location-based data, phone numbers, email addresses, Twitter IDs, home addresses, data or records related to the user's health or fitness level (e.g., vital sign measurements, medication information, exercise information), date of birth, or any other identification or personal information.

[0050] The present disclosure recognizes that the use of such personal information data in the present technology can be used to benefit the user. For example, the personal information data can be used to improve the user experience. In addition, the present disclosure also contemplates other uses of personal information data that benefit the user. For example, health and fitness data may be used to provide insights into the user's overall health, or may be used as positive feedback to individuals who use technology to pursue health goals.

[0051] The disclosure envisions that entities responsible for collecting, analyzing, disclosing, transmitting, storing or other such personal information data use will comply with established privacy policies and / or privacy practices. Specifically, such entities should implement and adhere to the use of privacy policies and practices that are recognized as meeting or exceeding industry or government requirements for maintaining the privacy and security of personal information data. Such policies should be easily accessible to users and should be updated as changes in the collection and / or use of data occur. Personal information from users should be collected for the legal and reasonable purposes of the entity and not shared or sold outside these legal uses. In addition, such collection / sharing should be performed after receiving the user's informed consent. Additionally, such entities should consider taking any necessary steps to protect and safeguard access to such personal information data, and ensure that other entities with access to personal information data comply with their privacy policies and procedures. In addition, such entities can subject themselves to third-party assessments to prove that they comply with widely accepted privacy policies and practices. In addition, policies and practices should be suitable for specific types of personal information data being collected and / or accessed, and comply with applicable laws and standards (including considerations of specific jurisdictions). For example, in the United States, the collection or access of certain health data may be governed by federal and / or state laws, such as the Health Insurance Portability and Accountability Act (HIPAA), while health data in other countries may be subject to other regulations and policies and should be handled accordingly. Therefore, different privacy practices should be maintained in each country for different types of personal data.

[0052] Regardless of the foregoing, the present disclosure also contemplates implementation schemes in which users selectively block the use or access of personal information data. That is, the present disclosure contemplates that hardware elements and / or software elements may be provided to prevent or block access to such personal information data. For example, the technology of the present invention may be configured to allow users to choose to "opt in" or "opt out" of participating in the collection of personal information data during registration for a service or at any time thereafter. In addition to providing "opt-in" and "opt-out" options, the present disclosure also contemplates providing notifications related to access or use of personal information. For example, a user may be notified that their personal information data will be accessed when downloading an application, and then be reminded again before the personal information data is accessed by the application.

[0053] In addition, it is the intention of the present disclosure that personal information data should be managed and processed in a manner that minimizes the risk of unintentional or unauthorized access or use. Once the data is no longer needed, the risk can be minimized by limiting data collection and data deletion. In addition and when applicable (including in certain health-related applications), data de-identification can be used to protect user privacy. De-identification can be facilitated by removing specific identifiers (e.g., date of birth, etc.), controlling the amount or specificity of stored data (e.g., collecting location data at the city level rather than at the address level), controlling the manner in which data is stored (e.g., aggregating data among users), and / or other methods when applicable.

[0054] Thus, while the present disclosure broadly covers the use of personal information data to implement one or more of the various disclosed embodiments, the present disclosure also contemplates that various embodiments may also be implemented without access to such personal information data. That is, various embodiments of the present technology will not fail to function properly due to the lack of all or a portion of such personal information data. For example, a user experience may be generated by inferring preferences based on non-personal information data or a minimal amount of personal information (such as content requested by a device associated with a user, other non-personal information available to a service, or publicly available information).

[0055] Therefore, in accordance with the above, some examples of the present disclosure relate to a wearable device. In some examples, the wearable device may include a plurality of electrodes, a sensing circuit, a posture detection circuit different from the sensing circuit, and one or more processors. In some examples, in a first operating mode, the one or more processors may be configured to configure the plurality of electrodes and the sensing circuit in a first configuration to use the plurality of electrodes and the posture detection circuit to detect a first physiological signal corresponding to a first type of physiological measurement. In some examples, in a second operating mode, the one or more processors may be configured to configure the plurality of electrodes and the sensing circuit in a second configuration to use the plurality of electrodes to detect a second physiological signal corresponding to a second type of physiological measurement, which is different from the first type of physiological measurement.

[0056] Additionally or alternatively to one or more of the examples disclosed above, in some examples, the first type of physiological measurement may be an electromyogram.

[0057] Additionally or alternatively to one or more of the examples disclosed above, in some examples, the second type of physiological measurement may be an electrocardiogram.

[0058] Additionally or alternatively to one or more of the examples disclosed above, in some examples, the gesture detection circuitry may include one or more inertial measurement units (IMUs).

[0059] In addition or alternatively to one or more of the examples disclosed above, in some examples, the wearable electronic device may further include a switching circuit and a plurality of amplifiers, the plurality of amplifiers including a first amplifier and a second amplifier. In some examples, in the first operating mode, a first pair of electrodes in the plurality of electrodes may be differentially coupled to the first amplifier via the switching circuit, and in the second operating mode, a second pair of electrodes in the plurality of electrodes that is different from the first pair of electrodes in the plurality of electrodes may be differentially coupled to the second amplifier via the switching circuit.

[0060] In addition to or alternatively to one or more of the examples disclosed above, in some examples, the sensing circuit may include one or more analog-to-digital converters (ADCs) coupled to the output ends of the first amplifier and the second amplifier.

[0061] In addition or alternatively to one or more of the examples disclosed above, in some examples, the one or more processors may also be configured to use one or more machine learning models to detect movement of a portion of a body of a user wearing the wearable electronic device during the first operating mode.

[0062] In addition or alternatively to one or more of the examples disclosed above, in some examples, the portion of the user's body may include a hand of the user wearing the wearable electronic device, and using the one or more machine learning models to detect the movement of the portion of the user's body may include determining a predicted gesture corresponding to the movement of the hand.

[0063] In addition or alternatively to one or more of the examples disclosed above, in some examples, the processor may also be configured to use one or more machine learning models to detect the posture of a portion of a body of a user wearing the wearable electronic device during the first operating mode.

[0064] In addition or alternatively to one or more of the examples disclosed above, in some examples, the portion of the user's body may include a hand of the user wearing the wearable electronic device, and using the one or more machine learning models to detect the posture of the portion of the user's body may include determining a predicted posture of the hand.

[0065] As a supplement or alternative to one or more of the examples disclosed above, in some examples, the wearable electronic device may also include a stimulation circuit that can be coupled to one of the multiple electrodes and the sensing circuit to inject a test signal into the sensing circuit. In some examples, the one or more processors may also be configured to: determine the quality of the first physiological measurement from the sensing circuit based on the injected test signal; and based on determining that the quality of the first physiological measurement meets one or more criteria, use the first physiological signal and the posture detection circuit to detect the movement of a part of the body of the user wearing the wearable electronic device; and based on determining that the quality of the first physiological measurement does not meet the one or more criteria, use the posture detection circuit to detect the movement of the part of the user's body, thereby abandoning the use of the first physiological signal to detect the movement.

[0066] In addition or alternatively to one or more of the examples disclosed above, in some examples, the one or more criteria include a criterion that can be satisfied when the conductance between a first electrode of the plurality of electrodes and a second electrode of the plurality of electrodes is greater than a conductance threshold level.

[0067] In addition or alternatively to one or more of the examples disclosed above, in some examples, the one or more criteria may include a criterion that may be satisfied when a noise level associated with the first physiological signal is greater than a threshold noise level.

[0068] As a supplement or alternative to one or more of the examples disclosed above, in some examples, the wearable electronic device may also include a stimulation circuit that can be coupled to one of the multiple electrodes and the sensing circuit to inject a test signal into the sensing circuit. In some examples, the one or more processors may also be configured to: determine the quality of the first physiological measurement from the sensing circuit based on the injected test signal; and based on determining that the quality of the first physiological measurement meets one or more criteria, use the first physiological signal and the posture detection circuit to detect the posture of a part of the body of the user wearing the wearable electronic device; and based on determining that the quality of the first physiological measurement does not meet the one or more criteria, use the posture detection circuit to detect the posture of the part of the user's body, thereby abandoning the use of the first physiological signal to detect the movement.

[0069] Some examples of the present disclosure relate to a non-transitory computer-readable medium storing instructions. In some examples, the one or more instructions may be configured to cause one or more processors included in a wearable electronic device (including multiple electrodes, a sensing circuit, and a posture detection circuit different from the sensing circuit) to configure the multiple electrodes and the sensing circuit in a first configuration in a first operating mode to use the multiple electrodes and the posture detection circuit to detect a first physiological signal corresponding to a first type of physiological measurement. In some examples, the one or more instructions may be configured to cause the one or more processors to configure the multiple electrodes and the sensing circuit in a second configuration in a second operating mode to use the multiple electrodes to detect a second physiological signal corresponding to a second type of physiological measurement, which is different from the first type of physiological measurement.

[0070] Some examples of the present disclosure relate to a method of operating a wearable electronic device, the wearable electronic device comprising a plurality of electrodes, a sensing circuit, and a posture detection circuit different from the sensing circuit. In some examples, the method may include: in a first operating mode, configuring the plurality of electrodes and the sensing circuit in a first configuration to detect a first physiological signal corresponding to a first type of physiological measurement using the plurality of electrodes and the posture detection circuit. In some examples, the method may include: in a second operating mode, configuring the plurality of electrodes and the sensing circuit in a second configuration to detect a second physiological signal corresponding to a second type of physiological measurement using the plurality of electrodes, the second type of physiological measurement being different from the first type of physiological measurement.

[0071] Some examples of the present disclosure involve detecting, analyzing, and storing health data. It should be understood that health data storage and use are performed in accordance with best practices to ensure the anonymity and privacy of user data.

[0072] Although the examples of the present disclosure have been fully described with reference to the accompanying drawings, it should be noted that various changes and modifications will become apparent to those skilled in the art. It should be understood that such changes and modifications are understood to be included within the scope of the examples of the present disclosure defined by the appended claims.

Claims

1. A wearable electronic device, comprising: Multiple electrodes; Sensing circuit; a gesture detection circuit, the gesture detection circuit being different from the sensing circuit; and One or more processors, wherein the one or more processors are configured to: In the first operating mode: configuring the plurality of electrodes and the sensing circuit in a first configuration to detect a first physiological signal corresponding to a first type of physiological measurement using the plurality of electrodes and using the gesture detection circuit; as well as In the second operating mode: The plurality of electrodes and the sensing circuit are configured in a second configuration to detect a second physiological signal corresponding to a second type of physiological measurement different from the first type of physiological measurement using the plurality of electrodes.

2. The wearable electronic device of claim 1, wherein the first type of physiological measurement is an electromyogram.

3. The wearable electronic device of claim 1, wherein the second type of physiological measurement is an electrocardiogram. 4 . The wearable electronic device of claim 1 , wherein the gesture detection circuit comprises one or more inertial measurement units.

5. The wearable electronic device according to claim 1, further comprising: Switching circuits; and a plurality of amplifiers, the plurality of amplifiers comprising a first amplifier and a second amplifier, wherein: In the first operating mode, a first pair of electrodes of the plurality of electrodes are differentially coupled to the first amplifier via the switching circuit, and In the second operating mode, a second pair of electrodes of the plurality of electrodes different from the first pair of electrodes of the plurality of electrodes is differentially coupled to the second amplifier via the switching circuit.

6. The wearable electronic device of claim 5, wherein the sensing circuit comprises one or more analog-to-digital converters coupled to outputs of the first amplifier and the second amplifier.

7. The wearable electronic device of claim 1 , wherein the one or more processors are further configured to: During the first operating mode, one or more machine learning models are used to detect movement of a portion of a body of a user wearing the wearable electronic device.

8. A wearable electronic device according to claim 7, wherein the part of the user's body includes a hand of the user wearing the wearable electronic device, and using the one or more machine learning models to detect the movement of the part of the user's body includes determining a predicted gesture corresponding to the movement of the hand.

9. The wearable electronic device of claim 1 , wherein the one or more processors are further configured to: During the first operating mode, one or more machine learning models are used to detect a posture of a portion of a body of a user wearing the wearable electronic device.

10. A wearable electronic device according to claim 8, wherein the part of the user's body includes a hand of the user wearing the wearable electronic device, and using the one or more machine learning models to detect the posture of the part of the user's body includes determining a predicted posture of the hand.

11. The wearable electronic device according to claim 1, further comprising: a stimulation circuit capable of being coupled to one of the plurality of electrodes and the sensing circuit for injecting a test signal into the sensing circuit, wherein the one or more processors are further configured to: determining a quality of the first physiological signal from the sensing circuit based on the injected test signal, and Based on determining that the quality of the first physiological signal satisfies one or more criteria: detecting movement of a portion of a body of a user wearing the wearable electronic device using the first physiological signal and using the gesture detection circuit, and Based on determining that the quality of the first physiological signal does not meet the one or more criteria, using the gesture detection circuit to detect the movement of the portion of the user's body, thereby abandoning the use of the first physiological signal to detect the movement.

12. The wearable electronic device of claim 11, wherein the one or more criteria include a criterion that is satisfied when a conductance between a first electrode of the plurality of electrodes and a second electrode of the plurality of electrodes is greater than a conductance threshold level.

13. The wearable electronic device of claim 11, wherein the one or more criteria include a criterion that is satisfied when a noise level associated with the first physiological signal is greater than a threshold noise level.

14. The wearable electronic device according to claim 1, further comprising: a stimulation circuit capable of being coupled to one of the plurality of electrodes and the sensing circuit for injecting a test signal into the sensing circuit, wherein the one or more processors are further configured to: determining a quality of the first physiological signal from the sensing circuit based on the injected test signal, and Based on determining that the quality of the first physiological signal satisfies one or more criteria: detecting a posture of a part of a body of a user wearing the wearable electronic device using the first physiological signal and using the posture detection circuit, and Based on determining that the quality of the first physiological signal does not meet the one or more criteria, using the gesture detection circuit to detect the gesture of the portion of the user's body, thereby abandoning the use of the first physiological signal to detect the gesture.

15. A non-transitory computer-readable medium storing instructions, wherein the one or more instructions are configured to cause one or more processors included in a wearable electronic device to perform the following operations, the wearable electronic device also including a plurality of electrodes, a sensing circuit, and a gesture detection circuit different from the sensing circuit: In the first operating mode: configuring the plurality of electrodes and the sensing circuit in a first configuration to detect a first physiological signal corresponding to a first type of physiological measurement using the plurality of electrodes and using the gesture detection circuit; and In the second operating mode: The plurality of electrodes and the sensing circuit are configured in a second configuration to detect a second physiological signal corresponding to a second type of physiological measurement different from the first type of physiological measurement using the plurality of electrodes.

16. A method of operating a wearable electronic device, the wearable electronic device comprising a plurality of electrodes, a sensing circuit, and a gesture detection circuit different from the sensing circuit, the method comprising: In the first operating mode: configuring the plurality of electrodes and the sensing circuit in a first configuration to detect a first physiological signal corresponding to a first type of physiological measurement using the plurality of electrodes and using the gesture detection circuit; as well as In the second operating mode: The plurality of electrodes and the sensing circuit are configured in a second configuration to detect a second physiological signal corresponding to a second type of physiological measurement different from the first type of physiological measurement using the plurality of electrodes.

17. The non-transitory computer readable medium storing instructions of claim 15, wherein the first type of physiological measurement is an electromyogram.

18. The non-transitory computer readable medium storing instructions of claim 15, wherein the second type of physiological measurement is an electrocardiogram.

19. The method of claim 16, wherein the first type of physiological measurement is electromyography.

20. The method of claim 16, wherein the second type of physiological measurement is an electrocardiogram.

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