Electronic device for providing strength training guide and operating method thereof

Abstract

Disclosed are an electronic device providing a strength training guide and an operating method thereof. A wearable electronic device may comprise a biometric sensor including at least one light emitter and at least one light receiver. The wearable electronic device may, while an application related to strength training is running, acquire biometric data related to a user's blood flow via the biometric sensor, and identify a change in the user's grip strength on the basis of a change in blood flow appearing in the biometric data due to strength training performed by the user. The wearable electronic device may generate training information related to the strength training on the basis of a result of the identification, and provide the generated training information to the user. Various embodiments identified through the present document are also possible.

Description

Electronic device providing a strength training guide and its method of operation

[0001] The present disclosure relates to an electronic device and a method of operating the same, and more specifically, to an electronic device and a method of operating the same that provides a muscle strength exercise guide.

[0002] With the recent advancement of mobile communication technology, the use of portable or mobile electronic devices (e.g., smartphones, wearable electronic devices, mobile terminals, or tablet PCs) has become widespread, and the services that can be provided through these electronic devices are becoming increasingly diverse. Since these electronic devices are implemented in a form that users can carry or wear and are closely integrated into their daily lives, they can be effectively utilized for various services.

[0003] Wearable electronic devices (e.g., smartwatches, smart bands) can provide healthcare services that continuously monitor a user's biometric data, or data related to exercise, sleep, and / or diet, and manage health. For example, a wearable electronic device can acquire a user's biometric data or motion data through one or more sensors, analyze the acquired data, and store the analysis results in conjunction with an application (e.g., a health application, an exercise application) or provide exercise guidance (or coaching) based on the analysis results.

[0004] The information described above may be provided as related art to aid in understanding the present disclosure. None of the foregoing is to be claimed as prior art related to the present disclosure, nor is it to be used to determine prior art related to the present disclosure.

[0005] A wearable electronic device according to one embodiment of the present disclosure may include at least one processor comprising a processing circuitry, a biosensor, a communication circuit, an output interface, and a memory for storing instructions. The biosensor is intended to sense the blood flow of a user wearing the wearable electronic device and may include at least one light emitter and at least one light receiver. The instructions may be executed individually or collectively by the at least one processor so that, while an application related to strength exercise is executed, the wearable electronic device acquires biodata related to the user's blood flow through the biosensor, identifies changes in the user's grip strength based on changes in blood flow appearing in the biodata due to the strength exercise performed by the user, generates exercise information related to the strength exercise based on the identified changes in grip strength, and provides the exercise information to the user through at least one of the communication circuit or the output interface.

[0006] A method of operating a wearable electronic device according to one embodiment of the present disclosure may include, while an application related to muscle strength exercise is executed, acquiring biometric data related to blood flow of a user wearing the wearable electronic device through a biometric sensor comprising at least one light emitter and at least one light receiver; identifying a change in grip strength of the user based on a change in blood flow appearing in the biometric data due to the muscle strength exercise performed by the user; generating exercise information related to the muscle strength exercise based on the identified change in grip strength; and providing the exercise information.

[0007] A storage medium according to one embodiment of the present disclosure may be a computer-readable, non-transient storage medium. The storage medium may have at least one program recorded thereon for executing a method of operating a wearable electronic device. The storage medium may have at least one program recorded thereon for executing a method comprising, while an application related to strength exercise is executed, acquiring bio-data related to blood flow of a user wearing the wearable electronic device through a bio-sensor comprising at least one light emitter and at least one light receiver, identifying a change in the user's grip strength based on a change in blood flow appearing in the bio-data due to the strength exercise performed by the user, generating exercise information related to the strength exercise based on the identified change in grip strength, and providing the exercise information.

[0008] FIG. 1 is a block diagram of an electronic device in a network environment according to various embodiments.

[0009] FIG. 2 is a block diagram of an electronic device according to one embodiment.

[0010] FIG. 3 is a flowchart illustrating the operation method of an electronic device according to one embodiment.

[0011] FIG. 4a is a front perspective view of a wearable electronic device according to one embodiment.

[0012] FIG. 4b is a rear perspective view of a wearable electronic device according to one embodiment.

[0013] FIG. 5 is a diagram illustrating an example of a process in which an electronic device according to one embodiment provides motion information.

[0014] FIG. 6 is a flowchart illustrating the operation method of an electronic device according to one embodiment.

[0015] FIG. 7a is a graph illustrating examples of non-grip force and grip force sections of sensor data according to one embodiment.

[0016] FIG. 7b is a graph illustrating an example of a non-grip force section of sensor data according to one embodiment.

[0017] FIG. 7c is a graph illustrating an example of a grip strength range of sensor data according to one embodiment.

[0018] FIG. 8 is a graph illustrating an example of a repetitive grip strength activity interval of sensor data according to one embodiment.

[0019] FIG. 9a is a diagram illustrating an example of a graph of sensor data and a user interface when a first muscle strength exercise is performed according to one embodiment.

[0020] FIG. 9b is a diagram illustrating an example of a graph of sensor data and a user interface when a second muscle strength exercise is performed according to one embodiment.

[0021] FIG. 9c is a diagram illustrating an example of a graph of sensor data and a user interface when a third muscle strength exercise is performed according to one embodiment.

[0022] FIG. 10 is a diagram illustrating an environment in which a wearable electronic device and an electronic device operate in conjunction according to one embodiment.

[0023] FIG. 11 is a drawing illustrating an example of a user interface for selecting strength exercises according to one embodiment.

[0024] FIG. 12a is a drawing illustrating an example of a user interface for first motion information according to one embodiment.

[0025] FIG. 12b is a drawing illustrating an example of a user interface for second motion information according to one embodiment.

[0026] FIG. 12c is a drawing illustrating an example of a user interface for third motion information according to one embodiment.

[0027] Hereinafter, embodiments of the present disclosure are described in detail with reference to the drawings so that those skilled in the art can easily practice them. However, the present disclosure may be embodied in various different forms and is not limited to the embodiments described herein. In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components. Furthermore, in the drawings and related descriptions, descriptions of well-known functions and configurations may be omitted for clarity and brevity.

[0028] Users can wear a wearable electronic device on a specific body part, such as the wrist, and perform various strength exercises such as dumbbells, bench press, pull-ups, deadlifts, climbing, and pull-ups. Recently, wearable electronic devices often include motion sensors that measure motion data based on movement and photoplethysmography (PPG) sensors that measure heart rate data, but it may be difficult to provide sufficient guidance using only the motion data or heart rate data.

[0029] In strength training, grip strength is a key factor required for exercise analysis, monitoring, and / or exercise guidance, and can be a representative indicator of physical fitness measurement.

[0030] If grip strength is not taken into account when providing strength training guides, only limited guidance based on movement or heart rate data may be possible. In such cases, it may be difficult to provide comprehensive guidance on strength training or detailed guidance for the individual movements that constitute the exercise. Furthermore, if grip strength is not considered, the effectiveness of the workout or the risk of injury may decrease or increase due to inappropriate guidance regarding the user's posture, given the nature of strength training which involves the repetitive application and release of grip strength. Additionally, failing to account for grip strength when recognizing user gestures during strength training may lead to gesture recognition errors, thereby degrading the user experience.

[0031] An electronic device and its method of operation according to various embodiments of the present disclosure may be intended to increase the accuracy and efficiency of a muscle strength exercise guide by providing a muscle strength exercise guide that incorporates a grip strength element.

[0032] An electronic device and its method of operation according to various embodiments of the present disclosure may be intended to provide an appropriate strength exercise guide tailored to the characteristics of strength exercises in which movements of applying or releasing grip strength are repeatedly performed during exercise.

[0033] An electronic device and its method of operation according to various embodiments of the present disclosure may be intended to prevent injury and enhance exercise effects by reflecting real-time feedback on changes in grip strength in a muscle strength exercise guide.

[0034] An electronic device and its method of operation according to various embodiments of the present disclosure may be intended to prevent gesture recognition errors by performing gesture recognition that reflects a grip strength element while muscle strength exercise is being performed, thereby improving the user experience.

[0035] The technical problems to be solved in this disclosure are not limited to those mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art to which this disclosure pertains.

[0036] FIG. 1 is a block diagram of an electronic device (101) in a network environment (100) according to various embodiments. Referring to FIG. 1, in the network environment (100), the electronic device (101) may communicate with an electronic device (102) through a first network (198) (e.g., a short-range wireless communication network) or with an electronic device (104) or a server (108) through a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) through a server (108). According to one embodiment, the electronic device (101) may include a processor (120), memory (130), input module (150), sound output module (155), display module (160), audio module (170), sensor module (176), interface (177), connection terminal (178), haptic module (179), camera module (180), power management module (188), battery (189), communication module (190), subscriber identification module (196), or antenna module (197). In some embodiments, at least one of these components (e.g., connection terminal (178)) may be omitted from the electronic device (101), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (176), camera module (180), or antenna module (197)) may be integrated into a single component (e.g., display module (160)).

[0037] The processor (120) can control at least one other component (e.g., hardware or software component) of the electronic device (101) connected to the processor (120) by executing software (e.g., program (140)), for example, and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (120) can store commands or data received from other components (e.g., sensor module (176) or communication module (190)) in volatile memory (132), process the commands or data stored in volatile memory (132), and store the resulting data in non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., central processing unit or application processor) or an auxiliary processor (123) that can operate independently or together with it (e.g., graphics processing unit, neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor). For example, if the electronic device (101) includes a main processor (121) and an auxiliary processor (123), the auxiliary processor (123) may be configured to use less power than the main processor (121) or to be specialized for a designated function. The auxiliary processor (123) may be implemented separately from the main processor (121) or as part thereof.

[0038] The auxiliary processor (123) may control at least some of the functions or states associated with at least one component of the electronic device (101) (e.g., display module (160), sensor module (176), or communication module (190)) on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (123) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (180) or communication module (190)). According to one embodiment, the auxiliary processor (123) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (101) itself where the artificial intelligence is performed, or through a separate server (e.g., server (108)). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers.An artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to the hardware structure, the artificial intelligence model may include a software structure, either additionally or substantially.

[0039] The memory (130) can store various data used by at least one component of the electronic device (101) (e.g., processor (120) or sensor module (176)). The data may include, for example, input data or output data for software (e.g., program (140)) and related commands. The memory (130) may include volatile memory (132) or non-volatile memory (134).

[0040] The program (140) may be stored as software in memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0041] The input module (150) can receive commands or data to be used for a component of the electronic device (101) (e.g., processor (120)) from outside the electronic device (101) (e.g., user). The input module (150) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0042] The sound output module (155) can output a sound signal to the outside of the electronic device (101). The sound output module (155) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0043] The display module (160) can visually provide information to an external (e.g., user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0044] The audio module (170) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150) or output sound through the sound output module (155) or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (101).

[0045] The sensor module (176) can detect the operating state of the electronic device (101) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (176) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0046] The interface (177) may support one or more specified protocols that can be used for the electronic device (101) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (102)). According to one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0047] The connection terminal (178) may include a connector through which the electronic device (101) can be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0048] The haptic module (179) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that the user can perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module (179) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0049] The camera module (180) can capture still images and video. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0050] The power management module (188) can manage the power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0051] The battery (189) can supply power to at least one component of the electronic device (101). According to one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0052] The communication module (190) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may include one or more communication processors that operate independently of the processor (120) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (194) (e.g., LAN (local area network) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device (104) through a first network (198) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (199) (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can identify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (196).

[0053] The wireless communication module (192) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. NR access technology can support high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and connection of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low-latency communications (URLLC)). The wireless communication module (192) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (192) can support various technologies for securing performance in the high-frequency band, such as beamforming, massive MIMO (multiple-input and multiple-output), full-dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large-scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), external electronic device (e.g., electronic device (104)), or network system (e.g., second network (199)). According to one embodiment, the wireless communication module (192) can support a Peak data rate (e.g., 20 Gbps or more) for realizing eMBB, loss coverage (e.g., 164 dB or less) for realizing mMTC, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) for realizing URLLC.

[0054] An antenna module (197) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (197) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as a first network (198) or a second network (199), may be selected from the plurality of antennas, for example, by a communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (197).

[0055] According to various embodiments, the antenna module (197) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0056] At least some of the above components can be connected to each other via a communication method between peripheral area devices (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and exchange signals (e.g., commands or data) with each other.

[0057] According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) through a server (108) connected to a second network (199). Each of the external electronic devices (102, or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations performed on the electronic device (101) may be performed on one or more of the external electronic devices (102, 104, or 108). For example, if the electronic device (101) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (101) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (101) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device (104) or the server (108) may be included within a second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0058] FIG. 2 is a block diagram of an electronic device (200) according to one embodiment.

[0059] According to one embodiment, the electronic device (200) may be for providing a muscle strength exercise guide.

[0060] According to one embodiment, the electronic device (200) may be implemented as a wearable electronic device of a type that can be worn (or attached). For example, the electronic device (200) may be a wearable electronic device of a type that can be worn on a specific body part (e.g., wrist) (e.g., a smart watch type) (e.g., a smart watch type wearable electronic device (400) shown in FIG. 4a and FIG. 4b, a smart ring type wearable electronic device (1020) shown in FIG. 10).

[0061] According to one embodiment, the electronic device (200) may be implemented as a portable type of electronic device (e.g., smartphone type) (e.g., the electronic device (1010) of FIG. 10). For example, the electronic device (200) may be an electronic device (e.g., the electronic device (1010) of FIG. 10) connected via short-range wireless communication with a wearable electronic device (e.g., smart watch, smart band, smart ring, smart patch (or electrode)) worn on a part of the user's body (e.g., wrist, ankle).

[0062] Referring to FIG. 2, an electronic device (200) according to one embodiment (e.g., electronic device (101) of FIG. 1) may include a processor (210) (e.g., processor (120) of FIG. 1), a memory (220) (e.g., memory (130) of FIG. 1), a sensor module (230) (e.g., sensor module (176) of FIG. 1), an output interface (240) (e.g., at least one of the acoustic output module (155) of FIG. 1, a display module (160), an audio module (170), or a haptic module (179) of FIG. 1), and a communication module (250).

[0063] According to one embodiment, the electronic device (200) may omit at least one of the components or additionally include other components. A processor (210), memory (220), sensor module (230), output interface (240), and / or communication module (250) included in the electronic device (200) may be electrically and / or operationally connected to each other to exchange signals (e.g., commands or data).

[0064] According to one embodiment, the memory (220) may store instructions. As the instructions stored in the memory (220) are executed, the operation of the processor (210) may be performed. The processor (210) may perform operations or control components of the electronic device (200) by executing the instructions stored in the memory (220) individually or collectively. In the present disclosure, the operation of the electronic device (200) may be understood as being performed when the processor (220) executes the instructions.

[0065] According to one embodiment, the processor (210) may include at least one processor comprising processing circuitry. The processor (210) can execute and / or control various functions supported by the electronic device (200). The processor (210) can control at least some of the memory (220), sensor module (230), output interface (240), and communication module (250). The processor (210) can execute an application and control various hardware by executing instructions stored in the memory (220) of the electronic device (200) and / or code written in a programming language. For example, the processor (210) can execute an application (e.g., a health application, an exercise application) and provide a strength training guide using said application. An application executed on the electronic device (200) may operate independently or operate in conjunction with an external electronic device (e.g., the electronic device (102, 104) of FIG. 1, the server (108)).

[0066] According to one embodiment, the sensor module (230) may include at least one sensor and / or sensor circuitry.

[0067] According to one embodiment, the sensor module (230) may include a biosensor (231). The biosensor (231) may be for sensing the blood flow of a user wearing an electronic device (200) (e.g., a wearable electronic device (400, 1020)). The biosensor (231) may output bio-data related to the user's blood flow.

[0068] According to one embodiment, the biosensor (231) may include at least one light emitter and at least one light receiver.

[0069] According to one embodiment, the biosensor (231) may include a photoplethysmography (PPG) sensor. The biodata from the biosensor (231) may be sensor data (PPG data) output from the PPG sensor.

[0070] According to one embodiment, the PPG sensor can detect a pulse wave using light and output PPG data corresponding to the pulse wave. The PPG sensor can measure (or detect) changes in blood flow by transmitting or reflecting light to the skin in an optical manner. As the blood flow within the blood vessel fluctuates due to the heartbeat, the PPG sensor can output PPG data (or PPG signals, e.g., voltage or digital data) based on the amount of light reflected or absorbed by the fluctuation.

[0071] According to one embodiment, the PPG sensor may include a light-emitting module (or at least one light-emitting part) and a light-receiving module (or at least one light-receiving part). The light-emitting module may output light externally to generate (e.g., acquire) PPG data (or PPG signal). For example, the light-emitting module may include at least one of a VCSEL (vertical cavity surface emitting laser), an LED (light emitting diode), a white LED, and a white laser. For example, the light-emitting module may include various light sources that output light in various wavelength ranges. The light-receiving module may receive light output from the light-emitting module and reflected from an object (e.g., a user). The light-receiving module may convert the received light into an electrical signal. The light-emitting module may generate PPG data (or PPG signal) using the received light. For example, the light receiving module may include at least one of an avalanche photodiode (APD), a single photon avalanche diode (SPAD), a photodiode, a photomultiplier tube (PMT), a charge coupled device (CCD), a CMOS array, and a spectrometer.

[0072] According to one embodiment, the PPG sensor used as a biosensor (231) may further include a sensor integrated circuit. The sensor integrated circuit may perform at least some of the functions of the processor (210) or be coupled with the processor (210). For example, the sensor integrated circuit may be implemented as a single chip with the light-emitting module and / or the light-receiving module. For example, the sensor integrated circuit may be implemented separately from the light-emitting module and the light-receiving module and be coupled with the light-emitting module and the light-receiving module.

[0073] However, the type of biosensor (231) is not limited to a PPG sensor. For example, the biosensor (231) may be another type of sensor capable of acquiring bio-data related to blood flow (e.g., blood flow volume, blood flow status, heart rate, heart rate variability, blood pressure, electrocardiogram, oxygen concentration in blood, oxygen saturation, and other cardiovascular data). For example, the biosensor (231) may include at least one of a near-infrared spectroscopy (NIRS) sensor, an electrocardiography (ECG) sensor, a galvanic skin response (GSR) sensor, a bioelectrical impedance analysis (BIA) sensor, or a biomarker sensor that detects specific substances or components within the body.

[0074] According to one embodiment, the sensor module (230) may further include a motion sensor (232). The motion sensor (232) may output motion data according to the user's movement. For example, the motion sensor (232) may include at least one of an accelerometer, a gyroscope, a barometer (or altitude sensor), a gesture sensor, or a grip sensor.

[0075] According to one embodiment, the output interface (240) may include a display module (160). The display module (160) may provide visual information to an external (e.g., user) of the electronic device (200). According to one embodiment, the display module (160) may be a touchscreen display and may include a touch circuitry configured to detect a touch, and / or a sensor circuitry configured to measure the intensity of a force generated by the touch (e.g., a pressure sensor).

[0076] According to one embodiment, the communication module (250) may include communication circuitry.

[0077] According to one embodiment, the communication module (250) may include a wireless communication module (e.g., the wireless communication module (192) of FIG. 1 (e.g., a cellular communication module, a short-range wireless communication module, or a GNSS (global navigation satellite system) communication module).

[0078] According to one embodiment, the communication module (250) can support a short-range wireless communication connection of an electronic device (200) (e.g., a wearable electronic device worn by a user). For example, the communication module (250) can support a short-range wireless communication (e.g., Bluetooth, Bluetooth LE (low energy), WiFi (wireless fidelity) direct, or IrDA (infrared data association)) connection between the electronic device (200) and an external electronic device (e.g., a smartphone carried by a user while exercising or located near the user).

[0079] According to one embodiment, the communication module (250) can support a long-distance wireless communication connection of the electronic device (200). For example, the communication module (250) can support a GNSS communication connection between a satellite and the electronic device (200) for positioning of the electronic device (200), and receive positioning data indicating the current location of the electronic device (200) from the satellite. The communication module (250) can receive the positioning data of the electronic device (200) via long-distance wireless communication and transmit it to the processor (210) or store it in memory (220). For example, the communication module (250) can support a long-distance wireless communication (e.g., cellular communication, or the Internet) connection between an external server (e.g., server (108) of FIG. 1) and the electronic device (200), and provide exercise information related to strength training to the external server. For example, the exercise information can be stored in conjunction with a user account managed by the external server.

[0080] According to one embodiment, the processor (210) can acquire (e.g., detect, measure, or receive) bio-data (or bio-signals) related to the user's blood flow through a bio-sensor (231).

[0081] According to one embodiment, the processor (210) can acquire biometric data while an application related to strength training (e.g., a health application, an exercise application) is running. In one embodiment, the processor (210) of the electronic device (200) (e.g., a wearable electronic device (400) worn by a user, a smart watch) can acquire biometric data (or biometric signals) through an internal biometric sensor (231) while an application related to strength training is running on the electronic device (200). In one embodiment, the processor (210) of the electronic device (200) (e.g., a wearable electronic device (400, 1020) worn by a user, a smart watch, a smart ring) can acquire biometric data (or biometric signals) through an internal biometric sensor (231) while an application related to strength training is running on an external electronic device (e.g., the electronic device (1010) of FIG. 10) (e.g., a user's smartphone) connected via short-range wireless communication.

[0082] According to one embodiment, the processor (210) may activate the biosensor (231) to acquire biometric data or adjust the measurement cycle (or measurement frequency) of the biosensor (231). For example, the processor (210) of an electronic device (200) (e.g., a smart watch, a smart ring worn by a user) may activate the biosensor (231) to acquire biometric data or adjust the measurement cycle of the biosensor (231) from a first cycle to a second cycle shorter than the first cycle when an application related to strength training is executed on the electronic device (200) or an external electronic device (e.g., the electronic device (1010) of FIG. 10, a user's smartphone) connected to the electronic device (200) via short-range wireless communication.

[0083] According to one embodiment, the processor (210) can identify changes in the user's grip strength based on biometric data from the biosensor (231). The processor (210) can identify changes in the user's grip strength based on changes in blood flow indicated in the biometric data by strength exercises performed by the user. Changes in the user's grip strength may be related to changes in blood flow caused by strength exercises performed by the user. The user's blood flow (e.g., volume, direction, pattern, fluctuations in blood flow) changes due to strength exercises performed by the user, and changes in grip strength can be identified based on changes in blood flow. The processor (210) can identify changes in grip strength based on biometric data indicating changes in blood flow caused by strength exercises when the user performs strength exercises.

[0084] According to one embodiment, the processor (210) can detect an event (or triggering event) indicating the start of strength exercise. In one embodiment, the processor (210) can detect an event indicating the start of strength exercise based on at least one of user input, biometric data from a biometric sensor (231), or motion data from a motion sensor (232). In response to the event indicating the start of strength exercise, the processor (210) can start monitoring grip strength information indicating a change in grip strength.

[0085] According to one embodiment, the processor (210) may receive user input selecting a strength exercise through the execution screen of an application related to strength exercise (e.g., a touch on the strength exercise icon (1120) of FIG. 11). Based on the reception of said user input, the processor (210) may detect an event indicating the start of a strength exercise. In response to said event, the processor (210) may begin monitoring grip strength information indicating a change in grip strength.

[0086] According to one embodiment, the processor (210) can detect an event indicating the start of strength exercise based on the change in the amount of bio-data (or bio-signal) obtained from the bio-sensor (231) exceeding a specified threshold range (e.g., a range between a lower threshold and an upper threshold). In response to said event, the processor (210) can start monitoring grip strength information indicating a change in grip strength.

[0087] According to one embodiment, the processor (210) can acquire motion data (or motion signal) of a user through a motion sensor (232). The processor (210) can detect an event indicating the start of strength exercise based on the detection of the user's body movement (e.g., movement corresponding to a designated body posture for strength exercise, arm movement, movement repeated more than a certain number of times) from the motion data. In response to the event, the processor (210) can start monitoring of grip strength information indicating a change in grip strength.

[0088] According to one embodiment, the processor (210) can acquire motion data of a user through a motion sensor (232). Based on the detection of the user's static state (or static posture, e.g., a state without positional movement) and the user's wrist movement (e.g., local / partial movement) from the motion data, the processor (210) can detect an event indicating the start of a strength exercise. In response to the event, the processor (210) can start monitoring grip strength information indicating a change in grip strength.

[0089] According to one embodiment, the processor (210) can monitor grip strength information based on biometric data from the biosensor (231). The grip strength information may indicate changes in grip strength caused by muscular exercise performed by the user. For example, the grip strength information may include information on at least one of whether grip strength is measured, the start time of the grip strength activity, the degree of grip strength, the end time of the grip strength activity, the duration of the grip strength activity, the number of grip strength activities, the pattern of the grip strength activity, or the interval between grip strength activities.

[0090] According to one embodiment, the processor (210) can identify a first time interval (non-grip force interval) in which no grip force is applied and a second time interval (grip force interval) in which a grip force is applied, based on biometric data from the biometric sensor (231). The processor (210) can filter out the first biometric data (e.g., PPG data of a first pattern, normal heart rate data) during the first time interval. The processor (210) can monitor the grip force information (e.g., whether grip force is measured, the start time of the grip force activity, the degree of grip force, the end time of the grip force activity, the duration of the grip force activity, the number of grip force activities, the pattern of the grip force activity, the interval between grip force activities) based on the second biometric data (e.g., PPG data of a second pattern, abnormal heart rate data, grip force data) during the second time interval.

[0091] According to one embodiment, the type of information to be monitored may vary depending on whether strength training is performed or whether grip force is applied. For example, the processor (210) may monitor different types of information using a single biosensor (231) depending on whether strength training is performed or whether grip force is applied. During a first time interval when no grip force is applied, the processor (210) may monitor heart rate information (e.g., heart rate, heart rate variability, oxygen saturation) based on first biodata obtained through the biosensor (231). During a second time interval when grip force is applied, the processor (210) may monitor grip force information indicating changes in grip force based on second biodata obtained through the biosensor (231).

[0092] According to one embodiment, the processor (210) may determine that a grip strength activity (an activity in which grip strength is applied or an activity in which grip strength is generated) has started when the amount of change in bio-data (or bio-signal) obtained from the bio-sensor (231) exceeds a specified first threshold (e.g., when the slope of the bio-data changes by more than a specified level in the positive direction). The grip strength activity may be a component of a muscle strength exercise. The processor (210) may determine that the grip strength activity has ended when, after the grip strength activity has started, the amount of change in bio-data (or bio-signal) obtained from the bio-sensor (231) exceeds a specified second threshold (e.g., when the slope of the bio-data changes by more than a specified level in the negative direction). The processor (210) may obtain individual grip strength information from the bio-data during the interval corresponding to the grip strength activity. By collecting individual grip strength information over a plurality of time intervals, the processor (210) may monitor grip strength information indicating changes in grip strength caused by muscle strength exercise performed by the user.

[0093] According to one embodiment, the processor (210) may generate exercise information related to strength exercises based on a change in grip strength identified from biometric data (or grip strength information indicating said change in grip strength). For example, said exercise information may be intended to guide strength exercises.

[0094] According to one embodiment, exercise information related to strength training may include information regarding risk. A processor (210) may determine the risk related to the load applied to the wrist by strength training based on changes in grip strength identified from biometric data (or grip strength information indicating said changes in grip strength). The processor (210) may provide (e.g., display, output) an indicator of said risk (e.g., risk notification message, warning sound according to risk, vibration pattern corresponding to risk) as exercise information related to strength training through an output interface (240).

[0095] According to one embodiment, exercise information related to strength training may be intended to guide the strength training. For example, the exercise information may include at least some of guide information regarding real-time grip strength measurement results, guide information regarding strength training analysis results, and guide information regarding risk analysis results.

[0096] According to one embodiment, the processor (210) may provide exercise information related to strength exercises performed by the user to the user. In one embodiment, the processor (210) may provide the exercise information to the user through at least one of a communication module (250) or an output interface (240). For example, the processor (210) of an electronic device (200) (e.g., a wearable electronic device (400), a smart watch worn by the user) may output a user interface for the exercise information through the output interface (240). For example, the processor (210) of an electronic device (200) (e.g., a wearable electronic device (400, 1020), a smart watch worn by the user, a smart ring) may transmit at least a portion of the exercise information to an external electronic device (e.g., the electronic device (1010) of FIG. 10, a user's smartphone) through the communication module (250), thereby causing a user interface for the exercise information to be output on the external electronic device.

[0097] According to one embodiment, a user interface for exercise information related to strength training (e.g., a user interface that guides strength training) may be implemented as a visual type (e.g., screen, text), an auditory type (e.g., audio, sound), a tactile type (e.g., vibration), or a hybrid type combining at least some of these.

[0098] According to one embodiment, the processor (210) of the electronic device (200) may provide exercise information related to strength training through an output interface (240), for example, at least one of the display module (160), audio module (170), sound output module (155), and haptic module (179) of FIG. 1. For example, the exercise information may be for guiding strength training.

[0099] In one embodiment, the processor (210) can output a user interface for the exercise information through an output interface (240). For example, the processor (210) can output a visual type, auditory type, tactile type, or hybrid type user interface to the user through the output interface (240).

[0100] According to one embodiment, an electronic device (200) (e.g., a wearable electronic device worn by a user, the electronic device (101) of FIG. 1, the wearable electronic device (400) of FIG. 10)) may provide exercise information related to strength training (e.g., a user interface guiding strength training) by linking with an external electronic device (e.g., a user's smartphone, the electronic device (101, 104) of FIG. 1, the electronic device (1010) of FIG. 10). For example, a processor (210) of the electronic device (200) (e.g., a wearable electronic device (400, 1020) worn by a user) may transmit information regarding a user interface guiding strength training to an external electronic device (e.g., the electronic device (1010) of FIG. 10, the user's smartphone) through a communication module (250), thereby enabling at least a part of the user interface (e.g., a screen, text, voice, vibration) to be output through the external electronic device. The above external electronic device may be connected to the electronic device (200) via short-range wireless communication through a communication module (250).

[0101] FIG. 3 is a flowchart illustrating the operation method of an electronic device (200) according to one embodiment.

[0102] According to one embodiment, the method of FIG. 3 may be for providing a strength exercise guide. The movements illustrated in FIG. 3 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of the movements may be changed, and at least two movements may be performed in parallel. In some embodiments, some of the illustrated movements may be omitted, some movements may be integrated, some movements may be changed, or other movements may be added.

[0103] According to one embodiment, the electronic device (200) may be a wearable electronic device (e.g., a smart watch type wearable electronic device (400) shown in FIG. 4a and 4b, a smart ring type wearable electronic device (1020) shown in FIG. 10).

[0104] Referring to FIG. 3, the operation method of an electronic device (200) according to one embodiment may include operation 310, operation 320, operation 330 and operation 340.

[0105] According to one embodiment, in operation 310, an electronic device (200) (e.g., a wearable electronic device (400)) can acquire (e.g., detect, measure, or receive) biometric data (or biometric signals) related to the user's blood flow through a biometric sensor (231).

[0106] According to one embodiment, the biosensor (231) may include at least one light emitter and at least one light receiver. For example, the biosensor (231) may include a PPG sensor. The biodata from the biosensor (231) may be sensor data output from the PPG sensor. However, it is not limited thereto. For example, the biosensor (231) may be another type of sensor capable of acquiring biodata related to blood flow (e.g., blood flow volume, blood flow status, heart rate, heart rate variability, blood pressure, electrocardiogram, oxygen concentration in blood, oxygen saturation, and other cardiovascular data). For example, the biosensor (231) may include at least one of an NIRS sensor, an ECG sensor, a GSR sensor, a BIA sensor, or a biomarker sensor.

[0107] According to one embodiment, an electronic device (200) (e.g., a wearable electronic device (400)) can acquire biometric data while an application related to strength training (e.g., a health application, an exercise application) is running. For example, a wearable electronic device (400) worn by a user can acquire biometric data (or biometric signals) through an internal biometric sensor (231) while an application related to strength training is running on the wearable electronic device (400). For example, a wearable electronic device (400, 1020) worn by a user can acquire biometric data (or biometric signals) through an internal biometric sensor (231) while an application related to strength training is running on an external electronic device (e.g., the electronic device (1010) of FIG. 10) connected via short-range wireless communication.

[0108] According to one embodiment, the electronic device (200) may activate the biosensor (231) to acquire biometric data or adjust the measurement cycle (or measurement frequency) of the biosensor (231). For example, when an application related to strength exercise is executed on the electronic device (200) or an external electronic device (e.g., the electronic device (1010) of FIG. 10) connected to the electronic device (200) via short-range wireless communication, the electronic device (200) may activate the biosensor (231) to acquire biometric data or adjust the measurement cycle of the biosensor (231) from a first cycle to a second cycle shorter than the first cycle.

[0109] According to one embodiment, in operation 320, an electronic device (200) (e.g., a wearable electronic device (400)) can identify changes in the user's grip strength based on biometric data obtained through operation 310. The electronic device (200) can identify changes in the user's grip strength based on changes in blood flow appearing in the biometric data due to strength exercises performed by the user. Changes in the user's grip strength may be related to changes in blood flow caused by strength exercises performed by the user. The user's blood flow (e.g., volume, direction, pattern, fluctuations in blood flow) changes due to strength exercises performed by the user, and changes in grip strength can be identified based on changes in blood flow. The electronic device (200) can identify changes in grip strength based on biometric data indicating changes in blood flow caused by strength exercises when the user performs strength exercises.

[0110] According to one embodiment, an action (action 320) for identifying a change in a user's grip strength may include an action for monitoring grip strength information indicating the change in grip strength.

[0111] According to one embodiment, the electronic device (200) can detect an event (or triggering event) indicating the start of a strength exercise. In one embodiment, the electronic device (200) can detect an event indicating the start of a strength exercise based on at least one of user input, biometric data from a biometric sensor (231), or motion data from a motion sensor (232). In response to the event indicating the start of a strength exercise, the electronic device (200) can start monitoring grip strength information indicating a change in grip strength.

[0112] According to one embodiment, an electronic device (200) may receive user input selecting a strength exercise through an execution screen of an application related to strength exercise (e.g., a touch on the strength exercise icon (1120) of FIG. 11). Based on the reception of said user input, the electronic device (200) may detect an event indicating the start of a strength exercise. In response to said event, the electronic device (200) may begin monitoring grip strength information indicating a change in grip strength.

[0113] According to one embodiment, the electronic device (200) can detect an event indicating the start of muscle strength exercise based on the change in the amount of bio-data (or bio-signal) obtained from the bio-sensor (231) exceeding a specified threshold range (e.g., a range between a lower threshold and an upper threshold). In response to said event, the electronic device (200) can start monitoring grip strength information indicating a change in grip strength.

[0114] According to one embodiment, the electronic device (200) can acquire motion data (or motion signal) of a user through a motion sensor (232). The electronic device (200) can detect an event indicating the start of strength exercise based on the detection of the user's body movement (e.g., movement corresponding to a designated body posture for strength exercise, arm movement, movement repeated more than a certain number of times) from the motion data. In response to the event, the electronic device (200) can start monitoring grip strength information indicating a change in grip strength.

[0115] According to one embodiment, an electronic device (200) can acquire motion data of a user through a motion sensor (232). The electronic device (200) can detect an event indicating the start of a strength exercise based on the detection of the user's static state (or static posture, e.g., a state without positional movement) and the user's wrist movement (e.g., local / partial movement) from the motion data. In response to the event, the electronic device (200) can start monitoring grip strength information indicating a change in grip strength. For example, the electronic device (200) can identify that the user is in a static state based on motion data from the motion sensor (232) and / or positioning data indicating the current position of the electronic device (200). For example, the user's static state may be a state where the user has no positional movement or the user's overall body movement is below a specified level. For example, the static state of the user may be a state in which the user does not move for a certain period of time after assuming a designated body posture (e.g., standing in a certain position, sitting, lying down, basic posture for strength training). For example, the static state of the user may be a state in which the user moves only restrictively within a certain range of motion while not moving (e.g., moving only the hands, wrists, or arms within a certain range of motion while maintaining a designated body posture).

[0116] According to one embodiment, in operation 320, the electronic device (200) can monitor grip strength information indicating changes in grip strength based on biometric data obtained through operation 310. The grip strength information may indicate changes in grip strength caused by muscle strength exercises performed by a user. For example, the grip strength information may include information on at least one of whether grip strength is measured, the start time of the grip strength activity, the degree of grip strength, the end time of the grip strength activity, the duration of the grip strength activity, the number of grip strength activities, the pattern of the grip strength activity, or the interval between grip strength activities.

[0117] According to one embodiment, the operation of monitoring grip strength information indicating a change in grip strength may include at least some of the operations of FIG. 6 (operation 625, operation 630, operation 635, operation 640, operation 645, operation 650, operation 655, operation 660).

[0118] According to one embodiment, the electronic device (200) can identify a first time interval (non-grip force interval) in which no grip force is applied and a second time interval (grip force interval) in which a grip force is applied, based on biometric data from a biometric sensor (231). The electronic device (200) can filter out the first biometric data (e.g., PPG data of a first pattern, normal heart rate data) during the first time interval. The electronic device (200) can monitor grip force information (e.g., whether grip force is measured, the start time of the grip force activity, the degree of grip force, the end time of the grip force activity, the duration of the grip force activity, the number of grip force activities, the pattern of the grip force activity, the interval between grip force activities) based on the second biometric data (e.g., PPG data of a second pattern, abnormal heart rate data, grip force data) during the second time interval.

[0119] According to one embodiment, the type of information to be monitored may vary depending on whether strength training is performed or whether grip force is applied. For example, an electronic device (200) may monitor different types of information using a single biosensor (231) depending on whether strength training is performed or whether grip force is applied. During a first time interval when no grip force is applied, the electronic device (200) may monitor heart rate information (e.g., heart rate, heart rate variability, oxygen saturation) based on first biodata obtained through the biosensor (231). During a second time interval when grip force is applied, the electronic device (200) may monitor grip force information indicating changes in grip force based on second biodata obtained through the biosensor (231).

[0120] According to one embodiment, the electronic device (200) may determine that a grip strength activity (an activity in which grip strength is applied or an activity in which grip strength is generated) has started when the amount of change in bio-data (or bio-signal) obtained from the bio-sensor (231) exceeds a specified first threshold (e.g., when the slope of the bio-data changes by more than a specified level in the positive direction). The grip strength activity may be a component of a muscle strength exercise. The electronic device (200) may determine that the grip strength activity has ended when, after the grip strength activity has started, the amount of change in bio-data (or bio-signal) obtained from the bio-sensor (231) exceeds a specified second threshold (e.g., when the slope of the bio-data changes by more than a specified level in the negative direction). The electronic device (200) may obtain individual grip strength information from the bio-data during the interval corresponding to the grip strength activity. By collecting individual grip strength information over a plurality of time intervals, the electronic device (200) may monitor grip strength information indicating changes in grip strength caused by muscle strength exercise performed by the user.

[0121] According to one embodiment, in operation 330, an electronic device (200) (e.g., a wearable electronic device (400)) may generate exercise information related to strength exercises (e.g., 520 of FIG. 5) based on a change in grip strength identified through operation 320 (or grip strength information indicating said change in grip strength). For example, said exercise information may be intended to guide strength exercises.

[0122] According to one embodiment, in operation 340, an electronic device (200) (e.g., a wearable electronic device (400)) may provide exercise information (e.g., 520 in FIG. 5) generated through operation 330 to a user. In one embodiment, the electronic device (200) may provide the exercise information to a user through at least one of a communication module (250) or an output interface (240). For example, the electronic device (200) (e.g., a wearable electronic device (400), a smart watch worn by a user) may output a user interface for the exercise information through the output interface (240). For example, an electronic device (200) (e.g., wearable electronic device (400, 1020), smart watch worn by a user, smart ring) can transmit at least a portion of the exercise information to an external electronic device (e.g., electronic device (1010) of FIG. 10, user's smartphone) through a communication module (250), thereby enabling a user interface for the exercise information to be output on the external electronic device.

[0123] According to one embodiment, exercise information related to strength training may include information regarding risk. The electronic device (200) may determine the risk related to the load applied to the wrist by strength training based on a change in grip strength identified through motion 320 (or grip strength information indicating said change in grip strength). The electronic device (200) may provide (e.g., display, output) an indicator of said risk (e.g., risk notification message, warning sound according to risk, vibration pattern corresponding to risk) as exercise information related to strength training through an output interface (240).

[0124] According to one embodiment, exercise information related to strength training may be intended to guide the strength training. For example, the exercise information may include at least some of guide information for real-time grip strength measurement results (e.g., 521 in FIG. 5), guide information for strength training analysis results (e.g., 522 in FIG. 5), and guide information for risk analysis results (e.g., 523 in FIG. 5).

[0125] According to one embodiment, an electronic device (200) (e.g., a wearable electronic device (400)) may provide guidance information (start time of grip strength activity, end time of grip strength activity) for real-time grip strength measurement results. The electronic device (200) may detect grip strength through a biosensor (231) (e.g., a PPG sensor). For example, the electronic device (200) may determine that grip strength has occurred if the slope of the PPG data (output data of the PPG sensor) over a recent specified time period changes above a specified level (or exceeds a threshold). For example, the electronic device (200) may estimate that it is in a normal state (or non-grip strength state) where no grip strength is applied, if the slope of the graph representing the PPG data over the last 10 seconds (e.g., the graph (700) in FIG. 7a) is close to horizontal and is below a first threshold (e.g., absolute value 1) (e.g., the non-grip strength section (710) in FIG. 7a). The electronic device (200) can estimate that a state in which grip strength is applied (or grip strength state) is present when the slope of a graph representing PPG data over the past 2 seconds is close to vertical and greater than a second threshold value (e.g., absolute value 10). The electronic device (200) can identify a point in time as the start point of grip strength activity when the slope of the PPG data increases significantly in the positive (+) direction compared to the normal state. The electronic device (200) can identify a point in time as the end point of grip strength activity when the slope of the PPG data decreases significantly in the negative (-) direction. In this way, the electronic device (200) can analyze the PPG data during the interval estimated as the grip strength state to monitor real-time grip strength measurement results and / or grip strength information based on the real-time grip strength measurement results. The electronic device (200) can provide guide information regarding the real-time grip strength measurement results as exercise information related to muscle strength exercises.

[0126] According to one embodiment, an electronic device (200) (e.g., a wearable electronic device (400)) can provide guidance information regarding the results of strength exercise analysis (e.g., number of activity / strength exercises, duration of activity / strength exercises) as exercise information related to strength exercises through grip strength detection.

[0127] For example, while it is possible to track hand movements using a motion sensor (232), it may be difficult to analyze strength exercises without hand movement or to measure the number of activities constituting the strength exercises. For example, in strength exercises such as pull-ups, the activity (or motion) of lifting the body by applying force to the hand or lowering the body by releasing force from the hand may be repeated while the hand (or wrist) is fixed in a certain position or there is no movement of the hand (or wrist). The electronic device (200) can detect (or measure) grip strength using a bio-sensor (231) (e.g., PPG sensor), and through the detected grip strength, can identify a first point in time when force is actually applied to the hand and a second point in time when force is released from the hand during the strength exercise. Generally, in the case of strength exercises, once started, activities (or motions) of continuously applying or releasing grip strength may be repeated until finished. The electronic device (200) can measure the number of times the activity / strength exercise is performed through grip strength detection using the bio-sensor (231) (e.g., PPG sensor). For example, the electronic device (200) can estimate the number of activity / strength exercises through changes in grip strength, even for strength exercises that do not involve wrist movement, such as pull-ups. In this way, the electronic device (200) can provide guide information regarding the results of the strength exercise analysis, including the number of activity / strength exercises, as exercise information related to strength exercises.

[0128] For example, the electronic device (200) can provide guidance by focusing on a single activity rather than an activity set for multiple activities. The electronic device (200) can detect (or measure) grip strength using a biosensor (231) (e.g., a PPG sensor), and through the detected grip strength, can identify a first point in time when the hand actually starts to apply force during strength training and a second point in time when the hand releases force. The electronic device (200) can measure the duration of the single activity (the time from the first point in time to the second point in time) through the detected grip strength. For example, the electronic device (200) can use the measured duration to provide guidance information on the duration of the activity that can elicit maximum muscle activity. The appropriate duration of the activity may vary depending on the type of strength training (or exercise type). For example, in the case of pull-ups, an exercise method of going down over about 4 seconds and coming back up over 4 seconds may be effective. For example, in the case of push-ups, an exercise method of performing 3 low-intensity push-ups after 2 high-intensity push-ups may be effective. The electronic device (200) can provide improved activity unit guidance information compared to activity set unit guidance information (e.g., 'A rest time of [number] minutes is recommended' or 'Complete the set within [number] minutes') during the performance of pull-ups or push-ups through grip strength detection. For example, since the electronic device (200) can identify the actual start time of one activity, it can provide activity unit guidance information (e.g., 'Maintain the current position for 4 seconds' or '2 high-intensity push-ups and 3 low-intensity push-ups have been performed. After a 5-second rest, repeat the same activities') that indicates the exact time when the muscles should contract or relax.In this way, the electronic device (200) can provide guide information on the results of strength exercise analysis focused on a single activity as exercise information related to strength exercise. Accordingly, a more sophisticated strength exercise guide of improved quality can be provided to the user.

[0129] According to one embodiment, an electronic device (200) (e.g., a wearable electronic device (400)) can provide guidance information regarding the risk analysis results (risk level of strength exercise, time to stop exercise, suggestion for adjusting exercise difficulty) as exercise information related to strength exercise through grip strength detection. For example, the electronic device (200) can provide guidance information regarding the time to stop exercise or the adjustment of exercise difficulty through changes in grip strength (or grip strength pattern) detected by a biosensor (231).

[0130] According to one embodiment, the electronic device (200) can perform grip strength analysis (or monitoring of grip strength information) using a biosensor (231) in addition to motion recognition using a motion sensor (232). If only the motion sensor (232) is used, the muscle strength exercise may be terminated only when the condition of repeating activities a predetermined number of times is satisfied. For example, if a user of the wearable electronic device (400) raises their hand to touch the screen of the wearable electronic device (400) to stop exercising, the gesture of raising the hand may also be recognized (e.g., counted) as an activity count, and accurate motion recognition (e.g., counting the number of activities) may be difficult. For example, the types of gestures may include a first gesture that generates grip force (e.g., a gesture of clenching and unclenching the hand, a clench gesture, a gesture that shows shaking and / or a change in angle of the wrist, a gesture of rotating or bending the wrist beyond a certain angle) and a second gesture that does not generate grip force (e.g., moving the hand without grip force, a simple pinch gesture, a simple finger gesture). By performing a grip force analysis, the electronic device (200) can more accurately recognize the user's gesture, regardless of type, and the grip force activity or muscle exercise associated with said gesture.

[0131] According to one embodiment, the electronic device (200) can recognize both a first gesture related to strength exercise (e.g., a first gesture that generates grip strength) and a second gesture unrelated to strength exercise (e.g., a second gesture that does not generate grip strength). By the electronic device (200) recognizing both the first gesture and the second gesture, it may be possible to measure the number of activity / strength exercises more precisely.

[0132] According to one embodiment, the electronic device (200) can detect excessive weight or abnormal patterns (e.g., abnormal patterns in PPG data, abnormal movements of the wrist) during strength training through grip strength analysis. For example, there may be cases where the grip strength is suddenly released or the wrist is bent excessively, causing the value of sensor data (e.g., PPG data) not to be measured temporarily. In such cases, the electronic device (200) can provide feedback on the risk level of the strength training currently being performed by the user and provide guidance information suggesting that the set of activities be stopped immediately. In this way, the electronic device (200) can provide guidance information regarding the risk analysis results, including feedback on the risk level and / or the timing of stopping the exercise, as exercise information related to strength training. Accordingly, a safer and more positive exercise experience can be provided to the user.

[0133] According to one embodiment, an electronic device (200) can detect a gesture corresponding to a user's wrist movement through a motion sensor (232). The user's wrist movement may include not only the user's wrist but also the movement of at least one body part corresponding to a hand, fingers, or arm connected to the wrist. When the electronic device (200) detects a gesture corresponding to a user's wrist movement through the motion sensor (232), it may perform or skip monitoring of grip strength information depending on whether grip strength is measured from biometric data. The electronic device (200) may determine whether grip strength is measured based on biometric data from a biometric sensor (231). If the grip strength is measured, the electronic device (200) may determine the detected gesture as a first gesture related to muscle strength exercise. If the grip strength is not measured, the electronic device (200) may determine the detected gesture as a second gesture unrelated to muscle strength exercise.

[0134] According to one embodiment, if the electronic device (200) determines that a gesture detected from motion data is a first gesture related to muscle strength exercise, it may perform (or initiate) monitoring of grip strength information based on bio-data from a bio-sensor (231). If the electronic device (200) determines that a gesture detected from motion data is a second gesture unrelated to muscle strength exercise, it may skip (or omit) monitoring of grip strength information based on bio-data.

[0135] According to one embodiment, when the electronic device (200) detects a gesture corresponding to the user's wrist movement through a motion sensor (232), it may perform different functions depending on whether grip strength is measured from biometric data. If the electronic device (200) determines that the gesture detected from the motion data is a first gesture (or a first type of gesture) related to muscle strength exercise, it may perform a first function corresponding to the first gesture. If the electronic device (200) determines that the gesture detected from the motion data is a second gesture (e.g., a second type of gesture) unrelated to muscle strength exercise, it may perform a second function corresponding to the second gesture. For example, the first function may be a function of a first application (e.g., foreground application, health application, exercise application) (e.g., UI display of the first application, counting of grip strength activity repetitions). For example, the second function may be a function of a second application different from the first application (e.g., background application, home application) (e.g., displaying the UI of the second application, displaying the home screen, increasing screen brightness).

[0136] FIG. 4a is a front perspective view of a wearable electronic device (400) according to one embodiment. FIG. 4b is a rear perspective view of a wearable electronic device (400) according to one embodiment.

[0137] An electronic device (200) according to one embodiment may be a wearable electronic device (400) (e.g., a smart watch) worn on the wrist of a user.

[0138] According to one embodiment, the wearable electronic device (400) can perform grip strength detection and / or monitoring of grip strength information (or grip strength analysis) through a biosensor (e.g., biosensor (231) of FIG. 2) within the sensor module (411). The wearable electronic device (400) can provide (or output) exercise information related to muscle strength exercises. The wearable electronic device (400) can provide (or output) a user interface that displays guide information based on the results of grip strength detection and / or monitoring of grip strength information. The wearable electronic device (400) can detect gestures based on wrist movements of a user wearing the wearable electronic device (400) through a biosensor (e.g., biosensor (231) of FIG. 2) and / or a motion sensor (e.g., motion sensor (232) of FIG. 2) within the sensor module (411).

[0139] Referring to FIG. 4a and FIG. 4b, a wearable electronic device (400) according to one embodiment may include a housing (410) comprising a first surface (or front) (410A), a second surface (or rear) (410B), and a side (410C) surrounding the space between the first surface (410A) and the second surface (410B), and a fastening member (450, 460) connected to at least a part of the housing (410) and configured to detachably fasten the wearable electronic device (400) to a part of a user's body (e.g., wrist, ankle, etc.). In another embodiment (not shown), the housing may refer to a structure forming some of the first surface (410A), the second surface (410B), and the side (410C) of FIG. 4a. According to one embodiment, the first surface (410A) may be formed by a front plate (401) in which at least a portion is substantially transparent (e.g., a glass plate containing various coating layers, or a polymer plate). The second surface (410B) may be formed by a rear plate (407) in which it is substantially opaque. The rear plate (407) may be formed by, for example, coated or colored glass, ceramic, polymer, metal (e.g., aluminum, stainless steel (STS), or magnesium), or a combination of at least two of the above materials. The side surface (410C) may be formed by a side bezel structure (or side member) (406) comprising metal and / or polymer, which is combined with the front plate (401) and the rear plate (407). In some embodiments, the rear plate (407) and the side bezel structure (406) may be formed integrally and may comprise the same material (e.g., a metallic material such as aluminum). The above-mentioned connecting members (450, 460) can be formed in various materials and shapes. They can be formed such that an integral and a plurality of unit links are movable with each other by means of woven fabric, leather, rubber, urethane, metal, ceramic, or a combination of at least two of the above materials.

[0140] According to one embodiment, the wearable electronic device (400) may include at least one of a display (420) (e.g., the display module (160) of FIG. 1, the output interface (240) of FIG. 2), an audio module (405, 408) (e.g., the acoustic output module (155) of FIG. 1, the audio module (170) of FIG. 1, the output interface (240) of FIG. 2), a sensor module (411) (e.g., the sensor module (170) of FIG. 1, the sensor module (230) of FIG. 2), and a key input device (402, 403, 404) (e.g., the input module (150) of FIG. 1). In some embodiments, the wearable electronic device (400) may omit at least one of the components (e.g., the key input device (402, 403, 404)) or additionally include another component (e.g., one of the components of FIG. 1 or FIG. 2).

[0141] The display (420) may be exposed, for example, through a significant portion of the front plate (401). The shape of the display (420) may correspond to the shape of the front plate (401) and may be various shapes such as circular, elliptical, or polygonal. The display (420) may be combined with or placed adjacent to a touch detection circuit, a pressure sensor capable of measuring the intensity (pressure) of the touch, and / or a fingerprint sensor.

[0142] The audio module (405, 408) may include a microphone hole (405) and a speaker hole (408). A microphone for acquiring external sound may be placed inside the microphone hole (405), and in some embodiments, a plurality of microphones may be placed to detect the direction of sound. The speaker hole (408) may be used as an external speaker and a receiver for calls. In some embodiments, the speaker hole (408) and the microphone hole (405) may be implemented as a single hole, or a speaker may be included without the speaker hole (408) (e.g., a piezo speaker).

[0143] The sensor module (411) can detect (or output) electrical signals or data corresponding to the internal operating state and / or external environmental state of the wearable electronic device (400). The sensor module (411) may include, for example, a biosensor disposed on the second surface (410B) of the housing (410) and / or a motion sensor disposed inside the housing (410). The sensor module (411) can detect (or output) motion data corresponding to the movement of the wearable electronic device (400) and / or biometric data of a user wearing the wearable electronic device (400) (e.g., PPG data, NIRS (near-infrared spectroscopy) data, ECG data, GSR (galvanic skin response) data, BIA data, biomarker data obtained through the user's wrist in contact with the second surface (410B) of the housing (410)) or the corresponding biosignal.

[0144] The key input device (402, 403, 404) may include a wheel key (402) disposed on a first surface (410A) of the housing (410) and rotatable in at least one direction, and / or a side key button (403, 404) disposed on a side (410C) of the housing (410). The wheel key (402) may be in a shape corresponding to the shape of the front plate (401). In another embodiment, the wearable electronic device (400) may not include some or all of the aforementioned key input devices (402, 403, 404), and the key input device (402, 403, 404) that is not included may be implemented in other forms, such as soft keys, on the display (420). The fastening member (450, 460) may be detachably fastened to at least a portion of the housing (410). The fastening member (450, 460) may include one or more of a fixing member (452), a fixing member fastening hole (453), a band guide member (454), and a band fixing ring (455).

[0145] The fixing member (452) may be configured to fix the housing (410) and the fastening member (450, 460) to a part of the user's body (e.g., wrist, ankle, etc.). The fixing member fastening hole (453) may fix the housing (410) and the fastening member (450, 460) to a part of the user's body in correspondence with the fixing member (452). The band guide member (454) may be configured to limit the range of movement of the fixing member (452) when the fixing member (452) is fastened to the fixing member fastening hole (453), thereby allowing the fastening member (450, 460) to be fastened in close contact with a part of the user's body. The band fixing ring (455) may limit the range of movement of the fastening member (450, 460) when the fixing member (452) and the fixing member fastening hole (453) are fastened.

[0146] FIG. 5 is a diagram illustrating an example of a process in which an electronic device (200) according to one embodiment provides motion information.

[0147] According to one embodiment, an electronic device (200) (e.g., a processor (210) or a memory (220)) may include a grip strength analysis engine (510). The grip strength analysis engine (510) may be for generating and / or providing exercise information (520) related to muscle strength exercises. The grip strength analysis engine (510) may be implemented in hardware, software, or firmware. The grip strength analysis engine (510) may not need to be implemented in physically distinct hardware. For example, to implement the grip strength analysis engine (510), the processor (210) of the electronic device (200) may execute instructions stored in the memory (220) and control hardware associated with operation and / or function (e.g., a sensor module (230), an output interface (240), and a communication module (250) of FIG. 2).

[0148] According to one embodiment, the sensor module (230) of the electronic device (200) may include a biosensor (231) and / or a motion sensor (232).

[0149] According to one embodiment, the grip strength analysis engine (510) may acquire (e.g., receive) bio-data (or bio-signals) from a bio-sensor (231) and / or motion data (or motion signals) from a motion sensor (232) as input information. The grip strength analysis engine (510) may monitor grip strength information (or identify changes in grip strength) based on the input information and generate exercise information (520) based on the monitoring results. For example, the exercise information (520) may be intended to guide muscle strength exercises. The grip strength analysis engine (510) may provide the exercise information (520) to a user as output information. For example, the grip strength analysis engine (510) may output the exercise information (520) through an output interface (240).

[0150] According to one embodiment, strength exercises (or anaerobic exercises) may be classified into a first activity (or first type of activity) that is countable using a motion sensor (232) and a second activity (or second type of activity) that is uncountable using only a motion sensor (231). For example, the first activity may correspond to a non-grip strength activity in which no grip strength is generated. The second activity may correspond to a grip strength activity in which a grip strength is generated.

[0151] According to one embodiment, the grip strength analysis engine (510) can monitor (e.g., measure, track) the first activity based on motion data from the motion sensor (232). For example, if the electronic device (200) is a smart watch type wearable electronic device (400), the real-time progress (e.g., number of times performed) of the first activity can be monitored (e.g., measure, track) by detecting wrist movement (e.g., arm movement) through the motion sensor (232) within the wearable electronic device (400) due to the nature of the wearable electronic device (400) worn on the wrist. It may be difficult to monitor the overall strength exercise including the second activity using only motion data.

[0152] According to one embodiment, the grip strength analysis engine (510) can monitor the real-time progress of the second activity (e.g., number of repetitions, calorie consumption, grip strength change, grip strength duration, progress status of a preset set of activities, weight, total exercise duration) based on biometric data from the biometric sensor (231), for example, second biometric data during a second time interval in which grip strength is applied. Accordingly, it may be possible to monitor the real-time progress of the second activity or the overall monitoring (e.g., measurement, tracking) of the strength exercise including the second activity.

[0153] According to one embodiment, the grip strength analysis engine (510) can perform monitoring and / or analysis by combining motion data (e.g., wrist movement) and biometric data (e.g., second biometric data related to grip strength activity during a second time interval in which grip strength is applied). The grip strength analysis engine (510) can improve the accuracy and efficiency of the strength exercise guide by providing exercise information (520) that reflects the results of the monitoring and / or analysis. Accordingly, a safer and more positive exercise experience can be provided to the user.

[0154] According to one embodiment, the exercise information (520) may include at least some of the guide information (521) for real-time grip strength measurement results, guide information (522) for muscle strength exercise analysis results, and guide information (523) for risk analysis results.

[0155] According to one embodiment, the grip strength analysis engine (510) can generate guide information (521) for real-time grip strength measurement results based on monitoring results of a real-time single grip strength activity during a muscle strength exercise performed by a user (e.g., individual grip strength information detected from second biometric data during a second time interval in which grip strength is applied). For example, the guide information (521) for real-time grip strength measurement results may include at least one of the following: the time when grip strength occurs (or the start time of the grip strength activity), the current grip strength level, the end time of the grip strength activity, the duration of the grip strength activity, the number of grip strength activities (or the number of times grip strength is applied), the grip strength activity pattern, the estimated weight, and the grip strength level that must be sustained for maximum muscle activity during a single grip strength activity.

[0156] According to one embodiment, the grip strength analysis engine (510) can generate guide information (522) for the results of the muscle strength exercise analysis based on the results of comprehensively monitoring real-time grip strength activities (e.g., the results of collecting the individual grip strength information multiple times). For example, the guide information (522) for the results of the muscle strength exercise analysis may include guide information for at least one of the number of repetitions of the grip strength activity, the interval between the grip strength activities, the progress status of a set of activities (or a group of multiple grip strength activities), the number of times the activity is performed, the amount of calories consumed, and the total exercise time.

[0157] According to one embodiment, the grip strength analysis engine (510) can generate guide information (523) for the risk analysis results based on the risk assessment results that may occur during the strength exercise being performed by the user.

[0158] According to one embodiment, the grip strength analysis engine (510) can extract from the biometric data from the biometric sensor (231) (e.g., PPG sensor) first biometric data (e.g., PPG data of a first pattern, normal heart rate data) of a first time interval in which normal blood flow (e.g., blood flow when no grip strength is applied) occurs, and second biometric data (e.g., PPG data of a second pattern, abnormal heart rate data, grip strength data) of a second time interval in which abnormal blood flow (e.g., blood flow when grip strength is applied) occurs. The first time interval may be a interval in which no grip strength is applied. The first time interval may be a interval in which normal blood flow occurs. The second time interval may be a interval in which grip strength is applied. The second time interval may be a interval in which abnormal blood flow due to grip strength occurs.

[0159] In one embodiment, the grip strength analysis engine (510) can evaluate the degree of risk (or injury-related risk, e.g., high level, medium level, low level) related to the load applied to the wrist based on grip strength information detected from the second biometric data of the second time interval in which the grip strength is applied. In one embodiment, the grip strength analysis engine (510) can evaluate the degree of risk based on the current gesture detected from the first biometric data of the first time interval (e.g., PPG data of the first pattern, heart rate data) and the current grip strength information detected from the second biometric data of the second time interval in which the grip strength is applied (e.g., PPG data of the second pattern, grip strength data). For example, the grip strength analysis engine (510) can identify the allowable range of grip strength of the current gesture from information regarding the allowable range of grip strength per gesture stored in memory (220) and compare the identified allowable range of grip strength with the current grip strength information. The grip strength analysis engine (510) can evaluate the risk based on the above comparison.

[0160] According to one embodiment, the grip strength analysis engine (510) may use an artificial intelligence model learned according to at least one of machine learning, neural network, or deep learning algorithms. The grip strength analysis engine (510) may analyze input information (e.g., biometric data, output data) and generate output information (e.g., exercise information (520)) using a learning model learned using a rule-based model or an artificial intelligence algorithm. The grip strength analysis engine (510) may provide (e.g., display, output) the generated output information (e.g., exercise information (520)) to a user through an output interface (240).

[0161] FIG. 6 is a flowchart illustrating the operation method of an electronic device (200) according to one embodiment.

[0162] According to one embodiment, the electronic device (200) may be implemented as a wearable electronic device (400) of a wearable type. For example, the wearable electronic device (400) may be a wearable electronic device of a type that can be worn on a specific body part (e.g., wrist) (e.g., smart watch type). According to one embodiment, the biosensor (231) may be a PPG sensor. Sensor data from the biosensor (231) may be PPG data.

[0163] According to one embodiment, the method of FIG. 6 may be performed by a wearable electronic device (400). The method may be intended to provide a muscle strength exercise guide. The movements illustrated in FIG. 6 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of the movements may be changed, and at least two movements may be performed in parallel. In some embodiments, some of the illustrated movements may be omitted, some movements may be integrated, some movements may be changed in order, or other movements may be added.

[0164] At least some of the operations shown in FIG. 6 may correspond to the operations shown in FIG. 3 or be performed in combination with the operations shown in FIG. 3.

[0165] Referring to FIG. 6, a method of operation of an electronic device (200) (e.g., a wearable electronic device (400)) according to one embodiment may include operation 610, operation 615, operation 620, operation 625, operation 630, operation 635, operation 640, operation 645, operation 650, operation 655, operation 660, and operation 665.

[0166] In operation 610, the wearable electronic device (400) can detect an event indicating the start of a strength exercise.

[0167] According to one embodiment, a wearable electronic device (400) may receive user input selecting a strength exercise through a user interface displayed on a display (420) (e.g., a touch on the strength exercise icon (1120) of FIG. 11). When the wearable electronic device (400) receives the user input, it may determine that an event indicating the start of a strength exercise has occurred.

[0168] According to one embodiment, a wearable electronic device (400) can acquire motion data of a user through a motion sensor within a sensor module (411). The wearable electronic device (400) can detect the static state of the user (e.g., a state where there is no movement of the user's position or the user's overall body movement is below a specified level) and the user's wrist movement from the motion data. When the static state of the user and the user's wrist movement are detected, the electronic device (200) can determine that an event indicating the start of strength exercise has occurred.

[0169] In operation 615, the wearable electronic device (400) can activate (or turn on) the PPG sensor within the sensor module (411).

[0170] In operation 620, the wearable electronic device (400) can obtain PPG data, which is sensor data, from the activated PPG sensor. The wearable electronic device (400) can track (or monitor) the PPG data.

[0171] In operation 625, the wearable electronic device (400) can determine whether the amount of change (e.g., degree of change, rate of change, range of change, range of increase / decrease, deviation) of the sensor data (or PPG data) obtained through operation 620 exceeds a specified first threshold. For example, the wearable electronic device (400) can determine (or detect) whether the slope of the PPG data has changed significantly in the positive (+) direction (or above a specified level). For example, if a user wearing the wearable electronic device (400) applies a grip force after starting a strength exercise, the data may transition from the first PPG data of a first time interval in which normal blood flow occurs (or no grip force is applied) to the second PPG data of a second time interval in which abnormal blood flow occurs (or a grip force is applied). The wearable electronic device (400) can detect the start time of the second time interval. The above starting point may be the starting point of the grip strength activity (individual grip strength activity).

[0172] If, as a result of the judgment of operation 625, the amount of change in the sensor data exceeds a specified first threshold (e.g., if the slope of the PPG data changes significantly in the positive (+) direction), the wearable electronic device (400) may proceed to operation 630. In operation 630, the wearable electronic device (400) may start an analysis of a single grip strength activity (or individual grip strength activity) based on the sensor data.

[0173] According to one embodiment, a wearable electronic device (400) can monitor grip strength information (e.g., whether grip strength is measured, the start time of the grip strength activity, the degree of grip strength, the end time of the grip strength activity, the duration of the grip strength activity, the number of grip strength activities, the pattern of grip strength activities, the interval between grip strength activities) from second PPG data during a second time interval in which abnormal blood flow occurs (or grip strength is applied).

[0174] According to one embodiment, a wearable electronic device (400) can detect PPG data of a first pattern (or normal heart rate pattern) indicating a heart rate change within a normal range from sensor data of a PPG sensor, and continuously track the heart rate corresponding to the PPG data of the first pattern. During heart rate tracking, the wearable electronic device (400) can detect PPG data of a second pattern (or abnormal heart rate pattern, grip strength pattern) that can be inferred from grip strength from sensor data of the PPG sensor. As grip strength is applied, the PPG data corresponding to the sensor data may transition from a first pattern in a first time interval to a second pattern in a second time interval. In this case, the slope of the PPG data in the second time interval may change significantly compared to the first time interval. If the wearable electronic device (400) detects that the slope of the PPG data has changed significantly above a specified level, it may determine that one grip strength activity (or individual grip strength activity) has occurred. When the wearable electronic device (400) determines that a single gripping activity has occurred, it may start an analysis of gripping information corresponding to the gripping activity based on the PPG data of the second time interval.

[0175] In operation 635, the wearable electronic device (400) can determine (or detect) whether an abnormal pattern of PPG data, which is sensor data of the PPG sensor, or an abnormal movement of the wrist has been detected. For example, the wearable electronic device (400) can detect an abnormal pattern of PPG data (e.g., a pattern in which PPG data is interrupted without output for a certain period of time) or an abnormal movement of the wrist (e.g., a movement in which the weight is excessive or the wrist is bent excessively) by using motion data from a motion sensor within the sensor module (411) and / or PPG data from a PPG sensor within the sensor module (411).

[0176] If an abnormal pattern in the PPG data and / or abnormal movement of the wrist is detected as a result of the judgment of operation 635, the wearable electronic device (400) may proceed to operation 640. In operation 640, the wearable electronic device (400) may evaluate the risk related to the load applied to the wrist (or the risk related to injury) to a high level and store the risk analysis result in memory (220).

[0177] In operation 645, the wearable electronic device (400) can determine whether additional grip strength activity is detected. For example, the wearable electronic device (400) can determine that additional grip strength activity has occurred if additional PPG data of a second pattern (grip strength pattern) that can be inferred as grip strength from the sensor data of the PPG sensor is detected.

[0178] If additional grip strength activity is detected as a result of the judgment of operation 645, the wearable electronic device (400) may return to operation 620 and repeat (or continue) tracking (or monitoring) the PPG data, which is the sensor data of the PPG sensor.

[0179] If, as a result of the judgment of operation 635, no abnormal pattern of PPG data and / or abnormal movement of the wrist is detected, the wearable electronic device (400) evaluates the risk level to low and can proceed to operation 650.

[0180] In operation 650, the wearable electronic device (400) can determine whether the amount of change (e.g., degree of change, rate of change, range of change, range of increase / decrease, deviation) of sensor data (or PPG data) obtained from the PPG sensor after the grip strength activity of operation 625 has started exceeds a specified second threshold. For example, the wearable electronic device (400) can determine (or detect) whether the slope of the PPG data has changed significantly in the negative (-) direction (or above a specified level). If the slope of the PPG data has changed significantly in the negative (-) direction (or above a specified level), the wearable electronic device (400) can determine that the grip strength activity in which the user applies grip strength has stopped and proceed to operation 655. For example, when a user wearing the wearable electronic device (400) releases the applied grip force, the data may be switched from the second PPG data of the second time interval in which abnormal blood flow occurs (or grip force is applied) to the first PPG data of the first time interval in which normal blood flow occurs (or grip force is not applied). The wearable electronic device (400) may detect the end point of the second time interval. The end point may be the end point of the grip force activity (individual grip force activity).

[0181] In operation 655, the wearable electronic device (400) can terminate the analysis of a single grip strength activity (or individual grip strength activity) initiated in operation 630.

[0182] In operation 660, the wearable electronic device (400) can store the real-time grip strength measurement results and / or muscle strength exercise analysis results performed through operation 630 in memory (220).

[0183] In action 665, the wearable electronic device (400) may provide the user with a user interface that includes an indicator suggesting to stop strength exercise. For example, if no additional grip strength activity is detected as a result of the judgment in action 645, the wearable electronic device (400) may anticipate (or estimate) that strength exercise has been stopped and provide (or output) an indicator (e.g., UI element, guide message, guide voice, specified vibration pattern) suggesting to the user to stop strength exercise.

[0184] According to one embodiment, the wearable electronic device (400) may generate exercise information related to strength training (e.g., guide information for strength training) based on at least one of a risk analysis result stored through motion 640, a real-time grip strength measurement result stored through motion 660, or a strength training analysis result, and may provide a user interface for said exercise information to the user. For example, the wearable electronic device (400) may display UI elements corresponding to said user interface through a display (420). The wearable electronic device (400) may output a guide voice corresponding to said user interface through an audio module (405, 408) (e.g., a speaker). The wearable electronic device (400) may output a designated vibration pattern corresponding to said user interface through a haptic module (e.g., the haptic module (179) of FIG. 1).

[0185] FIG. 7a is a graph (700) illustrating examples of a non-grip force section (710) and a grip force section (720) of sensor data according to one embodiment. FIG. 7b is a graph illustrating examples of a non-grip force section (710) of sensor data according to one embodiment. FIG. 7c is a graph illustrating examples of a grip force section (720) of sensor data according to one embodiment.

[0186] According to one embodiment, an electronic device (200) that provides exercise information related to strength training (e.g., a strength training guide based on grip strength information) may be a wearable electronic device (400) worn on a user's wrist. A biosensor (231) used for monitoring the grip strength information may be a PPG sensor. The biodata used for monitoring the grip strength information may be PPG data, which is sensor data from the PPG sensor.

[0187] The graph (700) of FIG. 7a shows the trend of change in PPG data (or PPG signal), which is the output of the PPG sensor, when sensor data changes from a non-grip force section (710) to a grip force section (720). The non-grip force section (710) represents PPG data when the user's state is a normal state (or a non-grip force state, e.g., a state where no force is applied to the hand and it is not moving). The grip force section (720) represents PPG data when the user's state is a grip force state (e.g., a state where grip force is applied).

[0188] As shown in the graph (700) of FIG. 7a, in the PPG data, it can be seen that the distinction between the non-grip force section (710) and the grip force section (720) is relatively clearly revealed.

[0189] According to one embodiment, grip activity may not be detected in the non-grip section (710). The grip activity can be understood as an activity in which grip force is applied or in which grip force is generated, as a component of muscle exercise. For example, when the user is not applying grip force, there is no external pressure (grip force) on the blood vessels, so normal blood flow occurs and a heart rate pattern within the normal range may be detected. In the grip section (720), grip activity may be detected. For example, when the user is applying grip force, abnormal blood flow occurs due to the grip force acting as external pressure on the blood vessels, and an abnormal heart rate pattern outside the normal range may be detected.

[0190] According to one embodiment, during the non-grip force interval (710), the user's state may be normal (or non-grip force state). The non-grip force interval (710) may be a first time interval in which no grip force is applied. The non-grip force interval (710) may be a first time interval in which normal blood flow occurs. During the non-grip force interval (710), because normal blood flow without grip force causes heart rate changes within the normal range, monitoring of heart rate information (e.g., heart rate, heart rate variability, oxygen saturation) may be possible.

[0191] According to one embodiment, during the grip strength interval (720), the user's state may be a grip strength state. The grip strength interval (720) may be a second time interval in which grip strength is applied. The grip strength interval (720) may be a second time interval in which abnormal blood flow occurs. During the grip strength interval (720), instead of being able to monitor heart rate information due to abnormal blood flow different from the normal blood flow of the non-grip strength interval (710), monitoring of grip strength information may be possible.

[0192] The graph in FIG. 7b is an enlarged view of the non-grip force section (710) in FIG. 7a. The graph in FIG. 7c is an enlarged view of the grip force section (720). The graph in FIG. 7c is an example of PPG data output from a PPG sensor within the wearable electronic device (400) during the corresponding grip force section (720) when a user wearing the wearable electronic device (400) applies a total of 12 divided forces (grip force) while holding a cylindrical object (e.g., a steel bar).

[0193] When comparing the first PPG data (or first PPG signal) representing the non-grip force section (710) of FIGS. 7a and 7b with the second PPG data (or second PPG signal) representing the grip force section (720) of FIGS. 7a and 7c, it can be seen that the PPG data changes relatively significantly in the grip force section (720) compared to the non-grip force section (710). When muscle strength exercise is performed or grip force is applied (grip force section (720)), the amount of change in the PPG data may exceed a specified threshold range (e.g., the range of the PPG data in the non-grip force section (710)).

[0194] According to one embodiment, the PPG sensor may be a sensor comprising at least one light-emitting part and at least one light-receiving part. For example, the PPG sensor may acquire PPG data (or PPG signal) corresponding to the amount of blood flowing in the arterial blood vessel passing through the wrist using an optical signal. When the user does not perform strength training or does not apply grip strength (non-grip strength period (710)), a relatively large amount of blood may flow in the arterial blood vessel because no external pressure (grip strength) is applied to the user's arterial blood vessel. In this state, monitoring of heart rate information may be possible using an optical signal. In one embodiment, the electronic device (200) may perform monitoring of heart rate information during the non-grip strength period (710). When the user performs strength training or applies grip strength (grip strength period (720)), a relatively small amount of blood may flow in the arterial blood vessel because external pressure (grip strength) is applied to the user's arterial blood vessel. In this state, monitoring of heart rate information may not be possible. In one embodiment, the electronic device (200) can perform monitoring of grip strength information rather than heart rate information during the grip strength interval (720).

[0195] Referring to FIG. 7b, during the non-grip force interval (710), periodic peak signals (or signals having periodicity) corresponding to normal blood flow may be detected from the first PPG data (or first PPG signal). In one embodiment, the electronic device (200) may perform monitoring of heart rate information based on the first PPG signal including the periodic peak signals during the non-grip force interval (710).

[0196] Referring to FIG. 7c, periodic peak signals may not be detected during the grip strength interval (720) due to abnormal blood flow different from normal blood flow. During the grip strength interval (720), second PPG data (or second PPG signal) that falls outside a specified threshold range (e.g., the range of first PPG data in the non-grip strength interval (710)) may be detected. In one embodiment, the electronic device (200) may perform monitoring of grip strength information based on the second PPG signal.

[0197] According to one embodiment, the wearable electronic device (400) can recognize that a situation in which grip force is applied (a situation in which force is applied to the hand) has occurred at a first time point (the start time of the grip force activity) through a significantly changing PPG data value. The wearable electronic device (400) can recognize that a situation in which grip force is released has occurred at a second time point (the end time of the grip force activity) where a significant drop occurs in the PPG data. The wearable electronic device (400) can analyze grip force information (e.g., the start time of the grip force activity (the time when grip force is applied), the end time of the grip force activity (the time when grip force disappears), the degree of grip force, the duration of the grip force activity, the number of times grip force occurs, the interval) through changes or trends in the PPG data values ​​at the first and second time points.

[0198] According to one embodiment, the wearable electronic device (400) can identify a first time interval corresponding to a non-grip strength interval (710) and a second time interval corresponding to a grip strength interval (720) based on PPG data (or PPG signals). The wearable electronic device (400) can filter the first PPG data (e.g., PPG data of a first pattern or a normal heart rate pattern) during the first time interval. The wearable electronic device (400) can monitor and / or analyze grip strength information (e.g., the start time of the grip strength activity, the end time of the grip strength activity, the degree of grip strength, the duration of the grip strength activity, the number of grip strength activities, the interval between grip strength activities) based on the second PPG data (e.g., PPG data of a second pattern, an abnormal heart rate pattern or a grip strength pattern) during the second time interval.

[0199] According to one embodiment, the wearable electronic device (400) can monitor heart rate information (e.g., heart rate, heart rate variability, oxygen saturation) based on first PPG data (or first PPG signal) during a first time interval corresponding to a non-grip strength interval (710). The wearable electronic device (400) can monitor and / or analyze grip strength information indicating changes in grip strength (e.g., start time of grip strength activity, end time of grip strength activity, degree of grip strength, duration of grip strength activity, number of grip strength activities, interval between grip strength activities) based on second PPG data (or second PPG signal) during a second time interval corresponding to a grip strength interval (720).

[0200] FIG. 8 is a graph (800) illustrating an example of a repetitive grip strength activity interval of sensor data according to one embodiment.

[0201] FIG. 8 shows the trend of change in PPG data (or PPG signal) when a user applies a total of two gripping forces (performs a total of two gripping activities) while wearing a wearable electronic device (400) on their wrist. The first activity period (810) may be the period during which the first gripping force is applied (or the first gripping activity period). The second activity period (820) may be the period during which the second gripping force is applied (or the second gripping activity period). The first activity period (810) shows the change in PPG data when the user maintains a gripping force for a relatively long time (e.g., 5 seconds) while holding an object (e.g., a pull-up bar). The second activity period (820) shows the change in PPG data when the user maintains a gripping force for a relatively short time (e.g., 2 seconds) while holding an object (e.g., a pull-up bar).

[0202] According to one embodiment, a wearable electronic device (200) can identify multiple grip strength activities separately based on PPG data appearing as a first activity period (810) and a second activity period (820) of FIG. 8. The wearable electronic device (200) can monitor and / or analyze grip strength information such as the start / end time of each grip strength activity, the degree of grip strength, the duration of each grip strength activity, the interval between grip strength activities, the pattern of each grip strength activity, and the number of grip strength activities.

[0203] FIGS. 9a, 9b, and 9c are drawings illustrating graphs of sensor data of a biosensor (231) according to various types of strength exercises and examples of a user interface displayed on a wearable electronic device (400). The user interface may correspond to an execution screen of an application related to strength exercises (e.g., a health application, an exercise application). The user interface may be intended to provide exercise information related to strength exercises (e.g., guide information for strength exercises).

[0204] FIG. 9a is a drawing illustrating an example of a graph (910) of sensor data (e.g., PPG data) and a user interface (921, 922) displayed on a wearable electronic device (400) when a first strength exercise (e.g., deadlift exercise) is performed according to one embodiment.

[0205] According to one embodiment, the deadlift exercise may be a strength exercise that can count the number of activities using a motion sensor (232). When a user initiates a deadlift exercise while holding an object (e.g., a barbell) and performs a total of three gripping activities (e.g., lifting the barbell by applying gripping force and lowering the barbell by releasing gripping force), the wearable electronic device (400) can detect sensor data (e.g., PPG data) including a first activity period (911), a second activity period (912), and a third activity period (913) as shown in FIG. 9a through a biosensor (231) (e.g., a PPG sensor).

[0206] According to one embodiment, the wearable electronic device (400) can detect an abnormal pattern (915) (e.g., an abnormal pattern in PPG data, an abnormal movement of the wrist) during a deadlift exercise from the sensor data. When the abnormal pattern (915) occurs, the wearable electronic device (400) can perform an activity count processing (e.g., adding to or subtracting from the count) using motion data from the motion sensor (232). In a subsequent period (916) after the occurrence of the abnormal pattern (915), a specified time may pass without grip force being detected, or a change in motion data may be detected while grip force is not detected. In such cases, the wearable electronic device (400) can determine the time to stop the exercise based on the sensor data (e.g., PPG data) and / or the motion data, and provide guidance information regarding the time to stop the exercise.

[0207] According to one embodiment, the wearable electronic device (400) may display a first user interface (921) containing guide information for grip strength activities detected through a first activity period (911), a second activity period (912), and a third activity period (913). The wearable electronic device (400) may display a second user interface (922) containing guide information related to the time of exercise cessation.

[0208] FIG. 9b is a drawing illustrating an example of a graph (930) of sensor data (e.g., PPG data) and a user interface (940) displayed on a wearable electronic device (400) when a second strength exercise (e.g., climbing exercise) is performed according to one embodiment.

[0209] According to one embodiment, when a user performs a climbing exercise, the wearable electronic device (400) can detect sensor data (e.g., PPG data) including a first activity period (931), a second activity period (932), and a third activity period (933) as shown in FIG. 9b through a biosensor (231) (e.g., PPG sensor). When the user performs a gripping activity of gripping holds arranged laterally within the course a total of three times, sensor data such as the first activity period (931), the second activity period (932), and the third activity period (933) can be detected. The wearable electronic device (400) can detect a first gesture (e.g., a first gesture that generates grip strength) related to a strength exercise (e.g., climbing exercise) from the sensor data. For example, the first gesture above may correspond to an open grip gesture (a grip gesture in which the thumb and four fingers are separated) based on lateral movement (movement in the lateral direction).

[0210] According to one embodiment, a wearable electronic device (400) may detect grip strength in each activity segment (931, 932, 933) based on sensor data (e.g., PPG data) and provide guidance information for grip activities and / or sets of grip activities based on the detected grip strength. The wearable electronic device (400) may display a user interface (940) containing the guidance information. For example, the wearable electronic device (400) may compare grip strength information based on current grip activities with grip strength information based on previous grip activities of the course and provide guidance information (e.g., appropriate number of grips or intervals, feedback on grip duration, suggestions to add or subtract grip strength) based on the comparison. Since climbing exercises often involve attempting the same course multiple times, providing such guidance information can increase the accuracy and efficiency of strength training guidance.

[0211] FIG. 9c is a drawing illustrating an example of a graph (950) of sensor data (e.g., PPG data) and a user interface (960) displayed on a wearable electronic device (400) when a third strength exercise (e.g., pull-up exercise) is performed according to one embodiment.

[0212] According to one embodiment, the pull-up exercise may be a strength exercise for which it is impossible to count the number of activities using only the motion sensor (232). The wearable electronic device (400) can count the number of pull-up exercises by detecting grip strength based on sensor data (e.g., PPG data).

[0213] After the user initiates a pull-up exercise, if a total of five grip strength activities (e.g., applying grip strength to lift the arm and releasing grip strength to lower the arm) are performed, the wearable electronic device (400) can detect sensor data (e.g., PPG data) including a first activity period (951), a second activity period (952), a third activity period (953), a fourth activity period (954), and a fifth activity period (955) as shown in FIG. 9c through a biosensor (231) (e.g., PPG sensor).

[0214] According to one embodiment, a wearable electronic device (400) may display a user interface (960) containing guide information for grip strength activities detected through a first activity period (951), a second activity period (952), a third activity period (953), a fourth activity period (954), and a fifth activity period (955). For example, the guide information may include information regarding the number of times the activity is performed, calories consumed, the progress status (or progress rate) of the activity set, the total exercise time, etc.

[0215] FIG. 10 is a drawing illustrating an environment in which a wearable electronic device (400, 1020) and an electronic device (1010) operate in conjunction according to one embodiment.

[0216] According to one embodiment, the electronic device (200) of FIG. 2 may be a wearable electronic device (400, 1020). The electronic device (200) of FIG. 2 may be a smart watch type wearable electronic device (400) or a smart ring type wearable electronic device (1020).

[0217] Referring to FIG. 10, a wearable electronic device (400, 1020) (e.g., a wearable electronic device, smart watch, smart ring worn by a user) and an electronic device (1010) (e.g., a user's smartphone) according to one embodiment can be interconnected. For example, the wearable electronic device (400) may be a smart watch type wearable electronic device. The wearable electronic device (1020) may be a smart ring type wearable electronic device. The electronic device (1010) may be a smartphone type electronic device.

[0218] According to one embodiment, a wearable electronic device (400, 1020) may be wirelessly connected to an electronic device (1010). The wearable electronic device (400, 1020) may be connected to the electronic device (1010) via a short-range network supported by a communication circuit (e.g., the communication module (250) of FIG. 2), and may transmit and / or receive data to and from each other. For example, a network (e.g., a short-range network) for establishing a connection between the wearable electronic device (400, 1020) and the electronic device (1010) may be appropriately selected. For example, Bluetooth Low Energy (BLE), Wi-Fi Direct, Near Field Communication (NFC), Ultra-Wide Band (UWB) communication, or Infra-Red communication may be used to establish a connection between the wearable device (400, 1020) and the electronic device (1010), either together with or instead of Bluetooth.

[0219] According to one embodiment, the wearable electronic device (400, 1020) and / or the electronic device (1010) may provide exercise information related to strength exercises (e.g., guide information for strength exercises). The wearable electronic device (400, 1020) and / or the electronic device (1010) may provide a user interface to the user that guides strength exercises based on grip strength information.

[0220] According to one embodiment, a wearable electronic device (400, 1020) can transmit information regarding a user interface guiding strength exercises to an electronic device (1010) through a communication circuit (e.g., communication module (250) of FIG. 2), thereby enabling at least a portion of the user interface (e.g., screen, text, voice, vibration) to be output through the electronic device (1010). The electronic device (1010) may be connected to the wearable electronic device (400, 1020) via short-range wireless communication through a communication circuit (e.g., communication module (250) of FIG. 2).

[0221] FIG. 11 is a diagram illustrating an example of a user interface for selecting strength training according to one embodiment. The user interface may correspond to an execution screen of an application related to strength training (e.g., a health application, an exercise application). The user interface may be intended to provide exercise information related to strength training (e.g., guide information for strength training).

[0222] According to one embodiment, a wearable electronic device (400) may display a user interface screen (1110) for selecting a type of exercise (or exercise discipline) through a display (420). The user interface screen (1110) may include a strength exercise icon (1120). The wearable electronic device (400) may receive user input touching the strength exercise icon (1120). Based on the reception of the user input touching the strength exercise icon (1120), the wearable electronic device (400) may detect an event (or triggering event) indicating the start of strength exercise. In response to detecting the event, the wearable electronic device (400) may start monitoring grip strength information indicating a change in grip strength.

[0223] FIG. 12a is a diagram illustrating an example of a user interface for first exercise information according to one embodiment. The user interface may correspond to an execution screen of an application related to strength training (e.g., a health application, an exercise application).

[0224] According to one embodiment, the wearable electronic device (400) may display user interface screens (1211, 1212, 1213) for first exercise information. The first exercise information may be for strength exercise guidance. For example, the first exercise information may be guide information indicating real-time measurement results and / or analysis results of activity sets of strength exercise currently being performed (e.g., risk level of each activity set, grip strength duration, number of repetitions, exercise evaluation). The wearable electronic device (400) may provide (or output) a user interface for the first exercise information (e.g., user interface screens (1211, 1212, 1213) of FIG. 12a, UI elements, guide messages, guide voice, vibration patterns), thereby enabling the user to easily determine in real-time whether the exercise progress is smooth.

[0225] FIG. 12b is a diagram illustrating an example of a user interface for second exercise information according to one embodiment. The user interface may correspond to an execution screen of an application related to strength training (e.g., a health application, an exercise application).

[0226] According to one embodiment, the wearable electronic device (400) may display user interface screens (1221, 1222) for second exercise information. The second exercise information may be for strength exercise guidance. For example, the second exercise information may be generated based on grip strength information detected from biometric data (e.g., PPG data) and may be guidance information for risk analysis results. The wearable electronic device (400) may provide (or output) a user interface for the second exercise information (e.g., user interface screens (1221, 1222) of FIG. 12b, UI elements, guidance messages, guidance voice, vibration patterns). For example, the user interface for the second exercise information may include UI elements indicating changes in the exercise performance pattern (e.g., grip strength pattern) of the strength exercise (or activity, activity set) currently being performed, the risk level, or the element(s) that influenced the risk level. The user interface for the second exercise information above may include an indicator asking for the intention to stop the strength exercise (e.g., 'Stop set and rest' menu, 'Ignore and continue').

[0227] According to one embodiment, some of the UI elements of the user interface for the second exercise information (e.g., the first user interface screen (1221) of FIG. 12b) may be output through a wearable electronic device (400) (e.g., a wearable electronic device worn by a user). Other parts of the UI elements of the user interface for the second exercise information (e.g., the first user interface screen (1222) of FIG. 12b) may be output through an electronic device (1010) (e.g., a user's smartphone). For example, the wearable electronic device (400) (e.g., a wearable electronic device worn by a user) and the electronic device (1010) (e.g., a user's smartphone) may be connected via short-range wireless communication and output user interfaces that are linked or synchronized with each other.

[0228] FIG. 12c is a diagram illustrating an example of a user interface for third exercise information according to one embodiment. The user interface may correspond to an execution screen of an application related to strength training (e.g., a health application, an exercise application).

[0229] According to one embodiment, the wearable electronic device (400) may display a user interface screen (1230) for third exercise information when strength exercise is completed. The third exercise information may be for strength exercise guidance. For example, the third exercise information may be generated based on grip strength information and / or exercise performance patterns (e.g., grip strength patterns) detected from bio-data (e.g., PPG data) during strength exercise. For example, the third exercise information may be guide information indicating comprehensive analysis and / or evaluation results of the completed strength exercise.

[0230] According to one embodiment, the user interface screen (1230) may display information regarding exercise analysis results related to potential risks that may occur during the performance of strength exercises, such as rest time, set heart rate, exercise performance pattern (e.g., length of each grip strength activity or each movement within the set performed), stability, average movement time, stability of movement, stability of grip strength, and time taken to complete the set.

[0231] According to one embodiment, a wearable electronic device (e.g., electronic device (101) of FIG. 1, electronic device (200) of FIG. 2, wearable electronic device (400) of FIG. 4a and 4b, wearable electronic device (1020) of FIG. 10) comprises at least one processor including processing circuitry (e.g., processor (120) of FIG. 1, processor (210) of FIG. 2), a biosensor (e.g., sensor module (176) of FIG. 1, biosensor (231) of FIG. 2), a communication circuit (e.g., communication module (190) of FIG. 1, communication module (250) of FIG. 2), an output interface (e.g., acoustic output module (155) of FIG. 1, display module (160), audio module (170), haptic module (179), output interface (240) of FIG. 2), and a memory storing instructions (e.g., memory (130) of FIG. 1, FIG. It may include a memory (220) of 2. The biosensor is intended to sense the blood flow of a user wearing the wearable electronic device and may include at least one light emitter and at least one light receiver. The instructions may be executed individually or collectively by the at least one processor so that the wearable electronic device acquires biodata related to the user's blood flow through the biosensor while an application related to strength exercise is executed, identifies changes in the user's grip strength based on changes in blood flow appearing in the biodata due to the strength exercise performed by the user, generates exercise information related to the strength exercise based on the identified changes in grip strength, and provides the exercise information to the user through at least one of the communication circuit or the output interface.

[0232] According to one embodiment, the wearable electronic device may be a wearable electronic device worn on the wrist of the user (e.g., the wearable electronic device (400) of FIG. 4a and FIG. 4b).

[0233] According to one embodiment, the wearable electronic device may be a wearable electronic device worn on the user's finger (e.g., the wearable electronic device (1020) of FIG. 10).

[0234] According to one embodiment, the biosensor may include a PPG sensor.

[0235] According to one embodiment, the wearable electronic device may further include a motion sensor.

[0236] According to one embodiment, the instructions may be executed individually or collectively by the at least one processor to enable the wearable electronic device to monitor grip strength information indicating the change in grip strength. The grip strength information may include information on at least one of whether grip strength is measured, the start time of the grip strength activity, the degree of grip strength, the end time of the grip strength activity, the duration of the grip strength activity, the number of grip strength activities, the pattern of the grip strength activity, or the interval between grip strength activities.

[0237] According to one embodiment, the instructions may be executed individually or collectively by the at least one processor so that the wearable electronic device monitors heart rate information based on first biometric data obtained through the biometric sensor during a first time interval in which no grip force is applied, and monitors grip force information indicating the change in grip force based on second biometric data obtained through the biometric sensor during a second time interval in which a grip force is applied.

[0238] According to one embodiment, the instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device determines that a grip strength activity has started when the amount of change in the biometric data exceeds a specified first threshold, determines that the grip strength activity has ended when the amount of change in the biometric data exceeds a specified second threshold after the grip strength activity has started, obtains individual grip strength information from the biometric data during a time interval corresponding to the grip strength activity, and monitors the grip strength information indicating the change in grip strength by collecting the individual grip strength information.

[0239] According to one embodiment, the instructions may be executed individually or collectively by the at least one processor so that the wearable electronic device detects an event indicating the start of the muscle strength exercise based on the amount of change in the biometric data exceeding a specified threshold range, and in response to the event, starts monitoring of the grip strength information indicating the change in grip strength.

[0240] According to one embodiment, the instructions may be executed individually or collectively by the at least one processor so that the wearable electronic device receives user input selecting the strength exercise through the execution screen of the application, detects an event indicating the start of the strength exercise based on the reception of the user input, and in response to the event, starts monitoring of the grip strength information indicating the change in grip strength.

[0241] According to one embodiment, the instructions may be executed individually or collectively by the at least one processor so that the wearable electronic device acquires motion data of the user through a motion sensor of the wearable electronic device, detects an event indicating the start of the muscle strength exercise based on the detection of the user's body movement from the motion data, and in response to the detection of the event, starts monitoring of grip strength information indicating the change in grip strength.

[0242] According to one embodiment, the instructions may be executed individually or collectively by the at least one processor so that the wearable electronic device acquires motion data of the user through a motion sensor of the wearable electronic device, detects an event indicating the start of the muscle strength exercise based on the detection of the user's static state and the user's wrist movement from the motion data, and in response to the event, starts monitoring of grip strength information indicating the change in grip strength.

[0243] According to one embodiment, the instructions may be executed individually or collectively by the at least one processor so that the wearable electronic device detects a gesture corresponding to the user's wrist movement through a motion sensor of the wearable electronic device, determines whether a grip strength is measured based on the biometric data, determines the gesture as a first gesture related to the muscle strength exercise if the grip strength is measured, and determines the gesture as a second gesture unrelated to the muscle strength exercise if the grip strength is not measured.

[0244] According to one embodiment, the instructions are executed individually or collectively by the at least one processor, so that when the wearable electronic device determines the gesture as the first gesture, it monitors grip strength information indicating the change in grip strength, and when the gesture is determined as the second gesture, it skips monitoring the grip strength information.

[0245] According to one embodiment, the instructions may be executed individually or collectively by the at least one processor so that when the wearable electronic device determines the gesture to be the first gesture, it performs a first function corresponding to the first gesture, and when the gesture is determined to be the second gesture, it performs a second function corresponding to the second gesture.

[0246] According to one embodiment, the instructions may be executed individually or collectively by the at least one processor so that the wearable electronic device determines the risk associated with the load applied to the wrist by the muscle exercise based on grip strength information indicating the change in grip strength, and provides an indicator of the risk through the output interface.

[0247] According to one embodiment, the exercise information may include guide information for guiding the user to perform the strength exercise. The exercise information may include at least some of guide information regarding real-time strength measurement results, guide information regarding strength exercise analysis results, and guide information regarding risk analysis results.

[0248] According to one embodiment, the guide information for guiding the user to the muscle exercise may include at least some of the information regarding the time to stop the muscle exercise and the information for adjusting the difficulty of the exercise through changes in grip strength.

[0249] According to one embodiment, a method of operation of a wearable electronic device (e.g., electronic device (101) of FIG. 1, electronic device (200) of FIG. 2, wearable electronic device (400) of FIG. 4a and FIG. 4b, wearable electronic device (1020) of FIG. 10) may include, while an application related to strength exercise is executed, acquiring biometric data related to blood flow of a user wearing the wearable electronic device through a biometric sensor comprising at least one light emitter and at least one light receiver; identifying a change in grip strength of the user based on a change in blood flow appearing in the biometric data due to the strength exercise performed by the user; generating exercise information related to the strength exercise based on the identified change in grip strength; and providing the exercise information.

[0250] According to one embodiment, the operation of identifying the change in grip strength may include the operation of monitoring grip strength information indicating the change in grip strength. The grip strength information may include information regarding at least one of whether grip strength is measured, the start time of the grip strength activity, the degree of grip strength, the end time of the grip strength activity, the duration of the grip strength activity, the number of grip strength activities, the pattern of the grip strength activity, or the interval between grip strength activities.

[0251] According to one embodiment, the operation of identifying the change in grip strength may include the operation of monitoring heart rate information based on first bio-data obtained through the bio-sensor during a first time interval during which no grip strength is applied, and the operation of monitoring grip strength information indicating the change in grip strength based on second bio-data obtained through the bio-sensor during a second time interval during which grip strength is applied.

[0252] According to one embodiment, the operation of identifying the change in grip strength may include: determining that a grip strength activity has started when the amount of change in the bio-data exceeds a specified first threshold; determining that the grip strength activity has ended when the amount of change in the bio-data exceeds a specified second threshold after the grip strength activity has started; obtaining individual grip strength information from the bio-data during a time interval corresponding to the grip strength activity; and monitoring grip strength information indicating the change in grip strength by collecting the individual grip strength information.

[0253] According to one embodiment, the method may include an action of detecting an event indicating the start of muscle strength exercise based on the change amount of the bio-data exceeding a specified threshold range, and an action of starting monitoring of grip strength information indicating the change in grip strength in response to the event.

[0254] According to one embodiment, the method may include receiving user input selecting the strength exercise through the execution screen of the application, detecting an event indicating the start of the strength exercise based on the reception of the user input, and starting monitoring of grip strength information indicating the change in grip strength in response to the event.

[0255] According to one embodiment, the method may include the operation of acquiring motion data of the user through a motion sensor of the wearable electronic device, the operation of detecting an event indicating the start of the muscle strength exercise based on the detection of the user's body movement from the motion data, and the operation of starting monitoring of grip strength information indicating the change in grip strength in response to the event.

[0256] According to one embodiment, the method may include the operation of acquiring motion data of the user through a motion sensor of the wearable electronic device, the operation of detecting an event indicating the start of the muscle strength exercise based on the detection of the user's static state and the user's wrist movement from the motion data, and the operation of starting monitoring of grip strength information indicating the change in grip strength in response to the detection of the event.

[0257] According to one embodiment, the method may further include the action of detecting a gesture according to the wrist movement of the user through a motion sensor of the wearable electronic device, the action of determining whether a grip strength is measured based on the biometric data, the action of determining the gesture as a first gesture related to the muscle strength exercise when the grip strength is measured, and the action of determining the gesture as a second gesture unrelated to the muscle strength exercise when the grip strength is not measured.

[0258] According to one embodiment, the method may include an operation of monitoring grip strength information indicating a change in grip strength when the gesture is determined to be the first gesture, and an operation of skipping the monitoring of the grip strength information when the gesture is determined to be the second gesture.

[0259] According to one embodiment, the method may include, when the gesture is determined to be the first gesture, an operation of performing a first function corresponding to the first gesture, and when the gesture is determined to be the second gesture, an operation of performing a second function corresponding to the second gesture.

[0260] According to one embodiment, the method may include the operation of determining a risk related to the load applied to the wrist by the muscle strength exercise based on grip strength information indicating the change in grip strength, and the operation of providing an indicator of the risk through the output interface.

[0261] According to one embodiment, the storage medium may be a computer-readable non-transient storage medium. The storage medium may have a program recorded thereon for executing a method of operation of a wearable electronic device (e.g., the electronic device (101) of FIG. 1, the electronic device (200) of FIG. 2, the wearable electronic device (400) of FIG. 4a and FIG. 4b, the wearable electronic device (1020) of FIG. 10). The above storage medium may have a program recorded thereon for executing a method comprising: acquiring biometric data related to blood flow of a user wearing the wearable electronic device through a biometric sensor comprising at least one light emitter and at least one light receiver while an application related to muscle strength exercise is executed; identifying a change in the user's grip strength based on a change in blood flow appearing in the biometric data due to the muscle strength exercise performed by the user; generating exercise information related to the muscle strength exercise based on the identified change in grip strength; and providing the exercise information.

[0262] An electronic device and its method of operation according to various embodiments of the present disclosure can improve the accuracy and efficiency of a muscle strength exercise guide by providing a muscle strength exercise guide that incorporates a grip strength element.

[0263] An electronic device and its method of operation according to various embodiments of the present disclosure can provide an appropriate strength training guide tailored to the characteristics of strength training in which movements of applying or releasing grip strength are repeatedly performed during exercise.

[0264] An electronic device and its method of operation according to various embodiments of the present disclosure can prevent injury and enhance exercise effectiveness by reflecting real-time feedback on changes in grip strength in a muscle strength exercise guide.

[0265] An electronic device and its method of operation according to various embodiments of the present disclosure can prevent gesture recognition errors by performing gesture recognition that reflects a grip strength element while muscle strength exercise is being performed, thereby improving the user experience.

[0266] The effects obtainable from the present disclosure are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art to which the present disclosure belongs from the description of the present disclosure.

[0267] Methods according to the claims or embodiments described in the specification of the present disclosure may be implemented in the form of hardware, software, or a combination of hardware and software.

[0268] When implemented in software, a computer-readable storage medium may be provided for storing one or more programs (software modules). One or more programs stored in the computer-readable storage medium are configured for execution by one or more processors within an electronic device. One or more programs include instructions that cause the electronic device to execute methods according to the claims or embodiments described in the specification of this disclosure.

[0269] In the present disclosure, the function or operation performed by an electronic device may be performed by one or more processors executing one or more instructions stored in memory. The function or operation of the electronic device mentioned in the present disclosure may be performed by a single processor executing one or more instructions, or by a combination of multiple processors executing one or more instructions. A processor mentioned in the present disclosure is understood to include a circuit for performing operations or controlling other components of the electronic device. For example, the one or more processors may include a central processing unit (CPU), a micro-processor unit (MPU), an application processor (AP), a communication processor (CP), a neural processing unit (NPU), a system on chip (SoC), or an integrated circuit (IC) configured to execute one or more instructions. The one or more processors may be configured to perform the operation of the electronic device described above.

[0270] In the present disclosure, a program (software module, software) may be stored in a random access memory, a non-volatile memory including flash memory, a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic disc storage device, a compact disc-ROM (CD-ROM), digital versatile discs (DVDs), or other forms of optical storage devices, or a magnetic cassette. Alternatively, it may be stored in a memory composed of some or all of these. The memory may be composed of a single storage medium or a combination of multiple storage media. The one or more instructions may be stored in a single storage medium or distributed across multiple storage media.

[0271] The electronic device according to the various embodiments disclosed in this document may be of various forms. The electronic device may include, for example, a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a consumer electronics device. The electronic device according to the embodiments of this document is not limited to the devices described above.

[0272] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, phrases such as "A or B," "at least one of A and B," "at least one of A or B," "A, B or C," "at least one of A, B and C," and "at least one of A, B, or C" may each include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used simply to distinguish said components from other said components and do not limit said components in any other aspect (e.g., importance or order). Where any (e.g., 1st) component is referred to as “coupled” or “connected” to another (e.g., 2nd) component, with or without the terms “functionally” or “communicationly,” it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0273] The term “module” as used in the various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0274] Various embodiments of the present document may be implemented as software (e.g., program (140)) comprising one or more instructions stored in a storage medium (e.g., internal memory (136) or external memory (138)) readable by a machine (e.g., electronic device (101)). For example, a processor (e.g., processor (120)) of the machine (e.g., electronic device (101)) may call at least one of the one or more instructions stored in the storage medium and execute it. This enables the machine to be operated to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily.

[0275] According to one embodiment, the method according to the various embodiments disclosed herein may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or distributed online (e.g., download or upload) through an application store (e.g., Play Store™) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0276] According to various embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In a wearable electronic device, At least one processor including processing circuitry; A biosensor comprising at least one light emitter and at least one light receiver for sensing the blood flow of a user wearing the above-mentioned wearable electronic device; Communication circuit; Output interface; and It includes memory for storing instructions, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: While an application related to strength training is running, biometric data related to the user's blood flow is acquired through the biosensor, and Identifying changes in the user's grip strength based on changes in blood flow indicated in the biometric data by the strength exercises performed by the user, and Based on the above-mentioned changes in grip strength, exercise information related to the above-mentioned muscle strength exercise is generated, and A wearable electronic device that provides exercise information to the user through at least one of the communication circuit or the output interface.

2. In Claim 1, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: Monitor grip strength information indicating the above grip strength change, A wearable electronic device comprising information on at least one of the grip strength information, whether grip strength is measured, the start time of the grip strength activity, the degree of grip strength, the end time of the grip strength activity, the duration of the grip strength activity, the number of grip strength activities, the pattern of the grip strength activity, or the interval between grip strength activities.

3. In Claim 1, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: During a first time interval in which no gripping force is applied, heart rate information is monitored based on first biometric data obtained through the biometric sensor, and A wearable electronic device that monitors grip strength information indicating a change in grip strength based on second biometric data obtained through the biometric sensor during a second time interval in which grip strength is applied.

4. In Claim 1, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: If the amount of change in the above biometric data exceeds a specified first threshold, it is determined that grip strength activity has started, and If the amount of change in the biometric data exceeds a specified second threshold after the grip strength activity has started, it is determined that the grip strength activity has ended. Individual grip strength information is obtained from biometric data during the time interval corresponding to the above grip strength activity, and A wearable electronic device that monitors grip strength information indicating changes in grip strength by collecting the individual grip strength information.

5. In Claim 1, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: Based on the change amount of the above bio-data exceeding a specified threshold range, an event indicating the start of the muscle strength exercise is detected, and A wearable electronic device that initiates monitoring of grip strength information indicating the change in grip strength in response to the above event.

6. In Claim 1, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: Receiving user input to select the strength exercise through the execution screen of the above application, and Based on the reception of the above user input, detect an event indicating the start of the above strength exercise, and A wearable electronic device that initiates monitoring of grip strength information indicating the change in grip strength in response to the above event.

7. In Claim 1, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: Motion data of the user is acquired through the motion sensor of the above-mentioned wearable electronic device, and Based on the detection of the user's body movement from the motion data, an event indicating the start of the muscle strength exercise is detected, and A wearable electronic device that initiates monitoring of grip strength information indicating a change in grip strength in response to detecting the above event.

8. In Claim 1, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: Motion data of the user is acquired through the motion sensor of the above-mentioned wearable electronic device, and Based on the detection of the user's static state and the user's wrist movement from the motion data, an event indicating the start of the muscle strength exercise is detected, and A wearable electronic device that initiates monitoring of grip strength information indicating the change in grip strength in response to the above event.

9. In Claim 1, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: Detecting a gesture corresponding to the user's wrist movement through a motion sensor of the above-mentioned wearable electronic device, and Determining whether grip strength is measured based on the above biometric data, and When the above grip strength is measured, the above gesture is determined as a first gesture related to the above muscle strength exercise, and A wearable electronic device that determines the gesture as a second gesture unrelated to the muscle strength exercise when the above grip strength is not measured.

10. In Claim 9, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: When the above gesture is determined to be the above first gesture, grip strength information indicating the change in grip strength is monitored, and A wearable electronic device that skips monitoring of grip strength information when the above gesture is determined to be the above second gesture.

11. In Claim 9, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: If the above gesture is determined to be the above first gesture, a first function corresponding to the above first gesture is performed, and A wearable electronic device that performs a second function corresponding to the second gesture when the above gesture is determined to be the above second gesture.

12. In Claim 1, The above instructions are executed individually or collectively by the at least one processor, so that the wearable electronic device: Based on grip strength information indicating the above grip strength change, the risk associated with the load applied to the wrist by the above muscle strength exercise is determined, and A wearable electronic device that provides an indicator of the risk level through the output interface.

13. In a method of operating a wearable electronic device, The operation of acquiring biometric data related to the blood flow of a user wearing the wearable electronic device through a biometric sensor comprising at least one light emitter and at least one light receiver while an application related to muscle strength exercise is executed; An action of identifying a change in the user's grip strength based on a change in blood flow appearing in the biometric data due to the muscle strength exercise performed (exercised) by the user; An action of generating exercise information related to the muscle strength exercise based on the identified grip strength change; and A method including a motion that provides the above-mentioned exercise information.

14. In Claim 13, The action of identifying the above change in grip strength is, The operation of monitoring grip strength information indicating the above grip strength change, A method comprising information on at least one of the above grip strength information, whether grip strength is measured, the start time of the grip strength activity, the degree of grip strength, the end time of the grip strength activity, the duration of the grip strength activity, the number of grip strength activities, the pattern of the grip strength activity, or the interval between grip strength activities.

15. In Claim 13, The action of identifying the above change in grip strength is, An operation of monitoring heart rate information based on first biometric data obtained through the biometric sensor during a first time interval in which no gripping force is applied; and A method comprising the operation of monitoring grip strength information indicating a change in grip strength based on second biometric data obtained through the biometric sensor during a second time interval in which grip strength is applied.

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