Wearable device, method and storage medium for providing information about physical activity of a user

Abstract

According to an embodiment, the method performed by the wearable device may include recognizing the start of a user workout based on a specified action. The method may include obtaining second information about the specified action. The method may include obtaining second information about the user's workout action while performing the specified action. The method may include obtaining a first value indicating the number of times the specified action for the second information has been performed, based on a first threshold associated with first information. The method may include obtaining a second value indicating the number of times the specified action for the second information has been performed, based on a second threshold associated with the first information. The method may include displaying the first and second values ​​on a display.

Description

Technical Field

[0001] This disclosure relates to wearable devices, methods, and storage media for providing information about a user's physical activity. Background Technology

[0002] Various services are provided through wearable devices. Wearable devices can operate when worn on a part of a user's body. When worn on a user's body, wearable devices can identify the user's biometric information and provide services based on that information.

[0003] The above information may be provided as relevant technology for the purpose of aiding understanding of this disclosure. No claims or determination are made regarding whether any of the above information can be used as prior art in relation to this disclosure. Summary of the Invention

[0004] According to an embodiment, the wearable device may include a display, at least one sensor, a first memory storing first information about exercise, a second memory storing instructions, and at least one processor. When executed by the processor, the instructions cause the wearable device to recognize that a user's exercise has begun based on a specified action. When executed by the processor, the instructions cause the wearable device to obtain second information about the specified action. When executed by the processor, the instructions cause the wearable device to obtain a first value indicating the number of times the specified action for the second information has been performed, based on a first threshold associated with the first information. When executed by the processor, the instructions cause the wearable device to obtain a second value indicating the number of times the specified action for the second information has been performed, based on a second threshold associated with the first information. When executed by the processor, the instructions cause the wearable device to display the first and second values ​​on the display.

[0005] According to an embodiment, a method performed by a wearable device may include recognizing the start of a user workout based on a specified action. The method may include obtaining second information about the specified action. The method may include obtaining second information about the user's workout actions based on the execution of the specified action. The method may include obtaining a first value indicating the number of times the specified action has been performed in response to the second information, based on a first threshold associated with the first information. The method may include obtaining a second value indicating the number of times the specified action has been performed in response to the second information, based on a second threshold associated with the first information. The method may include displaying the first and second values ​​on a display.

[0006] According to an embodiment, a non-transitory computer-readable storage medium may store one or more programs. The one or more programs may include instructions that, when executed by a processor of a wearable device having a display, cause the wearable device to recognize the initiation of a user exercise based on a specified action. The one or more programs may include instructions that cause the wearable device to obtain second information about the specified action. The one or more programs may include instructions that cause the wearable device to: obtain a first value indicating the number of times the specified action for the second information has been performed, based on a first threshold associated with the first information. The one or more programs may include instructions that cause the wearable device to: obtain a second value indicating the number of times the specified action for the second information has been performed, based on a second threshold associated with the first information. The one or more programs may include instructions that cause the wearable device to display the first and second values ​​on the display. Attached Figure Description

[0007] Regarding the description of the accompanying drawings, the same or similar reference numerals may be used for the same or similar parts. Furthermore, the above and other aspects, features, and advantages of certain embodiments of this disclosure will become more apparent from the following detailed description taken in conjunction with the accompanying drawings, wherein:

[0008] Figure 1 This is a block diagram of an electronic device in a network environment according to various embodiments;

[0009] Figure 2a and Figure 2b This is a perspective view illustrating example electronic devices according to various embodiments;

[0010] Figure 3 This is an exploded perspective view showing an example electronic device according to various embodiments;

[0011] Figure 4a This is an illustration showing examples of wearable devices for recognizing various exercises of a user according to various embodiments;

[0012] Figure 4b It is a graph illustrating examples of performing multiple sets of time periods according to various embodiments for a specified action;

[0013] Figure 5 This is a block diagram illustrating example configurations of wearable devices according to various embodiments;

[0014] Figure 6a This is a graph illustrating example operations of a wearable device for identifying the number of times a specified action is performed, according to various embodiments.

[0015] Figure 6b This is a graph illustrating example operations of a wearable device for identifying the number of times a specified action is performed, according to various embodiments.

[0016] Figure 7a This is a flowchart illustrating example operation of a wearable device according to various embodiments;

[0017] Figure 7b This is a flowchart illustrating example operation of a wearable device according to various embodiments;

[0018] Figure 8 It is a graph illustrating example operation of a wearable device according to various embodiments;

[0019] Figure 9 It is a graph illustrating example operation of a wearable device according to various embodiments;

[0020] Figure 10 This is a diagram illustrating examples of screens of wearable devices according to various embodiments;

[0021] Figure 11a This is a diagram illustrating example operation of a wearable device for squat exercises according to various embodiments;

[0022] Figure 11b This is a diagram illustrating example operation of a wearable device for arm curl exercises according to various embodiments;

[0023] Figure 12 Includes graphs illustrating example operation of wearable devices according to various embodiments;

[0024] Figure 13 This is a diagram illustrating example operation of a wearable device for displaying a user's exercise results according to various embodiments;

[0025] Figure 14 These are graphs illustrating example operations of a wearable device for displaying a user's exercise results according to various embodiments; and

[0026] Figure 15 This is a flowchart illustrating example operation of a wearable device according to various embodiments. Detailed Implementation

[0027] In the following, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings, enabling those skilled in the art to readily implement the present disclosure. However, the present disclosure may be implemented in several different forms and is not limited to the embodiments described herein. Regarding the description of the drawings, the same or similar reference numerals may be used for the same or similar components. Furthermore, for clarity and brevity, descriptions of well-known functions and configurations may be omitted in the drawings and related descriptions.

[0028] Figure 1 This is a block diagram illustrating an electronic device 101 in a network environment 100 according to various embodiments.

[0029] Reference Figure 1 In network environment 100, electronic device 101 can communicate with electronic device 102 via a first network 198 (e.g., a short-range wireless communication network), or with at least one of electronic device 104 or server 108 via a second network 199 (e.g., a long-range wireless communication network). According to an embodiment, electronic device 101 can communicate with electronic device 104 via server 108. According to an embodiment, 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, user identification module (SIM) 196, or antenna module 197. In some embodiments, at least one of the above components (e.g., connection terminal 178) may be omitted from electronic device 101, or one or more other components may be added to electronic device 101. In some embodiments, some of the components described above (e.g., sensor module 176, camera module 180, or antenna module 197) may be implemented as a single integrated component (e.g., display module 160).

[0030] Processor 120 may run software (e.g., program 140) to control at least one other component (e.g., hardware or software component) of electronic device 101 connected to processor 120, and may perform various data processing or calculations. According to one embodiment, as at least part of the data processing or calculation, processor 120 may store commands or data received from another component (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 embodiments, processor 120 may include a main processor 121 (e.g., central processing unit (CPU) or application processor (AP)) or an auxiliary processor 123 (e.g., graphics processing unit (GPU), neural processing unit (NPU), image signal processor (ISP), sensor central processor, or communication processor (CP)) that is operationally independent of or combined with the main processor 121. For example, when electronic device 101 includes a main processor 121 and an auxiliary processor 123, the auxiliary processor 123 may be adapted to consume less power than the main processor 121, or to be dedicated to a specific function. The auxiliary processor 123 may be implemented separately from the main processor 121, or may be implemented as part of the main processor 121.

[0031] When the main processor 121 is inactive (e.g., in sleep) state, the auxiliary processor 123 (rather than the main processor 121) can 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), or when the main processor 121 is active (e.g., running an application), the auxiliary processor 123 can work with the main processor 121 to 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). According to embodiments, the auxiliary processor 123 (e.g., an image signal processor or a communication processor) may be implemented as part of another component (e.g., camera module 180 or communication module 190) functionally associated with the auxiliary processor 123. According to embodiments, the auxiliary processor 123 (e.g., a neural processing unit) may include hardware architecture dedicated to artificial intelligence model processing. Artificial intelligence models can be generated through machine learning. For example, such learning can be performed via electronic device 101 where artificial intelligence is performed or via a separate server (e.g., server 108). The learning algorithm may include, but is not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning. The artificial intelligence model may include multiple layers of artificial neural networks. The 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), or a deep Q-network, or a combination of two or more thereof, but is not limited thereto. Additionally or optionally, the artificial intelligence model may include software structures in addition to hardware structures.

[0032] Memory 130 may store various data used by at least one component of electronic device 101 (e.g., processor 120 or sensor module 176). The various data may include, for example, software (e.g., program 140) and input or output data for commands associated with it. Memory 130 may include volatile memory 132 or non-volatile memory 134.

[0033] The program 140 may be stored as software in the memory 130, and the program 140 may include, for example, an operating system (OS) 142, middleware 144, or application 146.

[0034] The input module 150 can receive commands or data from outside the electronic device 101 (e.g., a user) that will be used by other components of the electronic device 101 (e.g., processor 120). The input module 150 may include, for example, a microphone, mouse, keyboard, keys (e.g., buttons), or digital pen (e.g., stylus).

[0035] The sound output module 155 can output sound signals to the outside of the electronic device 101. The sound output module 155 may include, for example, a speaker or a receiver. The speaker can be used for general purposes such as playing multimedia or playing records. The receiver can be used to receive incoming calls. According to an embodiment, the receiver can be implemented separately from the speaker or as part of the speaker.

[0036] Display module 160 can visually provide information to the outside of electronic device 101 (e.g., to a user). Display device 160 may include, for example, a display, a holographic device, or a projector, and control circuitry for controlling a respective one of the display, holographic device, and projector. According to an embodiment, display module 160 may include a touch sensor adapted to detect touch or a pressure sensor adapted to measure the intensity of the force caused by touch.

[0037] The audio module 170 can convert sound into electrical signals and vice versa. According to an embodiment, the audio module 170 can obtain sound via the input module 150, or output sound via the sound output module 155 or headphones of an external electronic device (e.g., electronic device 102) that is directly (e.g., wired) or wirelessly connected to the electronic device 101.

[0038] Sensor module 176 can detect the operating state of electronic device 101 (e.g., power or temperature) or the environmental state outside electronic device 101 (e.g., user state), and then generate an electrical signal or data value corresponding to the detected state. According to embodiments, sensor module 176 may include, for example, a gesture sensor, gyroscope sensor, atmospheric pressure sensor, magnetic sensor, accelerometer, grip sensor, proximity sensor, color sensor, infrared (IR) sensor, biometric sensor, temperature sensor, humidity sensor, or illuminance sensor.

[0039] Interface 177 may support one or more specific protocols used to enable electronic device 101 to connect directly (e.g., wired) or wirelessly to external electronic devices (e.g., electronic device 102). According to embodiments, interface 177 may include, for example, a High Definition Multimedia Interface (HDMI), a Universal Serial Bus (USB) interface, a Secure Digital Card (SD) interface, or an audio interface.

[0040] Connection 178 may include a connector, through which electronic device 101 may be physically connected to an external electronic device (e.g., electronic device 102). According to embodiments, connection 178 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0041] The haptic module 179 can convert electrical signals into mechanical stimuli (e.g., vibration or motion) or electrical stimuli that can be recognized by a user through his touch or kinesthesia. According to an embodiment, the haptic module 179 may include, for example, a motor, a piezoelectric element, or an electrical stimulator.

[0042] Camera module 180 can capture still or moving images. According to an embodiment, camera module 180 may include one or more lenses, an image sensor, an image signal processor, or a flash.

[0043] The power management module 188 manages the power supply to the electronic device 101. According to an embodiment, the power management module 188 may be implemented as at least part of, for example, a power management integrated circuit (PMIC).

[0044] Battery 189 can power at least one component of electronic device 101. According to an embodiment, battery 189 may include, for example, a non-rechargeable primary battery, a rechargeable rechargeable battery, or a fuel cell.

[0045] Communication module 190 can support the establishment of a direct (e.g., wired) or wireless communication channel between electronic device 101 and external electronic devices (e.g., electronic device 102, electronic device 104, or server 108), and perform communication via the established communication channel. Communication module 190 may include one or more communication processors capable of operating independently of processor 120 (e.g., application processor (AP)) and support direct (e.g., wired) or wireless communication. According to embodiments, communication module 190 may include wireless communication module 192 (e.g., cellular communication module, short-range wireless communication module, or Global Navigation Satellite System (GNSS) communication module) or wired communication module 194 (e.g., local area network (LAN) communication module or power line communication (PLC) module). One of these communication modules can communicate with an external electronic device via a first network 198 (e.g., a short-range communication network such as Bluetooth, Wi-Fi Direct, or Infrared Data Association (IrDA)) or a second network 199 (e.g., a long-range communication network such as a traditional cellular network, 5G network, next-generation communication network, the Internet, or a computer network (e.g., a LAN or a wide area network (WAN))). These various types of communication modules can be implemented as a single component (e.g., a single chip) or as multiple components separate from each other (e.g., multiple chips). The wireless communication module 192 can identify and verify the electronic device 101 in the communication network (such as the first network 198 or the second network 199) using user information (e.g., the International Mobile Subscriber Identity (IMSI)) stored in the user identification module 196.

[0046] Wireless communication module 192 can support 5G networks following 4G networks and next-generation communication technologies (such as new radio (NR) access technologies). NR access technologies can support enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), or ultra-reliable low-latency communication (URLLC). Wireless communication module 192 can support high-frequency bands (e.g., millimeter-wave bands) to achieve, for example, high data transmission rates. Wireless communication module 192 can support various technologies used to ensure performance in high-frequency bands, such as, for example, beamforming, massive MIMO, full-dimensional MIMO (FD-MIMO), array antennas, analog beamforming, or massive antennas. Wireless communication module 192 can support various requirements specified in electronic device 101, external electronic devices (e.g., electronic device 104), or network systems (e.g., second network 199). According to an embodiment, the wireless communication module 192 may support peak data rates (e.g., 20 Gbps or greater) for implementing eMBB, lost coverage (e.g., 164 dB or less) for implementing mMTC, or U-plane latency (e.g., 0.5 ms or less for each of the downlink (DL) and uplink (UL), or 1 ms or less round trip) for implementing URLLC.

[0047] Antenna module 197 can transmit or receive signals or power to or from the exterior of electronic device 101 (e.g., external electronic device). According to an embodiment, antenna module 197 may include an antenna comprising a radiating element formed of a conductive material or conductive pattern formed in or on a substrate (e.g., a printed circuit board (PCB)). According to an embodiment, antenna module 197 may include multiple antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication scheme used in a communication network (such as a first network 198 or a second network 199) can be selected from the multiple antennas by, for example, communication module 190 (e.g., wireless communication module 192). Signals or power can then be transmitted or received between communication module 190 and the external electronic device via the selected at least one antenna. According to an embodiment, additional components besides the radiating element (e.g., a radio frequency integrated circuit (RFIC)) may be additionally incorporated into antenna module 197.

[0048] According to various embodiments, antenna module 197 may form a millimeter-wave antenna module. According to embodiments, the millimeter-wave antenna module may include a printed circuit board, a radio frequency integrated circuit (RFIC), and multiple antennas (e.g., an array antenna), wherein the RFIC is disposed on or adjacent to a first surface (e.g., a bottom surface) of the printed circuit board and is capable of supporting a specified high-frequency band (e.g., a millimeter-wave band), and the multiple antennas are disposed on or adjacent to a second surface (e.g., a top surface or a side surface) of the printed circuit board and are capable of transmitting or receiving signals in the specified high-frequency band.

[0049] At least some of the aforementioned components can be interconnected and communicate signals (e.g., commands or data) between them via an inter-peripheral communication scheme (e.g., bus, general purpose input / output (GPIO), serial peripheral interface (SPI), or mobile industrial processor interface (MIPI)).

[0050] According to an embodiment, commands or data can be sent or received between electronic device 101 and external electronic device 104 via server 108 connected to a second network 199. Each of electronic device 102 or electronic device 104 can be a device of the same type as electronic device 101, or a device of a different type. According to an embodiment, all or some operations that would be performed on electronic device 101 can be performed on one or more of external electronic devices 102, external electronic devices 104, or server 108. For example, if electronic device 101 is required to automatically perform a function or service, or is required to perform a function or service in response to a request from a user or another device, electronic device 101 may request the one or more external electronic devices to perform at least a portion of the function or service, instead of running the function or service, or electronic device 101 may request the one or more external electronic devices to perform at least a portion of the function or service in addition to running the function or service. Upon receiving the request, one or more external electronic devices may perform at least a portion of the requested function or service, or perform additional functions or services related to the request, and transmit the result of the execution to electronic device 101. Electronic device 101 may provide the result as at least a partial response to the request, with or without further processing of the result. For this purpose, technologies such as cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing may be used. Electronic device 101 may use, for example, distributed computing or mobile edge computing to provide ultra-low latency services. In another embodiment, external electronic device 104 may include an Internet of Things (IoT) device. Server 108 may be an intelligent server using machine learning and / or neural networks. According to embodiments, external electronic device 104 or server 108 may be included in a second network 199. Electronic device 101 may be applied to intelligent services based on 5G communication technology or IoT-related technologies (e.g., smart homes, smart cities, smart cars, or healthcare).

[0051] Figure 2a and Figure 2b This is a perspective view showing an example electronic device according to various embodiments.

[0052] Reference Figure 2a and Figure 2b According to an embodiment, electronic device 200 (e.g., Figure 1The electronic device 101 may include a housing 210 and mounting members 250 and 260. The housing 210 includes a first surface (or front surface) 210A, a second surface (or rear surface) 210B, and a side surface 210C surrounding the space between the first surface 210A and the second surface 210B. The mounting members 250 and 260 are directly or indirectly connected to at least a portion of the housing 210 and detachably couple the electronic device 200 to a part of the user's body (e.g., wrist, ankle, etc.). In another embodiment (not shown), the housing may refer to a structure formed... Figure 2a and Figure 2b The structure comprises some of the first surface 210A, the second surface 210B, and the side surface 210C. According to an embodiment, at least a portion of the first surface 210A may be formed of a substantially transparent front panel 201 (e.g., a glass or polymer panel including various coatings). The second surface 210B may be formed of a substantially opaque rear panel 207. For example, the rear panel 207 may be formed of coated or colored glass, ceramic, polymer, metal (e.g., aluminum, stainless steel (STS), or magnesium), or a combination of at least two materials. The side surface 210C may be formed of a side frame structure (or “side member”) 206, which is directly or indirectly coupled to the front panel 201 and the rear panel 207 and comprises metal and / or polymer. In some embodiments, the rear panel 207 and the side frame structure 206 may be integrally formed and may comprise the same material (e.g., a metallic material such as aluminum). Binding members 250 and 260 may be formed of various materials and shapes. Integrated unit links and multiple unit links can be formed to flow with each other by woven fabric, leather, rubber, polyurethane, metal, ceramic or a combination of at least two materials.

[0053] According to an embodiment, the electronic device 200 may include a display 220 (see reference 220). Figure 3 The electronic device 200 may include at least one of the following components: audio modules 205 and 208, sensor module 211 including at least one sensor, key input devices 202, 203 and 204, and connector hole 209. In some embodiments, the electronic device 200 may omit at least one of the components (e.g., keyboard input devices 202, 203 and 204, connector hole 209, or sensor module 211), or may additionally include another component.

[0054] Display 220 may be visually exposed, for example, through a large portion of front panel 201. The shape of display 220 may correspond to the shape of front panel 201 and may have various shapes, such as circular, elliptical, or polygonal. Display 220 may be coupled to touch detection circuitry, a pressure sensor capable of measuring the intensity (pressure) of touch, and / or a fingerprint sensor, or may be disposed adjacent to touch detection circuitry, a pressure sensor capable of measuring the intensity (pressure) of touch, and / or a fingerprint sensor.

[0055] Audio modules 205 and 208 may include a microphone hole 205 and a speaker hole 208. The microphone hole 205 may internally house a microphone for receiving external sound, and in some embodiments, multiple microphones may be provided to detect the direction of sound. The speaker hole 208 may serve as an external speaker and a receiver for making calls. In some embodiments, the speaker hole 208 and microphone hole 205 may be implemented as a single hole, or a speaker may be included without a speaker hole 208 (e.g., a piezoelectric speaker).

[0056] Sensor module 211 can generate electrical signals or data values ​​corresponding to the internal operating state or external environmental state of electronic device 200. Sensor module 211 may include, for example, a biometric sensor module 211 (e.g., an HRM sensor) disposed on the second surface 210B of housing 210. Electronic device 200 may also include at least one of the sensor modules not shown, such as a gesture sensor, gyroscope sensor, atmospheric pressure sensor, magnetic sensor, accelerometer, grip sensor, color sensor, infrared (IR) sensor, biometric sensor, temperature sensor, humidity sensor, or illuminance sensor.

[0057] Sensor module 211 may include electrode regions 213 and 214 forming part of the surface of electronic device 200, and a biosignal detection circuit (not shown) directly or indirectly electrically connected to electrode regions 213 and 214. For example, electrode regions 213 and 214 may include a first electrode region 213 and a second electrode region 214 disposed on a second surface 210B of housing 210. Sensor module 211 may be configured such that electrode regions 213 and 214 receive electrical signals from a part of the user's body, and the biosignal detection circuit detects the user's bio-information based on the electrical signals.

[0058] Key input devices 202, 203, and 204 may include a scroll wheel key 202 disposed on a first surface 210A of housing 210 and rotatable in at least one direction, and / or side key buttons 203 and 204 disposed on a side surface 210C of housing 210. The scroll wheel key may have a shape corresponding to the shape of the front panel 201. In another embodiment, electronic device 200 may not include some or all of the aforementioned key input devices 202, 203, and 204, and the excluded key input devices 202, 203, and 204 may be implemented in other forms such as soft keys on display 220. Connector hole 209 may accommodate a connector (e.g., a USB connector) for transmitting and / or receiving power and / or data to and from an external electronic device, and includes another connector hole (not shown) capable of accommodating a connector for transmitting and receiving audio signals to and from an external electronic device. For example, the electronic device 200 may also include a connector cover (not shown) that covers at least a portion of the connector hole 209 and prevents external foreign matter from flowing into the connector hole.

[0059] Binding members 250 and 260 can be detachably attached to at least a portion of housing 210 using locking members 251 and 261. Binding members 250 and 260 may include one or more of a retaining member 252, a retaining member fastening hole 253, a guide member 254, and a retaining ring 255.

[0060] The fixing member 252 can be configured to secure the housing 210 and the binding members 250 and 260 to a part of the user's body (e.g., wrist, ankle, etc.). Corresponding to the fixing member 252, the fixing member fastening hole 253 can secure the housing 210 and the binding members 250 and 260 to the part of the user's body. The guide member 254 can be configured to restrict the range of movement of the fixing member 252 when it is fastened to the fixing member fastening hole 253, and thus the binding members 250 and 260 can be tightly coupled to the part of the user's body. With the fixing member 252 and the fixing member fastening hole 253 fastened, the retaining ring 255 can restrict the range of movement of the binding members 250 and 260.

[0061] Figure 3 This is an exploded perspective view showing an example electronic device according to various embodiments.

[0062] Reference Figure 3 Electronic device 300 (e.g., Figure 1 Electronic device 101 or Figures 2a to 2bThe electronic device 300 may include a side bezel structure 310, a wheel key 320, a front panel 201, a display 220, a first antenna 350, a second antenna 355, a support member 360 (e.g., a bracket), a battery 370, a printed circuit board 380, a sealing member 390, a rear panel 393, and bonding members 395 and 397. At least one component of the electronic device 300 may be coupled with... Figure 1 and / or Figures 2a to 2b At least one component of the electronic device is identical or similar, and its repeated description will be omitted. The support member 360 may be disposed within the electronic device 300 to be directly or indirectly connected to the side bezel structure 310, or may be integrally formed with the side bezel structure 310. The support member 360 may be formed of, for example, a metallic material and / or a non-metallic (e.g., polymer) material. In the support member 360, the display 220 may be directly or indirectly coupled to one surface, and the printed circuit board 380 may be coupled to another surface. A processor, memory, and / or interface may be mounted on the printed circuit board 380. The processor may include one or more of, for example, a central processing unit, a graphics processing unit (GPU), an application processor, a sensor processor, or a communication processor.

[0063] The memory may include, for example, volatile or non-volatile memory. The interface may include, for example, a High Definition Multimedia Interface (HDMI), a Universal Serial Bus (USB) interface, an SD card interface, and / or an audio interface. For example, the interface can electrically or physically connect the electronic device 300 to an external electronic device and may include a USB connector, an SD card / MMC connector, or an audio connector.

[0064] Battery 370 is a device for supplying power to at least one component of electronic device 200 / 300, and may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell. At least a portion of battery 370 may be disposed on a plane substantially the same as, for example, a printed circuit board 380. Battery 370 may be integrally disposed within electronic device 200 / 300, or may be detachably disposed from electronic device 200 / 300.

[0065] The first antenna 350 may be disposed between the display 220 and the support member 360. The first antenna 350 may include, for example, a near-field communication (NFC) antenna, a wireless charging antenna, and / or a magnetically secure transmission (MST) antenna. For example, the first antenna 350 may perform short-range communication with external devices, wirelessly send and receive power required for charging, and may transmit short-range communication signals or self-based signals including payment data. In another embodiment, the antenna structure may be formed by a portion or combination of the side bezel structure 310 and / or the support member 360.

[0066] The second antenna 355 may be disposed between the printed circuit board 380 and the rear panel 393. For example, the second antenna 355 may include a near-field communication (NFC) antenna, a wireless charging antenna, and / or a magnetically secure transmission (MST) antenna. For example, the second antenna 355 may perform short-range communication with external devices, wirelessly send and receive power required for charging, and may transmit short-range communication signals or self-based signals including payment data. In another embodiment, the antenna structure may be formed by a portion of the side frame structure 310 and / or the rear panel 393, or a combination thereof.

[0067] The sealing member 390 may be located between the side frame structure 310 and the rear panel 393. The sealing member 390 may be configured to prevent moisture and foreign matter from flowing into the space surrounded by the side frame structure 310 and the rear panel 393 from the outside.

[0068] According to embodiments, wearable devices (e.g., Figure 1 Electronic device 101 Figure 2a and Figure 2b The electronic device 200 shown, or Figure 3 The electronic device 300 shown can operate when worn by a user. For example, the wearable device can be worn on a part of the user's body (e.g., wrist, finger, or face). According to embodiments, the wearable device can be used to provide information about the user's physical activity. For example, the wearable device can provide information about the user's exercise (or workout). Based on the user's workout based on a specified action, the wearable device can provide the user with the number of times the specified action was performed. Since each user's workout performance, posture, and / or body characteristics are different, the wearable device can set different thresholds for identifying the number of times each user performed the specified action. In this disclosure, technical features for personalizing the thresholds for identifying the number of times a specified action was performed will be described in more detail.

[0069] The operation of a wearable device according to various embodiments can be described below. The wearable device described below (e.g., wearable device 400) may correspond to Figure 1 Electronic device 101 Figure 2a and Figure 2b Electronic devices 200 and / or Figure 3 Electronic device 300.

[0070] Figure 4a This is an illustration showing examples of wearable devices for recognizing various exercises of a user, according to various embodiments.

[0071] Figure 4b This is a graph illustrating examples of multiple time periods for performing a specified action according to various embodiments.

[0072] refer to Figure 4a The wearable device 400 can operate when worn by a user. For example, the wearable device 400 can correspond to... Figure 2a and Figure 2b Electronic devices 200 and / or Figure 3 Electronic device 300. For example, wearable device 400 can operate when worn on a user's wrist.

[0073] Figure 4a An example of wearable device 400 being worn on a user's wrist is shown, but this disclosure is not limited thereto. Wearable device 400 may operate when worn on a part of the user's body. For example, wearable device 400 may be worn on one of the user's head, the user's finger, the user's neck, the user's ankle, and the user's ear (or ear canal).

[0074] According to an embodiment, the wearable device 400 can recognize various exercises. For example, when the wearable device 400 is worn on a user's wrist, the wearable device 400 can recognize that one of the following exercises is performed: squat exercise 401, rowing machine exercise 402, and dumbbell press exercise 403. Figure 4a The various exercises shown are examples, and this disclosure is not limited thereto.

[0075] According to embodiments, various exercises can be performed by repeatedly executing specified movements. For example, in squat exercise 401, the user can repeatedly perform the movement of bending and straightening the knee. For example, in rowing machine exercise 402, the user can repeatedly perform the movement of pulling and releasing the rowing machine cable. For example, in dumbbell press exercise 403, the user can repeatedly perform the movement of raising and lowering dumbbells using the arms.

[0076] According to an embodiment, the wearable device 400 can identify the number of times a specified action is performed. For example, the wearable device 400 can use at least one sensor to identify the number of times a specified action is performed. For example, in a squat exercise 401, the movement of bending and straightening the knee (hereinafter referred to as a squat exercise) can be counted as 1 time. For example, in a rowing machine exercise 402, the movement of pulling and releasing the rowing machine cable can be counted as 1 time. For example, in a dumbbell press exercise 403, the movement of raising and lowering the dumbbells can be counted as 1 time.

[0077] For example, multiple groups can be set up based on repetition of a specified value for a specified action. For example, a specified action repeated for a specified value can form a group. Wearable device 400 can identify one of the multiple groups based on recognizing that the number of times a specified action is performed corresponds to a specified value. As an example, in squat exercise 401, squatting exercises repeated for a specified value can form a group.

[0078] For example, the specified value can be set by the user. The user can use the wearable device 400 to set the repetitions of a specified movement to form a set. For example, in a squat exercise 401, a set can be set to perform 15 squats. The wearable device 400 can identify that a set has been performed based on recognizing that the user has performed 15 squats.

[0079] Reference Figure 4b The first set of exercises can be performed during the time period 461 between time t1 and time t2. For example, the wearable device 400 can recognize that a user's workout based on a specified action begins at time t1. At time t2, the wearable device 400 can recognize that the number of times the specified action is performed corresponds to a specified value. The wearable device 400 can recognize the completion of the first set based on recognizing that the number of times the specified action is performed corresponds to the specified value. For example, the wearable device 400 can provide the user with a notification indicating the completion of the first set. The notification indicating the completion of the first set can be provided based on at least one of screen changes, sound, and / or vibration.

[0080] According to an embodiment, a group can be set based on a specified time period (e.g., 3 minutes) rather than the number of times a specified action is performed. For example, the time period 461 for performing the first group (or the time period 462 for performing the second group) can be set to a specified time period (e.g., 3 minutes).

[0081] The time period 471 between time t2 and time t3 can be set as a rest period between the first and second groups. For example, rest periods can be formed between consecutive groups. The rest period can be set by the user or predetermined. According to an embodiment, the rest period can be maintained until the user's state is identified as a specified state. For example, the rest period can be maintained until the user's heart rate is identified as a specified heart rate. For example, the wearable device 400 can provide the user with a notification indicating that the rest period has ended at time t3. The notification indicating that the rest period has ended can be provided based on at least one of screen changes, sound, and / or vibration.

[0082] The second set of actions can be performed during the time interval 462 between time t3 and time t4. At time t4, the wearable device 400 can identify that the number of times the specified action was performed corresponds to a specified value. The wearable device 400 can identify that the second set of actions has been completed based on the identification that the number of times the specified action was performed corresponds to the specified value. For example, the wearable device 400 can provide a notification to the user indicating that the second set of actions has been completed. The notification indicating that the second set of actions has been completed can be provided based on at least one of screen changes, sound, and / or vibration.

[0083] The time interval 472 between time t4 and time t5 can be set as the rest time between the second and third groups.

[0084] As described above, when a user exercises in multiple sets, the wearable device 400 can provide information about the user's exercise. For example, the wearable device 400 can count the number of times a specified action is performed and display the number of times the specified action is performed on a display of the wearable device 400.

[0085] Figure 5 This is a block diagram illustrating example configurations of wearable devices according to various embodiments.

[0086] refer to Figure 5 The wearable device 400 can be implemented in various forms. For example, the wearable device 400 can be implemented in various forms that can be worn by a user, such as a smartwatch, smart bracelet, smart ring, wireless headphones, or smart glasses. For example, the wearable device 400 can correspond to... Figure 1 Electronic device 101 Figure 2a and Figure 2b Electronic devices 200 and / or Figure 3 Electronic device 300.

[0087] According to an embodiment, the wearable device 400 can operate in association with an electronic device connected to the wearable device 400. For example, at least a portion of the operation of the wearable device 400 described below can be performed in the electronic device connected to the wearable device 400.

[0088] According to an embodiment, the wearable device 400 may include a processor (e.g., including processing circuitry) 410, a communication circuitry 420, a sensor 430, a memory 440, and / or a display 450. According to an embodiment, the wearable device 400 may include at least one of the processor 410, communication circuitry 420, sensor 430, memory 440, and display 450. For example, according to an embodiment, at least a portion of the processor 410, communication circuitry 420, sensor 430, memory 440, and display 450 may be omitted.

[0089] According to an embodiment, the processor 410 may correspond to Figure 1 Processor 120. Processor 410 may be operatively coupled or connected to communication circuitry 420, sensor 430, memory 440, and display 450. For example, operative coupling of processor 410 to another component may mean that processor 410 is able to control another component. Processor 410 may control communication circuitry 420, sensor 430, memory 440, and display 450. For example, processor 410 may determine the operating time of sensor 430. Processor 410 may control the operation of sensor 430. Processor 410 may activate or deactivate sensor 430. Processor 410 may process information obtained from sensor 430.

[0090] According to an embodiment, processor 410 may be configured with at least one processor. Processor 410 may include at least one processor. According to an embodiment, processor 410 may include hardware components for processing data based on one or more instructions. For example, the hardware components for processing data may include an arithmetic and logic unit (ALU), a field-programmable gate array (FPGA), and / or a central processing unit (CPU). Processor 410 may include various processing circuitry and / or multiple processors. For example, as used herein, including the claims, the term "processor" may include various processing circuitry, including at least one processor, wherein one or more of the at least one processor may be configured individually and / or collectively in a distributed manner to perform the various functions described herein. As used herein, when "processor," "at least one processor," and "one or more processors" are described as being configured to perform a number of functions, these terms cover, for example, a case where one processor performs some of the functions and another processor performs other functions, and a case where a single processor can perform all of the functions. Additionally, at least one processor may include, for example, a combination of processors performing various described / disclosed functions in a distributed manner. At least one processor may execute program instructions to implement or perform various functions.

[0091] According to an embodiment, the wearable device 400 may include a communication circuit 420. For example, the communication circuit 420 may correspond to... Figure 1 At least a portion of the communication module 190.

[0092] For example, communication circuitry 420 can be used with various wireless access technologies (RATs). For example, communication circuitry 420 can be used to perform Bluetooth communication, wireless local area network (WLAN) communication, or ultra-wideband (UWB) communication. For example, communication circuitry 420 can be used to perform cellular communication.

[0093] For example, processor 410 can communicate with external electronic devices (e.g., communication circuit 420) via communication circuit 420. Figure 1 The processor 410 establishes a connection with the server via electronic device 102, electronic device 104, or server 108. For example, the processor 410 can establish a connection with the server via communication circuit 420.

[0094] According to an embodiment, the wearable device 400 may include a sensor 430. The sensor 430 can be used to acquire various external information. For example, the sensor 430 can be used to acquire data about the user's body. As an example, the sensor 430 can be used to acquire data about the user's state, data about the user's movement, and / or data about the user's heart rate. For example, the sensor 430 may correspond to... Figure 1 Sensor module 176.

[0095] According to an embodiment, sensor 430 may include at least one sensor. For example, sensor 430 may include at least one of an accelerometer sensor 431, a gyroscope sensor 432, an HR (heart rate) sensor 433, and / or an atmospheric pressure sensor 434.

[0096] For example, accelerometer 431 can identify (or measure or detect) the acceleration of wearable device 400 in the three directions of the x-axis, y-axis, and z-axis. For example, gyroscope sensor 432 can identify (or measure or detect) the angular velocity of wearable device 400 in the three directions of the x-axis, y-axis, and z-axis. According to an embodiment, wearable device 400 may include an inertial sensor configured with accelerometer 431 and gyroscope sensor 432.

[0097] For example, sensor 430 may include a heart rate (HR) sensor 433 (or a heart rate variability (HRV) sensor). Processor 410 can measure the regularity or variability of heart rate through HR sensor 433. Processor 410 can obtain information about the regularity or variability of heart rate through HR sensor 433.

[0098] For example, atmospheric pressure sensor 434 can identify (or measure or detect) the atmospheric pressure around wearable device 400. Processor 410 can identify the height (or altitude) of wearable device 400 above the ground based on data related to the atmospheric pressure around wearable device 400 identified using atmospheric pressure sensor 434.

[0099] Although not shown, sensor 430 may also include sensors for acquiring (or identifying, measuring or detecting) various data related to the user.

[0100] For example, sensor 430 may include a body temperature sensor. Processor 410 can measure the skin temperature of a part of the user's body using the body temperature sensor. Processor 410 can obtain the user's body temperature based on the skin temperature of a part of the user's body.

[0101] For example, sensor 430 may include a photoplethysmography (PPG) sensor. A PPG sensor can be used to measure pulse (or changes in blood volume in a vessel) by recognizing changes in the amount of light-sensitive light based on changes in vessel volume. For example, a PPG sensor can be used to identify information about changes in a user's heart rate, information about user stress based on HRV, information about a user's sleep stage, information about a user's respiratory rate, and information about a user's blood pressure.

[0102] For example, sensor 430 may include a blood glucose sensor. Processor 410 can identify a user's blood glucose level by recognizing (or measuring) the current generated by the electrochemical reaction with blood glucose in the blood.

[0103] According to an embodiment, the wearable device 400 may include a memory 440. The memory 440 may be used to store information or data. For example, the memory 440 may be used to store data obtained from a user. For example, the memory 440 may correspond to... Figure 1 The memory 130. For example, the memory 440 may be one or more volatile memory cells. For example, the memory 440 may be one or more non-volatile memory cells. For example, the memory 440 may be another type of computer-readable medium, such as a disk or optical disk. For example, the memory 440 may store data obtained based on operations performed in the processor 410 (e.g., algorithm execution operations). For example, the memory 440 may store data obtained from the sensor 430 (e.g., data about the user's heart rate).

[0104] For example, memory 440 may include a first memory and a second memory. The first memory may store first information about the exercise. The first information about the exercise may include at least one threshold for counting the number of times the user exercises. The second memory may store instructions. When executed by processor 410, the instructions may cause wearable device 400 to perform a specified action.

[0105] For example, display 450 can be used to display various screens. Display 450 can be controlled by processor 410, which includes circuitry such as a graphics processing unit (GPU), and output visual information to the user. Display 450 can be used to output content, data, or signals through the screen. For example, display 450 can correspond to... Figure 1 The display module 160.

[0106] Although not shown, wearable device 400 may also include a speaker, microphone, and / or buttons. For example, processor 410 may use a speaker to provide notifications to the user. Notifications may include notifications for the start of a group, notifications for the completion (or end) of a group, notifications for the start of a rest period, notifications for the end of a rest period, and / or notifications for the posture of a specified action. For example, processor 410 may use display 450 to display the number of times a specified action has been recognized, and may use at least one of display 450, buttons, and microphone to receive input for changing the number of times. For example, processor 410 may use at least one of display 450, buttons, and microphone to receive input indicating that a group has been completed.

[0107] According to an embodiment, processor 410 may be configured to execute at least one algorithm. For example, at least one algorithm (or at least one instruction) may be stored in memory 440.

[0108] For example, processor 410 can execute an algorithm for identifying the number of times a specified action has been performed. For example, processor 410 can use a specified threshold to identify whether a specified action has been performed. Processor 410 can identify whether a specified action has been performed by comparing a sensor value identified by sensor 430 with the specified threshold.

[0109] For example, processor 410 can execute an algorithm for changing the number of times a specified action is performed. Processor 410 can provide the user with suggested values ​​for modifying (or changing) the number of times a specified action is performed. Processor 410 can set (or update) a personalized threshold for identifying the number of times a specified action is performed based on the user's selection of suggested values.

[0110] For example, processor 410 can execute algorithms for evaluating a user's exercise. Processor 410 can evaluate the posture of each specified movement. For example, processor 410 can identify whether a specified movement (e.g., a squat) is performed with incorrect posture and / or incomplete movement.

[0111] Figure 6a This is a graph illustrating example operations of a wearable device for identifying the number of times a specified action is performed, according to various embodiments.

[0112] Figure 6b This is a graph illustrating example operations of a wearable device for identifying the number of times a specified action is performed, according to various embodiments.

[0113] refer to Figure 6a and Figure 6b The processor 410 of the wearable device 400 can use a first threshold 610 to identify whether a specified action has been performed. For example, when a set of movements formed by the specified action is being performed, the processor 410 of the wearable device 400 can use the sensor 430 to obtain sensor data. The processor 410 can identify the value of the sensor data over time.

[0114] The sensor data values ​​described below may include the acceleration value of the wearable device 400 in a specified direction (e.g., the z-axis), the angular velocity value of the wearable device 400 in a specified direction, and the atmospheric pressure value identified by the wearable device 400. According to embodiments, the sensor data values ​​may be obtained based on a combination (e.g., a sum or average) of at least two of the acceleration value in a specified direction (e.g., one of the x-axis, y-axis, and z-axis), the angular velocity value in a specified direction (e.g., one of the x-axis, y-axis, and z-axis), and the atmospheric pressure value identified by the wearable device 400. However, this disclosure is not limited thereto.

[0115] According to an embodiment, the processor 410 can identify the number of intervals in which the sensor data value is less than or equal to a first threshold 610. The processor 410 can identify the number of intervals in which the sensor data value is less than or equal to the first threshold 610 as the number of times a specified action is performed.

[0116] refer to Figure 6a The processor 410 can identify the number of intervals within time interval 621 where the sensor data value is less than or equal to the first threshold 610. The processor 410 can identify the number of intervals within time interval 621 where the sensor data value is less than or equal to the first threshold 610 as 10. The processor 410 can identify that 10 specified actions were performed within time interval 621.

[0117] For example, processor 410 can identify the number of intervals within time interval 621 where the value of sensor data drops below or rises above the first threshold 610. Processor 410 can identify the number of portions of sensor data in time interval 621 where the value is below or above the first threshold 610 as 10. Processor 410 can identify that a specified action was performed 10 times within time interval 621.

[0118] refer to Figure 6b The processor 410 can identify the number of intervals within time interval 622 where the sensor data value is less than or equal to the first threshold 610. The processor 410 can identify the number of intervals within time interval 622 where the sensor data value is less than or equal to the first threshold 610 as 8. The processor 410 can identify that a specified action was performed 8 times within time interval 622.

[0119] For example, processor 410 can identify the number of intervals within time interval 622 where the sensor data value drops below and rises above the first threshold 610. Processor 410 can identify the number of intervals within time interval 622 where the sensor data value drops below and rises above the first threshold 610 as 8. Processor 410 can identify that a specified action was performed 8 times within time interval 622.

[0120] refer to Figure 6a and Figure 6b When performing a user exercise based on a specified action, processor 410 can identify the number of times the specified action is performed based on sensor data obtained using sensor 430 (e.g., accelerometer 431, gyroscope 432, HR sensor 433, or atmospheric pressure sensor 434). Processor 410 can provide the user with the number of times the specified action is performed. Processor 410 can use display 450 to provide the user with the number of times the specified action is performed.

[0121] For example, the first threshold 610 can be fixed. For example, the first threshold 610 can be set to a fixed value, independent of the user. Since exercise performance, posture, and / or body characteristics are different for each user, the number of times a specified action is performed, identified using the first threshold 610, may be inaccurate depending on the user. For example, when a user's posture is incorrect later in the workout, the number of times a specified action is performed, identified using the first threshold 610, may be less than the number identified by the user. Therefore, the processor 410 can set a personalized threshold such that the number of times a specified action is performed, identified by the processor 410, corresponds to the number identified by the user. An example of the operation of the wearable device 400 (or processor 410) for setting a second threshold as a personalized threshold will be described in more detail below.

[0122] Figure 7a This is a flowchart illustrating example operations of a wearable device according to various embodiments. In the following examples, each operation may be performed sequentially, but not necessarily sequentially. For example, the order of each operation can be changed, and at least two operations can be performed in parallel.

[0123] refer to Figure 7a In operation 710, the processor 410 can recognize the start of a user workout based on a specified movement. For example, the user's workout may include squat exercises (e.g., Figure 4a Squat exercises 401), rowing machine exercises (for example, Figure 4a Rowing machine exercises 402), dumbbell press exercises (for example, Figure 4a Dumbbell press exercises (403) and / or arm curl exercises.

[0124] For example, processor 410 can identify the number of sets of exercises performed by the user, the number of specified movements included in each set, and / or the rest time between consecutive sets. The number of sets of exercises performed by the user, the number of specified movements included in each set, and / or the rest time between consecutive sets can be set by the user or are stored in memory 440.

[0125] For example, memory 440 may store first information about the exercise. Memory 440 may store the first information, which includes at least one threshold (e.g., a first threshold or a second threshold) for identifying the number of times a specified action is performed.

[0126] For example, processor 410 can recognize the start of a user's workout based on user input. For example, processor 410 can recognize user input indicating the start of a workout. Processor 410 can recognize the start of a user's workout based on user input.

[0127] For example, processor 410 can recognize user input for setting the type of exercise (e.g., squat, rowing machine, dumbbell press, or bicep curl) and recognize the start of the user's workout based on the execution of a specified movement according to the set exercise type.

[0128] According to an embodiment, processor 410 may obtain second information about the user's exercise movements based on recognizing the start of the user's exercise. For example, the second information about a specified action (or the user's exercise movements) may include sensor values ​​(or sensor data) obtained by sensor 430.

[0129] In operation 720, processor 410 may obtain a first value indicating the number of times a specified action for the second information is performed, based on a first threshold associated with the first information. For example, processor 410 may use the first threshold to obtain the first value indicating the number of times a specified action is performed. For example, processor 410 may use the first threshold to obtain the first value indicating the number of times a specified action is performed, based on the specified action being performed.

[0130] For example, a first threshold can be set based on at least one of the user's height, weight, body type, age, and / or gender. For example, the first threshold can be a fixed value. For example, the first threshold can be referred to as a default threshold.

[0131] While executing a set of actions, the processor 410 can use a first threshold to obtain a first value indicating the number of times a specified action has been performed. The processor 410 can also identify the number of time periods in which the value of sensor data identified by the sensor 430 is less than or equal to the first threshold as a first value. According to an embodiment, based on the type of sensor data value and / or the type of exercise, the processor 410 can identify the number of time periods in which the value of sensor data identified by the sensor 430 is greater than the first threshold as a first value.

[0132] In operation 730, processor 410 may obtain a second value indicating the number of times a specified action for the second information is performed, based on a second threshold associated with the first information.

[0133] According to an embodiment, the processor 410 may determine a second threshold for identifying the number of times a specified action is performed as a second value different from the first value. For example, based on the first value corresponding to the specified value, the processor 410 may determine a second threshold for identifying the number of times a specified action is performed as a second value different from the first value. The second threshold may be related to second information.

[0134] According to an embodiment, processor 410 can identify that a first value corresponds to a specified value. For example, multiple groups can be set based on the repetition of a specified value according to a specified action. For example, a specified action repeated for a specified value can form a group. Processor 410 can identify that the first group of multiple groups has been executed based on the first value corresponding to the specified value. As an example, the specified value can be changed based on user input. As an example, the specified value can be changed based on the type of exercise and / or exercise goal (e.g., muscle hypertrophy, fat reduction, or increased strength).

[0135] For example, processor 410 may provide a notification to the user indicating that the setup is complete based on a first value corresponding to a specified value. For example, the notification may be provided based on at least one of screen changes, sound, and / or vibration.

[0136] According to an embodiment, processor 410 may determine a second threshold, which is different from the first value, as a second threshold used to identify the number of times a specified action is performed. For example, when using a second threshold different from the first threshold to identify the number of times a specified action is performed, processor 410 may identify the value indicating the number of times the specified action is performed as the second value. Processor 410 may determine the second threshold, which is different from the first threshold, as the second value. For example, the second threshold may be a value changed by the user during the user's exercise. For example, the second threshold may be referred to as a personalized threshold.

[0137] For example, processor 410 can determine a second threshold within a specified range for identifying a value indicating the number of times a specified action is performed as a second value. The specified range can be set based on a first reference value and a second reference value. The second reference value can be set to be greater than the first reference value. Processor 410 can determine the second threshold within the specified range to prevent and / or reduce the occurrence of the second threshold being set too low or too high. When the second threshold is determined within the specified range, the probability of incorrectly identifying the specified action may be lower. For example, processor 410 can determine the second threshold as the first reference value based on the second threshold for identifying a value indicating the number of times a specified action is performed as a second value being identified as less than the first reference value. As an example, processor 410 can determine the second threshold as the second reference value based on the second threshold for identifying a value indicating the number of times a specified action is performed as a second value being identified as greater than the second reference value. Specific examples of determining the second threshold within a specified range are provided below. Figure 9 This will be discussed later.

[0138] In operation 740, processor 410 may display a first value and a second value. For example, processor 410 may display the first value and the second value on display 450. For example, processor 410 may display a screen for inputting one of the first value and the second value. For example, based on determining a second threshold, processor 410 may display a screen for inputting one of the first value and the second value.

[0139] For example, based on determining a second threshold, processor 410 can display a screen including a first visual object representing a first value and a second visual object representing a second value. For example, input for one of the first and second values ​​can include input for one of the first and second visual objects. For example, processor 410 can identify input for one of the first and second values ​​based on input for one of the first and second visual objects. For example, the features of the first visual object and the features of the second visual object can be set differently. As an example, the second visual object can be highlighted compared to the first visual object on the screen. The size of the second visual object can be set to be larger than the size of the first visual object. As an example, the color of the first visual object can be set to be different from the color of the second visual object. For example, reference will be made below. Figure 10 A more detailed description of an example of a screen that includes a first visual object and a second visual object.

[0140] According to an embodiment, based on the input identifying a first value, the processor 410 can maintain a threshold for identifying the value indicating the number of times a specified action is performed (or the number of times a specified action is performed) at the first threshold. Based on the input identifying a second value, the processor 410 can add a second threshold to the threshold for identifying the value indicating the number of times a specified action is performed (or the number of times a specified action is performed). The processor 410 can use both the first and second thresholds to identify the value indicating the number of times a specified action is performed (or the number of times a specified action is performed). As an example, the processor 410 can use the second threshold to identify the value indicating the number of times a specified action is performed as a third value, and use the first threshold to identify the value indicating the number of times a specified action is performed as a fourth value. The processor 410 can display the third value via the display 450. When the third value is displayed via the display 450, the processor 410 can store the fourth value in the memory 440.

[0141] According to an embodiment, based on the input identifying a first value, the processor 410 can maintain the threshold used to identify the number of times a specified action is performed as the first threshold. Based on the input identifying a second value, the processor 410 can change the threshold used to identify the number of times a specified action is performed to the second threshold.

[0142] For example, processor 410 can display a screen for inputting one of a first value and a second value based on the completion of the first group of multiple groups. Based on the identification of input for the first value, processor 410 can use a first threshold in a second group following the first group to identify a third value indicating the number of times a specified action has been performed. Based on the identification of input for the second value, processor 410 can use a second threshold to identify a third value indicating the number of times a specified action in the second group of actions following the first group of actions. Processor 410 can display a screen representing the third value while performing the specified action in the second group. Each time the specified action in the second group is performed, processor 410 can increment the third value. When the specified action in the second group is performed, processor 410 can use the first threshold to identify a fourth value indicating the number of times the specified action in the second group has been performed. Processor 410 can store the fourth value in memory 440.

[0143] Figure 7b This is a flowchart illustrating example operations of a wearable device according to various embodiments. In the following examples, each operation may be performed sequentially, but not necessarily sequentially. For example, the order of each operation can be changed, and at least two operations can be performed in parallel.

[0144] refer to Figure 7b It can be executed Figure 7aOperations 751 to 756 are executed after operation 740. For example, when the user executes the first group of multiple groups, the processor 410 of the wearable device 400 can execute... Figure 7a Operations 710 to 740. When executing the second group, which is the next group after the first group, processor 410 may execute operations 751 to 756. However, this disclosure is not limited thereto. Operations 751 to 756 can be performed independently of... Figure 7a The operation is executed.

[0145] In operation 751, processor 410 may use the second threshold to obtain a third value indicating the number of times a specified action has been performed. For example, based on the specified action being performed, processor 410 may use the second threshold to obtain a third value indicating the number of times a specified action has been performed.

[0146] When executing a set of actions, processor 410 can use a second threshold to obtain a third value indicating the number of times a specified action has been performed. Processor 410 can also identify the number of time periods in which the values ​​of sensor data identified by sensor 430 are less than or equal to the second threshold as the third value. According to an embodiment, processor 410 can identify the number of time periods in which the values ​​of sensor data identified by sensor 430 are greater than the second threshold as the third value, based on the type of sensor values ​​and / or the type of exercise.

[0147] According to an embodiment, when a third value indicating the number of times a specified action has been performed is obtained using a second threshold, the processor 410 can use a first threshold to obtain a fourth value indicating the number of times the specified action has been performed. For example, when the user performs the specified action, the processor 410 may not provide the fourth value to the user. The processor 410 may provide the third value to the user and store the fourth value in the memory 440. When displaying the exercise results after the exercise is completed, the processor 410 may provide the fourth value to the user. However, this disclosure is not limited thereto. According to an embodiment, the processor 410 may provide the third value and the fourth value to the user together. The operation of providing a value (e.g., the third value or the fourth value) to the user may refer to, for example, the operation of notifying the user of the value by various methods. For example, the processor 410 may provide the third value to the user by displaying the third value on the display 450. For example, the processor 410 may provide the third value to the user by outputting a sound (or voice) indicating the third value. For example, the processor 410 may provide the third value to the user by outputting a vibration indicating the third value.

[0148] In operation 752, processor 410 can identify a candidate threshold used to identify the number of times a specified action is performed as a fifth value, different from the third value. For example, a candidate threshold can be identified to determine whether to change the second threshold.

[0149] For example, when using a candidate threshold to identify the number of times a specified action is performed, processor 410 can identify the value indicating the number of times the specified action is performed as the fifth value. Processor 410 can identify the candidate threshold used to identify the value indicating the number of times the specified action is performed as the fifth value.

[0150] For example, processor 410 can identify a fifth value from a candidate threshold within a specified range, used to identify the number of times a specified action is performed. The specified range can be set based on a first reference value and a second reference value. Processor 410 can set the candidate threshold within the specified range, such as the second threshold. For example, operation 752 can correspond to... Figure 7a Operation 730.

[0151] In operation 753, the processor 410 can display a screen for inputting one of the third and fifth values. Operation 753 can correspond to Figure 7a Operation 740.

[0152] In operation 754, processor 410 can identify whether input for a fifth value is recognized. For example, processor 410 can identify whether input for a fifth value is recognized based on a screen displaying input for one of the third and fifth values.

[0153] In operation 755, when input for the fifth value is recognized, processor 410 can change the second threshold to a candidate threshold. Processor 410 can change the second threshold to a candidate threshold based on input for the fifth value. Processor 410 can identify the number of times the user will perform the specified action as the fifth value based on input for the fifth value. Processor 410 can change the second threshold to a candidate threshold and use the changed second threshold to perform operation 751 for identifying the number of times the next set of specified actions will be performed.

[0154] In operation 756, when no input for the fifth value is recognized, processor 410 can maintain the second threshold. Based on the lack of recognition of input for the fifth value, processor 410 can maintain the second threshold. For example, processor 410 can maintain the second threshold based on the recognition of input for the third value. Processor 410 can identify the number of times the user will perform the specified action as the third value based on the input for the third value. Processor 410 can maintain the second threshold and perform operation 751 for identifying the next set of specified actions using the second threshold.

[0155] According to an embodiment, processor 410 may perform operations 751 to 756 each time the user completes a set. For example, processor 410 may repeatedly perform operations 751 to 756 until the user completes all sets. For example, processor 410 may repeatedly perform operations 751 to 756 until the user terminates the exercise.

[0156] According to an embodiment, when the second threshold is maintained based on the termination of the continuous group, operations 751 to 756 may not be performed.

[0157] According to an embodiment, processor 410 can provide results related to the user's exercise based on the completion of the exercise. For example, processor 410 can display a screen representing the results of the user's exercise via display 450. For example, the screen representing the results can show the level of each specified movement.

[0158] For example, the second threshold can be determined to be greater than the first threshold. Based on the value of sensor data associated with the first specified action in the specified actions being less than the first threshold, the processor 410 can identify the level of the first specified action as a first level (e.g., excellent). Based on the value of sensor data associated with the first specified action being less than the second threshold and less than or equal to the first threshold, the processor 410 can identify the level of the first specified action as a second level (e.g., good). Based on the value of sensor data associated with the first specified action being greater than or equal to the second threshold, the processor 410 can identify the level of the first specified action as a third level (e.g., bad).

[0159] According to an embodiment, a second threshold can be determined to be less than a first threshold based on the type of sensor data values ​​and / or the type of exercise. Based on a sensor data value associated with a first specified action in a specified activity being greater than the first threshold, the processor 410 can identify the level of the first specified action as a first level (e.g., excellent). Based on a sensor data value associated with the first specified action being less than or equal to the first threshold and greater than a second threshold, the processor 410 can identify the level of the first specified action as a second level (e.g., good). Based on a sensor data value associated with the first specified action being less than or equal to the second threshold, the processor 410 can identify the level of the first specified action as a third level (e.g., bad).

[0160] Figure 8 This is a graph illustrating example operation of a wearable device according to various embodiments.

[0161] refer to Figure 8 Graph 812 illustrates an example of how sensor data values ​​change over time within a time period 811. For example, a user may perform a specified action (e.g., a squat) within time period 811. Processor 410 may obtain a first value indicating the number of times the specified action is performed, based on the user's performance of the specified action within time period 811, using a first threshold 810. For example, processor 410 may obtain a first value indicating the number of intervals where sensor data values ​​are less than or equal to the first threshold 810. For example, processor 410 may identify the first value indicating the number of intervals where sensor data values ​​are less than or equal to the first threshold 810 as 6.

[0162] For example, processor 410 can identify that the first value corresponds to a specified value (e.g., 6). Processor 410 can identify a set of completed actions based on the first value corresponding to the specified value. After a set of completed actions, processor 410 can determine a second threshold 820, which is used to identify a value indicating the number of times a specified action was performed within time period 811 as a second value different from the first value. For example, processor 410 can identify a second value indicating the number of intervals in which sensor data values ​​are less than or equal to the second threshold 820. As an example, processor 410 can identify the second value indicating the number of intervals in which sensor data values ​​are less than or equal to the second threshold 820 as 8.

[0163] For example, even if the user has performed eight specified actions during time period 811, two of the eight specified actions may not be counted by the wearable device 400. Since the values ​​of the sensor data associated with the two specified actions are greater than a first threshold 810 and less than or equal to a second threshold 820, the processor 410 can identify the first value as 6. Therefore, a difference can arise between the number of times the specified actions were performed as identified by the user and the number of times the specified actions were performed as identified by the processor 410. The processor 410 can determine the second threshold 820 to further count the two specified actions. For example, the processor 410 can also count the two specified actions based on patterns in the sensor data associated with the specified actions. The processor 410 can determine the second threshold 820 for further counting the two specified actions. Based on the determined second threshold 820, the processor 410 can display a screen for inputting one of the first value (e.g., 6) and the second value (e.g., 8). During rest periods between consecutive groups, the processor 410 can determine the second threshold 820 and display a screen for inputting one of the first value (e.g., 6) and the second value (e.g., 8).

[0164] According to an embodiment, after determining the second threshold 820, when identifying the change of sensor data values ​​over time in another group (such as curve 812), the processor 410 can identify a value indicating the number of times a specified action has been performed as 8. According to an embodiment, the processor 410 can identify candidate thresholds for the second threshold 820 whenever multiple groups are performed. Whenever the user performs a group formed by the specified action, the processor 410 can base its decisions on the number of times the specified action has been performed. Figure 7bOperations 751 to 756 are used to change (or update) or maintain the second threshold 820. For example, if the second threshold 820 is set too high in the first group, it can be changed based on user input after the second group. When the user identifies that a specified action has not been performed correctly, the processor 410 can identify user input via the screen after the second setting to set the second threshold 820 low. Whenever the user completes the setting, the processor 410 can change (or update) the second threshold 820 based on the received user input.

[0165] According to an embodiment, processor 410 can identify a second value that is different from the first value. Processor 410 can determine a second threshold for identifying each second value. Processor 410 can display a screen for inputting one of the first and second values.

[0166] Figure 9 This is a graph illustrating example operation of a wearable device according to various embodiments.

[0167] Reference Figure 9 Graph 910 illustrates an example of how sensor data values ​​change over time within a time period 911. For example, a user may perform a specified action (e.g., a squat) within time period 911. Processor 410 may obtain a first value indicating the number of times the specified action is performed, using a first threshold 810, based on the user's performance of the specified action within time period 911. Processor 410 may identify a first value indicating the number of intervals in which sensor data values ​​are less than or equal to the first threshold 810 as 6.

[0168] For example, processor 410 can identify that the first value corresponds to a specified value (e.g., 6). Processor 410 can identify a set of completed actions based on the first value corresponding to the specified value. After a set of completed actions, processor 410 can determine a second threshold 820 for identifying a value indicating the number of times a specified action is performed within time period 911 as a second value different from the first value.

[0169] According to an embodiment, a second threshold 820 can be determined within a specified range. The processor 410 can determine the second threshold 820 within the specified range. For example, the specified range can be set based on reference values ​​901 and 902. Reference value 901 can be set to be greater than reference value 902.

[0170] For example, processor 410 may determine the second threshold 820 as reference value 901 based on the recognition that the second threshold 820 is greater than reference value 901. Although not shown, processor 410 may determine the second threshold 820 as reference value 902 based on the recognition that the second threshold 820 is less than reference value 901.

[0171] Reference Figure 9 When the second threshold 820 is set to be less than the reference value 902, the processor 410 may not recognize that the specified action has been performed even when the user performs the specified action. When the second threshold 820 is set to be greater than the reference value 901, the processor 410 may recognize that the specified action has been performed even when the user has not yet performed the specified action. For example, atmospheric pressure 434 can be used to obtain sensor data. When the second threshold 820 is set to be outside the specified range, the processor 410 may recognize that the specified action has been performed even when the interval of vertical movement from the ground is short. For example, gyroscope sensor 432 can be used to obtain sensor data. When the second threshold 820 is set to be outside the specified range, the processor 410 may recognize that the specified action has been performed even when the posture of the wearable device 400 moves irregularly.

[0172] As described above, a malfunction may occur when the second threshold 820 is outside the specified range set based on reference values ​​901 and 902. Therefore, the processor 410 can determine the second threshold 820 within the specified range.

[0173] Figure 10 This is a diagram illustrating examples of the screen of a wearable device according to various embodiments.

[0174] refer to Figure 10 The state of the wearable device 400 can change from state 1001 to state 1006.

[0175] In states 1001 and 1002, when the user performs the first set, the processor 410 can display screens 1011 and 1012 related to the first set via the display 450 of the wearable device 400. Screens 1011 and 1012 in states 1001 and 1002 may include text 1010 indicating the type of exercise, text 1020 indicating the elapsed time of the set, text 1030 indicating the number of sets, and text 1040 indicating the number of times a specified action is identified when the user performs the first set.

[0176] According to an embodiment, when a user performs a first set of actions, the processor 410 can use a first threshold to identify a first value indicating the number of times a specified action is performed. In state 1001, the processor 410 can use the first threshold to identify the first value indicating the number of times a specified action is performed as 7. The processor 410 can indicate through text 1040 that the number of times the specified action is performed is 7. The processor 410 can indicate through text 1040 within screen 1011 that the number of times the specified action is performed is 7.

[0177] In state 1002, processor 410 can use a first threshold to identify a first value indicating the number of times the specified action is performed as 8. Based on the recognition that the specified action is performed again after state 1001, processor 410 can identify the first value indicating the number of times the specified action is performed as 8. Processor 410 can indicate that the number of times the specified action is performed is 8 based on changing text 1040. Based on changing text 1040, processor 410 can indicate that the number of times the specified action is performed is 8 within screen 1012.

[0178] According to an embodiment, processor 410 can identify that a first value (e.g., 8) corresponds to a specified value (e.g., 8). Processor 410 can change the state of wearable device 400 from state 1002 to state 1003 based on the identification that the first value corresponds to the specified value. Processor 410 can identify that the first set has been completed based on the identification that the first value corresponds to the specified value. Processor 410 can change the state of wearable device 400 from state 1002 to state 1003 based on the identification that the first set has been completed.

[0179] In state 1003, during the rest period between the first and second sets, processor 410 can display a screen 1013 on display 450 for inputting one of the first and second values. For example, processor 410 can display text 1021 on screen 1013 indicating that this is a rest period during exercise.

[0180] Processor 410 may display screen 1013 for inputting one of a first value and a second value based on displaying a first visual object 1051 and a second visual object 1052. For example, processor 410 may determine a second threshold for identifying a value indicating the number of times a specified action is performed in a first group as a second value (e.g., 10) that is different from the first value (e.g., 8). Processor 410 may display the first visual object 1051 indicating the first value on screen 1013. Processor 410 may display the second visual object 1052 indicating the second value on screen 1013.

[0181] For example, a second visual object 1052 can be highlighted on screen 1013 compared to the first visual object 1051. As an example, the size of the second visual object 1052 can be set to be larger than the size of the first visual object 1051.

[0182] Figure 10 An example showing only the first visual object 1051 and the second visual object 1052 is illustrated, but this disclosure is not limited thereto. The processor 410 may display a second visual object on the screen representing each of the second values ​​(e.g., 7, 9, 10, and 11).

[0183] According to an embodiment, processor 410 can identify that the user has performed a specified action 10 times in the first group based on the input recognized for the second visual object 1052. Processor 410 can use a second threshold in the second group to identify the number of times the specified action has been performed. Processor 410 can change the state of wearable device 400 from state 1003 to state 1004 based on the input recognized for the second visual object 1052. According to an embodiment, processor 410 can identify that the user has performed a specified action eight times in the first group based on the input recognized for the first visual object 1051. Even in the second group, processor 410 can use a first threshold to identify the number of times the specified action has been performed.

[0184] In state 1004, processor 410 may display screen 1014 based on input to the second visual object 1052. Screen 1014 may include text 1021 indicating a break time, text 1061 indicating the number of times a specified action was performed in the previous group, and / or text 1060 indicating the remaining time of the break. For example, because input to the second visual object 1052 has been performed, processor 410 may display 10 as the number of times a specified action was performed in the first group.

[0185] According to an embodiment, after all the remaining time of the rest period has passed, the processor 410 can change the state of the wearable device 400 from state 1004 to state 1005.

[0186] In states 1005 and 1006, the second set can begin after all remaining time of the rest period has elapsed. When the user performs the second set, the processor 410 can display screens 1015 and 1016 related to the second set via the display 450 of the wearable device 400. Screens 1015 and 1016 in states 1005 and 1006 may include text 1010 indicating the type of exercise, text 1020 indicating the elapsed time of the set, text 1030 indicating the number of sets, and text 1040 indicating the number of times a specified movement is identified during the user's performance of the second set.

[0187] When the user performs the second set of actions, the processor 410 can use the second threshold to identify a third value indicating the number of times the specified action has been performed.

[0188] In state 1005, processor 410 can use the second threshold to identify a third value indicating the number of times a specified action has been performed as 9. Processor 410 can indicate via text 1040 that the specified action has been performed 9 times. Processor 410 can also indicate via text 1040 on screen 1015 that the specified action has been performed 9 times.

[0189] In state 1006, processor 410 can use a second threshold to identify a third value indicating the number of times a specified action has been performed as 10. Based on the recognition that the specified action was performed again after state 1005, processor 410 can identify the third value indicating the number of times the specified action has been performed as 10. Processor 410 can indicate that the number of times the specified action has been performed is 10 based on changing text 1040. Based on changing text 1040, processor 410 can indicate that the number of times the specified action has been performed is 10 within screen 1016. According to an embodiment, processor 410 can obtain a fourth value indicating the number of times the specified action has been performed using the first threshold while the second group is in progress. Processor 410 can store the fourth value in memory 440. According to an embodiment, after the second group terminates, processor 410 can use the first threshold to obtain a fourth value indicating the number of times the specified action has been performed. Processor 410 can store the fourth value in memory 440.

[0190] Figure 11a It is a diagram including graphs illustrating example operation of a wearable device for squat exercises according to various embodiments.

[0191] Figure 11b It is a graph that includes a curve illustrating an example operation of a wearable device for arm curling exercises according to an embodiment.

[0192] refer to Figure 11a and Figure 11b The sensor data used to set the first and second thresholds can be configured differently. In the above embodiments, although an example of configuring the sensor data with a single value has been described for ease of explanation, the sensor data can be composite data obtained using at least one of the accelerometer sensor 431, gyroscope sensor 432, and / or atmospheric pressure sensor 434. For example, when performing a squat exercise, the processor 410 can use sensor data related to vertical movement in the z-axis direction (e.g., the ground direction) of the accelerometer sensor 431 to identify the squat movement. For example, when performing a squat exercise, the processor 410 can use both sensor data obtained using the accelerometer sensor 431 and sensor data obtained using the gyroscope sensor 432 to identify the squat movement. The processor 410 can determine a first specified value for identifying the squat movement based on the sensor data obtained using the accelerometer sensor 431, and a second specified value for identifying the squat movement based on the sensor data obtained using the gyroscope sensor 432. The threshold for identifying the squat movement may include the first specified value and the second specified value.

[0193] exist Figure 11aDuring time period 1101, when a user performs squat exercises, processor 410 can identify the user's squat movements based on sensor data including acceleration values ​​in the z-axis direction (or ground direction) obtained using accelerometer 431. The unit of acceleration values ​​can be set to [mm / s²].

[0194] For example, processor 410 can identify the number of time periods during which the acceleration value is less than or equal to a first threshold 810 based on sensor data. Processor 410 can identify the number of time periods during which the acceleration value is less than or equal to the first threshold 810 as 5. Processor 410 can use the first threshold 810 to identify that the squatting operation was performed 5 times.

[0195] For example, processor 410 can identify the number of time periods where the acceleration value is less than or equal to a second threshold 820 based on sensor data. Processor 410 can identify the number of time periods where the acceleration value is less than or equal to the second threshold 820 as 7. Processor 410 can use the second threshold 820 to identify that the number of times the squat operation was performed is 7.

[0196] For example, processor 410 can identify the number of time periods where the acceleration value is less than or equal to the reference value 1151 based on sensor data. Processor 410 can identify the number of time periods where the acceleration value is less than or equal to the reference value 1151 as 8. Processor 410 can use the reference value 1151 to identify that the number of squats performed is 8. For example, when the second threshold increases to the reference value 1151, processor 410 can use the second threshold to identify that the number of squats performed is 8.

[0197] exist Figure 11b During time period 1102, when a user performs an arm curl exercise, processor 410 can obtain sensor data including acceleration values ​​in the z-axis direction (or ground direction) and the x-axis direction obtained using accelerometer 431. Processor 410 can use the sensor data to identify the user's arm curl motion. The unit of acceleration values ​​can be set to [mm / s²]. Because the arm curl motion has a semi-circular radius, changes in acceleration in the z-axis and x-axis directions may occur.

[0198] Curve 1110 shows the change of acceleration value in the z-axis direction over time. Curve 1120 shows the change of acceleration value in the x-axis direction over time. Based on the user's arm curling motion, the acceleration values ​​in the z-axis and x-axis directions can be changed. Processor 410 can set a first threshold 810 and a second threshold 820 based on the acceleration values ​​in the z-axis and x-axis directions.

[0199] For example, processor 410 can identify the number of time intervals in which the acceleration values ​​in both the z-axis and x-axis directions are greater than or equal to a first threshold 810. Processor 410 can identify the number of time intervals in which the acceleration values ​​in both the z-axis and x-axis directions are greater than or equal to the first threshold 810 as 8. Processor 410 can use the first threshold 810 to identify that the number of times the arm curl exercise is performed is 8.

[0200] For example, processor 410 can identify the number of time periods in which the acceleration values ​​in both the z-axis and x-axis directions are greater than or equal to a second threshold 820. Processor 410 can identify the number of time periods in which the acceleration values ​​in both the z-axis and x-axis directions are greater than or equal to the second threshold 820 as 9. Processor 410 can use the second threshold 820 to identify that the number of times the arm curl movement was performed is 9. For example, when using the second threshold 820, compared to using the first threshold 810, processor 410 can further count the user's last two arm curl movements.

[0201] For example, processor 410 can identify the number of time intervals in which the acceleration values ​​in both the z-axis and x-axis directions are greater than or equal to the reference value 1152. Processor 410 can identify the number of time intervals in which the acceleration values ​​in both the z-axis and x-axis directions are greater than or equal to the reference value 1152 as 10. Processor 410 can use the reference value 1152 to identify that the number of times the arm curl exercise was performed is 10. For example, when using the reference value 1152, compared to using the second threshold 820, processor 410 can also count the user's last arm curl exercise. For example, when the second threshold 820 decreases to the reference value 1152, processor 410 can use the second threshold 820 to identify that the number of times the arm curl exercise was performed is 10.

[0202] refer to Figure 11a and Figure 11b When the second threshold 820 changes, the number of times a specified action has been identified can be changed. For example, the processor 410 can use the first threshold 810 to identify the number of times a specified action has been performed, and use the second threshold 820, which changes according to user input, to identify the number of times a specified action has been performed. The processor 410 can use the second threshold 820, which is a personalized threshold based on the user, to identify the number of times a specified action has been performed.

[0203] Reference values ​​1151 and 1152 can be configured to prevent and / or reduce the recognition of a specified action even when the user does not perform the specified action. For example, reference value 1151 (or reference value 1152) can be set based on a first threshold 810. As an example, reference value 1151 (or reference value 1152) can be set to 50% of the first threshold 810.

[0204] Figure 12 Includes graphs illustrating example operation of wearable devices according to various embodiments.

[0205] refer to Figure 12 When the second threshold 820 is changed based on user input, the processor 410 can also count specified actions performed with incorrect postures, which can negatively affect the training effect based on the user's judgment. Therefore, the processor 410 can evaluate each specified action after the user's training has ended. For example, the processor 410 can identify one of multiple levels for each specified action. For example, the processor 410 can identify each specified action as one of a first level (e.g., excellent), a second level (e.g., good), and a third level (e.g., bad).

[0206] Curve 1210 represents the change in sensor data values ​​(e.g., acceleration values ​​in the ground direction) based on the time identified in the first group. Curve 1220 represents the change in sensor data values ​​(e.g., acceleration values ​​in the ground direction) based on the time identified in the second group. Curve 1230 represents the change in sensor data values ​​(e.g., acceleration values ​​in the ground direction) based on the time identified in the third group.

[0207] According to an embodiment, after the users in the first, second, and third groups have completed their workouts, the processor 410 can use a first threshold 810 and a second threshold 820 to identify the level of each specified action when the workout ends. For example, the processor 410 can identify the level of the first specified action as a first level (e.g., excellent) based on the value of sensor data associated with the first specified action in the specified actions being less than the first threshold 810. The processor 410 can identify the level of the first specified action as a second level (e.g., good) based on the value of sensor data associated with the first specified action in the specified actions being greater than or equal to the first threshold 810 and less than the second threshold 820. The processor 410 can identify the level of the first specified action as a third level (e.g., bad) based on the value of sensor data associated with the first specified action in the specified actions being greater than or equal to the second threshold 820 and less than a reference value 1201.

[0208] Processor 410 can identify three intervals based on a first threshold 810, a second threshold 820, and a reference value 1201. Processor 410 can identify the interval where the sensor data value is less than the first threshold 810 as the first interval 1251. Processor 410 can identify the interval where the sensor data value is greater than or equal to the first threshold 810 and less than the second threshold 820 as the second interval 1252. Processor 410 can identify the interval where the sensor data value is greater than or equal to the second threshold 820 and less than the reference value 1201 as the third interval 1253.

[0209] Referring to graph 1210, the number of time intervals in which the sensor data values ​​fall within the first interval 1251 can be identified as 10. There may be no time intervals in which the sensor data values ​​fall within the second interval 1252 or the third interval 1253. Processor 410 can identify that the level of the 10 specified actions performed in the first group is the first level.

[0210] Referring to curve 1220, the number of time intervals within the first interval 1251 for the sensor data values ​​can be identified as 7. The number of time intervals within the second interval 1252 for the sensor data values ​​can be identified as 2. The number of time intervals within the third interval 1253 for the sensor data values ​​can be identified as 1. The processor 410 can identify that among the 10 specified actions executed in the second group, 7 specified actions are at level 1, 2 specified actions are at level 2, and 1 specified action is at level 3.

[0211] Referring to curve 1230, the number of time intervals within the first interval 1251 of the sensor data value can be identified as 4. The number of time intervals within the second interval 1252 of the sensor data value can be identified as 4. The number of time intervals within the third interval 1253 of the sensor data value can be identified as 2. The processor 410 can identify that among the 10 specified actions executed in the third group, 4 specified actions are at the first level, 4 specified actions are at the second level, and 2 specified actions are at the third level.

[0212] According to an embodiment, after the exercise is completed, the processor 410 can display a screen on the display 450 to provide exercise results. The following will refer to... Figure 13 A more detailed description of specific examples of screens used to display workout results.

[0213] Figure 13 This is a diagram illustrating example operation of a wearable device for displaying a user's exercise results according to various embodiments.

[0214] refer to Figure 13After the exercise is completed, the processor 410 can display a screen 1300 on the monitor 450 to provide exercise results. For example, the processor 410 can display the level of each specified movement as one of objects 1301, 1302, and 1303. For example, object 1301 can represent the first level. Object 1302 can represent the second level. Object 1303 can represent the third level.

[0215] The level of each of the 10 specified actions in the first group (e.g., group 1) can be displayed in area 1310. For example, the levels of all 10 specified actions in the first group can be identified as level 1.

[0216] The level of each of the 10 specified actions in the second group (e.g., group 2) can be displayed in area 1320. For example, in the 10 specified actions of the second group, the level of 7 specified actions can be identified as level 1. In the 10 specified actions of the second group, the level of 2 specified actions can be identified as level 2. In the 10 specified actions of the second group, the level of 1 specified action can be identified as level 3.

[0217] The level of each of the 10 specified actions in the third group (e.g., group 3) can be displayed in area 1330. For example, in the 10 specified actions of the third group, the level of 4 specified actions can be identified as level 1. In the 10 specified actions of the second group, the level of 4 specified actions can be identified as level 2. In the 10 specified actions of the second group, the level of 2 specified actions can be identified as level 3.

[0218] According to an embodiment, screen 1300 may also include a region 1350 for displaying text indicating feedback on exercise results. Although not shown, processor 410 may display text in region 1350 indicating that the last 9 and 10 postures in the third group were unstable and suggesting that the correct posture should be maintained until the end. Although not shown, when displaying exercise results using dumbbells (or barbells), processor 410 may display text guiding the user to reduce the weight of the dumbbells (or barbells) in the groups with unstable postures.

[0219] Figure 14 This is a graph illustrating example operation of a wearable device for displaying a user's exercise results according to various embodiments.

[0220] refer to Figure 14The processor 410 can provide the user with a screen 1400 indicating changes to the first threshold 810 and the second threshold 820. For example, the first threshold 810 can be a fixed value and may not change. The second threshold 820 can change based on user input. Therefore, the second threshold 820 can be changed whenever the user exercises.

[0221] The processor 410 can store the results of multiple training sessions in the memory 440. For example, based on the results of multiple training sessions, the processor 410 can identify the trend of change in the first threshold 810 and the trend of change in the second threshold 820, and present them through the screen 1400.

[0222] For example, processor 410 can identify trends in the change of a first threshold 810 and a second threshold 820 based on 11 training results. Graph 1401 can represent the trend in the change of the first threshold 810. Graph 1402 can represent the trend in the change of the second threshold 820.

[0223] Although not shown, processor 410 can display the ratio of the second threshold 820 to the first threshold 810 at substantially the same point in time (e.g., 9 weeks ago). For example, processor 410 can display the ratio of the second threshold 820 to the first threshold 810 as 80% based on training results from 6 weeks ago. Although not shown, processor 410 can display the rate of change of the second threshold 820 at different points in time. Processor 410 can display the rate of change of the second threshold 820 as 10% based on training results from 7 weeks ago and 6 weeks ago.

[0224] Figure 15 This is a flowchart illustrating example operation of a wearable device according to various embodiments.

[0225] refer to Figure 15 In operation 1510, processor 410 can recognize the start of a user workout based on a specified movement. For example, the user's workout may include squat exercises (e.g., Figure 4a Squat exercises 401), rowing machine exercises (for example, Figure 4a Rowing machine exercises 402), dumbbell press exercises (for example, Figure 4a Dumbbell press exercise 403) and / or arm curl exercise. For example, operation 1510 can correspond to Figure 7a Operation 710.

[0226] For example, memory 440 may store a first threshold. Memory 440 may store a first threshold used to identify the number of times a specified action is performed.

[0227] For example, a first threshold can be set based on at least one of the user's height, weight, body type, age, and / or gender. For example, the first threshold can be a fixed value. For example, the first threshold can be referred to as a default threshold.

[0228] In operation 1520, processor 410 can obtain information about a specified action. For example, processor 410 can obtain information about a specified action based on recognizing the start of a user's exercise. For example, information about a specified action (or the user's exercise movement) may include sensor values ​​(or sensor data) obtained through sensor 430.

[0229] In operation 1530, processor 410 may obtain a second threshold for identifying the number of times a specified action has been performed. For example, based on information about the specified action, processor 410 may obtain a second threshold for identifying the number of times the specified action has been performed. For example, processor 410 may obtain a second threshold for identifying the number of times the specified action has been performed, which is different from the first threshold.

[0230] In operation 1540, processor 410 may display a first threshold and a second threshold on display 450. For example, the first threshold and the second threshold can be used to identify the number of times a specified action is performed.

[0231] According to an embodiment, processor 410 may display a screen on display 450 for input to one of a first threshold and a second threshold. For example, processor 410 may identify each of the first threshold and the second threshold as one of "high", "medium", and "low". Processor 410 may display a screen on display 450 for input to one of a first threshold set to "medium" and a second threshold set to "low".

[0232] According to an embodiment, the screen for input to one of a first threshold and a second threshold may include a first visual object associated with the first threshold and a second visual object associated with the second threshold. Input to one of the first and second thresholds may include input to one of the first and second visual objects. For example, the second visual object may be highlighted on the screen compared to the first visual object.

[0233] According to an embodiment, processor 410 may maintain the threshold for identifying the number of times a specified action is performed at the first threshold based on identifying input for a first threshold. Processor 410 may change the threshold for identifying the number of times a specified action is performed from the first threshold to the second threshold based on identifying input for a second threshold.

[0234] According to an example embodiment, the wearable device may include a display, at least one sensor, a first memory (including one or more storage media) storing first information about exercise movements, a second memory (including one or more storage media) storing instructions, and at least one processor including processing circuitry. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to recognize the start of a user's exercise based on a specified action. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to obtain second information about the user's exercise movements based on the execution of the specified action. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to obtain a first value indicating the number of times the specified action has been performed, based on the second information and using a first threshold included in the first information. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to determine a second threshold, the second threshold being used to identify the value indicating the number of times the specified action has been performed as a second value distinguished from the first value. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to display a screen for input to one of the first and second values ​​based on the determined second threshold.

[0235] According to an example embodiment, when executed individually or jointly by at least one processor, the instructions cause the wearable device to display a screen comprising a first visual object representing a first value and a second visual object representing a second value based on a determined second threshold.

[0236] According to an example embodiment, input for one of the first value and the second value may include input for one of the first visual object and the second visual object.

[0237] According to an example embodiment, a second visual object can be highlighted compared to a first visual object on the screen.

[0238] According to an example embodiment, when the instructions are executed individually or jointly by at least one processor, the wearable device: based on an input identifying a first threshold, maintains a threshold for identifying the value indicating the number of times a specified action is performed at the first threshold. When the instructions are executed individually or jointly by at least one processor, the wearable device: based on an input identifying a second threshold, changes the threshold for identifying the value indicating the number of times a specified action is performed from the first threshold to the second threshold.

[0239] According to an example embodiment, when executed individually or jointly by at least one processor, the instructions cause the wearable device to: maintain a threshold for identifying the number of times a specified action is performed at a first threshold based on input identifying a first value. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: add a second threshold to a threshold for identifying the number of times a specified action is performed, based on input identifying a second value.

[0240] According to an example embodiment, when the instructions are executed individually or jointly by at least one processor, the wearable device determines a second threshold within a specified range, the second threshold being used to identify a value indicating the number of times a specified action is performed as a second value.

[0241] According to an example embodiment, a specified range can be set based on a first reference value and a second reference value greater than the first reference value. When the instructions are executed individually or jointly by at least one processor, the instructions cause the wearable device to perform the following operations: determining the second threshold as the first reference value based on the identification that the second threshold is less than the first reference value. When the instructions are executed individually or jointly by at least one processor, the instructions cause the wearable device to perform the following operations: determining the second threshold as the second reference value based on the identification that the second threshold is greater than the second reference value.

[0242] According to an example embodiment, the second threshold can be determined to be less than the first threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a first level based on a value of sensor data associated with a first specified action in the specified actions being greater than or equal to the first threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a second level based on a value of sensor data being less than the first threshold and greater than or equal to a second threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a third level based on a value of sensor data being less than the second threshold.

[0243] According to an example embodiment, the second threshold can be determined to be greater than the first threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a first level based on a value of sensor data associated with a first specified action in the specified actions being less than the first threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a second level based on a value of sensor data greater than or equal to the first threshold and less than the second threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a third level based on a value of sensor data greater than or equal to the second threshold.

[0244] According to an example embodiment, when instructions are executed individually or collectively by at least one processor, the instructions cause the wearable device to display a screen for showing the user's exercise results based on the user's exercise completion. The screen used to display the results may represent the level associated with each specified action.

[0245] According to an example embodiment, a user's workout can be performed through multiple sets based on the repetition of specified actions according to specified values. When executed individually or jointly by at least one processor, the instructions cause the wearable device to identify the first set of the multiple sets being executed based on a first value corresponding to the specified value.

[0246] According to an example embodiment, when executed individually or jointly by at least one processor, the instructions cause the wearable device to provide a notification indicating the end of a first group based on a first value corresponding to a specified value.

[0247] According to an example embodiment, when the instructions are executed individually or jointly by at least one processor, the wearable device identifies a third value using a second threshold based on input to a second value, the third value indicating the number of times a specified action of a second group, which is the next group after the first group, is performed.

[0248] According to an example embodiment, when the instructions are executed individually or jointly by at least one processor, the wearable device displays a screen using a second threshold that indicates the number of times the specified action in the second group is being performed, based on the specified action being performed in the second group.

[0249] According to an example embodiment, when the instruction is executed individually or jointly by at least one processor, while a specified action in the second group is being performed by the wearable device, a fourth value indicating the number of times the specified action in the second group is performed is stored using a first threshold.

[0250] According to an example embodiment, a method performed by a wearable device may include: obtaining second information about a user's exercise based on the execution of a specified action. The method may include: obtaining a first value indicating the number of times the specified action has been performed, based on the second information and using a first threshold included in first information about the exercise stored in the wearable device's memory. The method may include determining a second threshold for identifying the value indicating the number of times the specified action has been performed as a second value distinguished from the first value. The method may include: displaying a screen for inputting one of the first and second values, based on the determined second threshold.

[0251] According to an example embodiment, the method may include: displaying a screen comprising a first visual object representing a first value and a second visual object representing a second value, based on determining a second threshold. Input for one of the first and second values ​​may include input for one of the first and second visual objects.

[0252] According to an example embodiment, a second visual object can be highlighted compared to a first visual object on the screen.

[0253] According to an example embodiment, the method may include: maintaining a threshold for identifying a value indicating the number of times a specified action is performed at the first threshold based on identifying input for a first threshold. The method may also include: changing the threshold for identifying a value indicating the number of times a specified action is performed from the first threshold to the second threshold based on identifying input for a second threshold.

[0254] According to an example embodiment, a non-transitory computer-readable storage medium may store one or more programs. The one or more programs may include instructions that, when executed individually and / or jointly by at least one processor of a wearable device having a display, cause the wearable device to recognize the start of a user's exercise based on a specified action. The one or more programs may include instructions that, when executed by at least one processor, cause the wearable device to obtain second information about the user's exercise movement based on the execution of the specified action. The one or more programs may include instructions that, when executed by at least one processor, cause the wearable device to: obtain a first value indicating the number of times the specified action has been performed, based on the second information, using a first threshold included in the first information. The one or more programs may include instructions that, when executed by at least one processor, cause the wearable device to determine a second threshold, the second threshold being used to identify the value indicating the number of times the specified action has been performed as a second value distinguished from the first value. The one or more programs may include instructions that, when executed by at least one processor, cause the wearable device to: display a screen for input to one of the first and second values, based on the determined second threshold.

[0255] According to an example embodiment, the wearable device may include a display, at least one sensor, a first memory (including one or more storage media) storing first information about exercise movements, a second memory (including one or more storage media) storing instructions, and at least one processor including processing circuitry. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to recognize the start of a user exercise based on a specified action. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to obtain second information about the specified action. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to obtain a first value indicating the number of times the specified action for the second information has been performed, based on a first threshold associated with the first information. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to obtain a second value indicating the number of times the specified action for the second information has been performed, based on a second threshold associated with the first information. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to display the first and second values ​​on the display.

[0256] According to an example embodiment, when executed individually or jointly by at least one processor, the instructions cause the wearable device to display a screen for inputting at least one of a first value and a second value. The screen may include a first visual object representing the first value and a second visual object representing the second value.

[0257] According to an example embodiment, input for at least one of a first value and / or a second value may include input for at least one of a first visual object and / or a second visual object.

[0258] According to an example embodiment, a second visual object can be highlighted compared to a first visual object on the screen.

[0259] According to an example embodiment, when the instructions are executed individually or jointly by at least one processor, the wearable device: based on input identifying a first value, maintains a threshold included in first information for identifying the number of times a specified action has been performed at a first threshold. When the instructions are executed individually or jointly by at least one processor, the wearable device: based on input identifying a second value, changes the threshold included in the first information for identifying the number of times a specified action has been performed from the first threshold to a second threshold.

[0260] According to an example embodiment, when executed individually or jointly by at least one processor, the instructions cause the wearable device to: maintain a threshold for identifying the number of times a specified action has been performed, included in first information, at a first threshold based on input identifying a first value. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: add a second threshold to a threshold for identifying the number of times a specified action has been performed, included in first information, based on input identifying a second value.

[0261] According to an example embodiment, when executed individually or jointly by at least one processor, the instructions cause the wearable device to determine a second threshold within a specified range for obtaining a second value.

[0262] According to an example embodiment, a specified range can be set based on a first reference value and a second reference value greater than the first reference value. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: determine a second threshold as the first reference value based on the identification that a second threshold is less than the first reference value. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: determine a second threshold as the second reference value based on the identification that a second threshold is greater than the second reference value.

[0263] According to an example embodiment, the second threshold can be determined to be less than the first threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a first level based on a value of sensor data associated with a first specified action in the specified actions being greater than or equal to the first threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a second level based on a value of sensor data being less than the first threshold and greater than or equal to a second threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a third level based on a value of sensor data being less than the second threshold.

[0264] According to an example embodiment, the second threshold can be determined to be greater than the first threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a first level based on a value of sensor data associated with a first specified action in the specified actions being less than the first threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a second level based on a value of sensor data greater than or equal to the first threshold and less than the second threshold. When executed individually or jointly by at least one processor, the instructions cause the wearable device to: identify the level of the first specified action as a third level based on a value of sensor data greater than or equal to the second threshold.

[0265] According to an example embodiment, when instructions are executed individually or collectively by at least one processor, the instructions cause the wearable device to display a screen for showing the results of the user's workout based on the completion of the workout. The screen used to display the results may represent a level associated with each specified action.

[0266] According to an example embodiment, a user's workout can be performed through multiple sets based on the repetition of specified actions according to specified values. When executed individually or jointly by at least one processor, the instructions cause the wearable device to identify the first set of the multiple sets being executed based on a first value corresponding to the specified value.

[0267] According to an example embodiment, when executed individually or jointly by at least one processor, the instructions cause the wearable device to provide a notification indicating the end of a first group based on a first value corresponding to a specified value.

[0268] According to an example embodiment, when the instructions are executed individually or jointly by at least one processor, the wearable device identifies a third value using a second threshold based on input to a second value, the third value indicating the number of times a specified action of a second group, which is the next group after the first group, is performed.

[0269] According to an example embodiment, when the instructions are executed individually or jointly by at least one processor, while a specified action in the second group is being performed on the wearable device, a screen is displayed based on a second threshold, indicating a third value representing the number of times the specified action in the second group has been performed.

[0270] According to an example embodiment, when the instructions are executed individually or jointly by at least one processor, the wearable device stores a fourth value indicating the number of times the specified action in the second group is executed, based on a first threshold, while a specified action in the second group is being performed.

[0271] According to an example embodiment, a method performed by a wearable device may include recognizing the start of a user workout based on a specified action. The method may include obtaining second information about the specified action. The method may include obtaining second information about the user's workout actions based on the execution of the specified action. The method may include obtaining a first value based on a first threshold associated with first information, the first value indicating the number of times the specified action has been performed relative to the second information. The method may include obtaining a second value indicating the number of times the specified action has been performed for the second information, based on a second threshold associated with the first information. The method may include displaying the first and second values ​​on a display.

[0272] According to an example embodiment, the method may include displaying a screen for inputting at least one of a first value and / or a second value. The screen may include a first visual object representing the first value and a second visual object representing the second value. Input of at least one of the first value and the second value may include input for at least one of the first visual object and / or the second visual object.

[0273] According to an example embodiment, a second visual object can be highlighted compared to a first visual object on the screen.

[0274] According to an example embodiment, the method may include: maintaining a threshold for identifying the number of times a specified action is performed at a first threshold based on input identifying a first value. The method may also include: changing the threshold for identifying the number of times a specified action is performed from the first threshold to a second threshold based on input identifying a second value.

[0275] According to an example embodiment, a non-transitory computer-readable storage medium may store one or more programs. The one or more programs may include instructions that, when executed by at least one processor of a wearable device having a display, cause the wearable device to recognize the initiation of a user exercise based on a specified action. The one or more programs may include instructions that cause the wearable device to obtain second information about the specified action. The one or more programs may include instructions that cause the wearable device to obtain a first value based on a first threshold associated with the first information, the first value indicating the number of times the specified action for the second information has been performed. The one or more programs may include instructions that cause the wearable device to obtain a second value based on a second threshold associated with the first information, the second value indicating the number of times the specified action for the second information has been performed. The one or more programs may include instructions that cause the wearable device to display the first and second values ​​on the display.

[0276] According to an example embodiment, the wearable device may include a display, at least one sensor, a first memory including one or more storage media for storing a first threshold, a second memory including one or more storage media for storing instructions, and at least one processor including processing circuitry. When executed individually or jointly by the at least one processor, the instructions cause the wearable device to recognize the start of a user workout based on a specified action. According to an example embodiment, when executed individually or jointly by the at least one processor, the instructions cause the wearable device to obtain information about the specified action. According to an example embodiment, when executed individually or jointly by the at least one processor, the instructions cause the wearable device to obtain a second threshold based on the information, recognizing the number of times the specified action has been performed. According to an example embodiment, when executed individually or jointly by the at least one processor, the instructions cause the wearable device to display the first threshold and the second threshold on the display.

[0277] According to an example embodiment, when executed individually or jointly by at least one processor, the instructions cause the wearable device to display a screen for input to one of a first threshold and a second threshold.

[0278] According to an example embodiment, the screen may include a first visual object representing a first threshold and a second visual object representing a second threshold. Input targeting one of the first threshold and the second threshold may include input targeting one of the first visual object and the second visual object.

[0279] According to an example embodiment, a second visual object can be highlighted compared to a first visual object on the screen.

[0280] According to an example embodiment, when the instructions are executed individually or jointly by at least one processor, the wearable device: maintains a threshold for identifying the number of times a specified action is performed at the first threshold based on input identifying a first threshold. When the instructions are executed individually or jointly by at least one processor, the wearable device changes the threshold for identifying the number of times a specified action is performed from the first threshold to the second threshold based on input identifying a second threshold.

[0281] According to various embodiments, the wearable device can identify a user's workout based on a specified action. The wearable device can identify the number of times the specified action is performed. The wearable device can provide the user with the number of times the specified action is performed. When the number of times the specified action provided to the user is performed differs from the number of times the specified action is actually performed, the wearable device can provide the user with a screen for correcting (or modifying) the number of times the specified action is performed. The wearable device can improve the accuracy of identification by correcting the number of times the specified action is identified as being performed in the wearable device. For example, the wearable device can provide a screen for correcting the count at the end of each user's workout set. The wearable device can display suggested correction values ​​on the screen, allowing the user to easily correct the count. The user can correct the number of times the specified action is performed in a group simply by inputting objects on the screen.

[0282] The electronic device according to various embodiments can be one of a variety of types of electronic devices. Electronic devices may include, for example, portable communication devices (e.g., smartphones), computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, or home appliances. According to embodiments of this disclosure, the electronic device is not limited to those described above.

[0283] It should be understood that the various embodiments of this disclosure and the terminology used therein are not intended to limit the technical features set forth herein to the specific embodiments, but rather to include various changes, equivalents, or substitutions to the respective embodiments. In the description of the drawings, similar reference numerals may be used to refer to similar or related elements. It will be understood that nouns in the singular form corresponding to terms may include one or more things unless the relevant context clearly indicates otherwise. As used herein, each of the 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 include any one or all possible combinations of the items enumerated together with the corresponding phrase among the plurality of phrases. As used herein, terms such as “first” and “second” or “first” and “second” may be used to simply distinguish the respective component from another component and do not limit the component in other respects (e.g., importance or order). It will be understood that, whether the terms “operably” or “communically” are used or not, if an element (e.g., a first element) is referred to as “combined with another element (e.g., a second element),” “combined to another element (e.g., a second element),” “connected to another element (e.g., a second element),” or “connected to another element (e.g., a second element)”, it means that the element can be directly (e.g., wiredly) connected to the other element, wirelessly connected to the other element, or connected to the other element via a third element.

[0284] As used in connection with various embodiments of this disclosure, the term "module" may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with other terms such as "logic," "logic block," "part," or "circuit." A module may be a single integrated component adapted to perform one or more functions, or the smallest unit or part of such a single integrated component. For example, according to embodiments, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0285] The various embodiments set forth herein can be implemented as software (e.g., program 140) containing one or more instructions readable by a machine (e.g., electronic device 101) stored in a storage medium (e.g., internal memory 136 or external memory 138). For example, under the control of a processor, the processor (e.g., processor 120) of the machine (e.g., electronic device 101) can invoke and execute at least one of the one or more instructions stored in the storage medium, with or without the use of one or more other components. This enables the machine to operate to perform at least one function according to the invoked at least one instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. Machine-readable storage media may be provided in the form of non-transitory storage media. The term "non-transitory" simply means that the storage medium is a tangible device and does not include signals (e.g., electromagnetic waves), but this term does not distinguish between data being stored semi-permanently in the storage medium and data being temporarily stored in the storage medium.

[0286] According to embodiments, methods according to various embodiments of this disclosure may be included and provided in a computer program product. The computer program product can be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., a compact disk read-only memory (CD-ROM)) or via an app store (e.g., the Play Store). TM The computer program product may be published online (e.g., downloaded or uploaded), or may be distributed directly between two user devices (e.g., smartphones) (e.g., downloaded or uploaded). If published online, at least a portion of the computer program product may be temporarily generated, or at least a portion of the computer program product may be temporarily stored in a machine-readable storage medium (such as the memory of a manufacturer's server, an app store's server, or a forwarding server).

[0287] According to various embodiments, each of the above-described components (e.g., a module or program) may include a single entity or multiple entities, and some of the multiple entities may be separately disposed in different components. According to various embodiments, one or more of the above-described components may be omitted, or one or more other components may be added. Optionally or additionally, multiple components (e.g., modules or programs) may be integrated into a single component. In this case, according to various embodiments, the integrated component may still perform the one or more functions of each of the multiple components in the same or similar manner as the corresponding component of the multiple components performed one or more functions before integration. According to various embodiments, the operations performed by a module, program, or other component may be performed sequentially, in parallel, repeatedly, or heuristically, or one or more of the operations may be run in a different order or omitted, or one or more other operations may be added.

[0288] While this disclosure has been shown and described with reference to various exemplary embodiments, it should be understood that these exemplary embodiments are intended to be illustrative and not restrictive. Those skilled in the art will further understand that various changes in form and detail may be made without departing from the true spirit and full scope of this disclosure (including the appended claims and their equivalents). It should also be understood that any embodiment described herein may be used in conjunction with any other embodiment described herein.

Claims

1. A wearable device, comprising: monitor; At least one sensor; A first memory stores first information about the exercise, and the first memory includes one or more storage media; Second memory, storing instructions, the second memory includes one or more storage media; as well as At least one processor, including processing circuitry; The instructions, when executed individually or jointly by the at least one processor, enable the wearable device to: Identify the start of a user's workout based on a specified action. Obtain second information about the specified action. Based on a first threshold related to the first information, a first value indicating the number of times a specified action for the second information is performed is obtained. Based on a second threshold related to the first information, a second value indicating the number of times a specified action for the second information is performed is obtained, and Display the first and second values ​​on the monitor.

2. The wearable device according to claim 1, wherein, When the instructions are executed individually or jointly by the at least one processor, the wearable device displays a screen for inputting at least one of a first value and a second value. The screen includes a first visual object representing a first value and a second visual object representing a second value, and The input of at least one of the first value and the second value includes input for the first visual object or the second visual object.

3. The wearable device according to claim 2, wherein, The second visual object is highlighted compared to the first visual object on the screen.

4. The wearable device according to claim 2, wherein, The instructions, when executed individually or jointly by the at least one processor, enable the wearable device to: Based on the input identified in response to the first value, the threshold for identifying the number of times a specified action is performed, included in the first information, is maintained as the first threshold. Based on the input for the second value, the threshold for identifying the number of times the specified action is performed, which is included in the first information, is changed from the first threshold to the second threshold.

5. The wearable device according to claim 2, wherein, The instructions, when executed individually or jointly by the at least one processor, enable the wearable device to: Based on the input identified in response to the first value, the threshold for identifying the number of times a specified action is performed, included in the first information, is maintained as the first threshold. Based on the input identified for the second value, the second threshold is added to the threshold included in the first information for identifying the number of times the specified action is performed.

6. The wearable device according to claim 1, wherein, When the instructions are executed individually or jointly by the at least one processor, the wearable device determines a second threshold within a specified range for obtaining the second value.

7. The wearable device according to claim 6, wherein, The specified range is set based on a first reference value and a second reference value greater than the first reference value, and The instructions, when executed individually or jointly by the at least one processor, enable the wearable device to: Based on the premise that the second threshold is less than the first reference value, the second threshold is determined as the first reference value, and Based on the fact that the second threshold is greater than the second reference value, the second threshold is determined as the second reference value.

8. The wearable device according to claim 1, wherein, The second threshold is determined to be less than the first threshold. The instructions, when executed individually or jointly by the at least one processor, enable the wearable device to: Based on the sensor data value associated with the first specified action in the specified actions being greater than or equal to a first threshold, the level of the first specified action is identified as the first level. Based on sensor data values ​​that are less than a first threshold and greater than or equal to a second threshold, the level of the first specified action is identified as the second level. If the value of the sensor data is less than the second threshold, the level of the first specified action is identified as the third level.

9. The wearable device according to claim 1, wherein, The second threshold is determined to be greater than the first threshold. In this embodiment, at least one processor is individually and / or collectively configured to enable the wearable device to: Based on the fact that the value of the sensor data associated with the first specified action in the specified actions is less than a first threshold, the level of the first specified action is identified as the first level. Based on sensor data values ​​that are greater than or equal to a first threshold and less than a second threshold, the level of the first specified action is identified as the second level. Based on the sensor data value being greater than or equal to the second threshold, the level of the first specified action is identified as the third level.

10. The wearable device according to claim 9, wherein, The instructions, when executed individually or jointly by the at least one processor, cause the wearable device to display a screen showing the user's exercise results based on the user's completed workout. The screen used to display the results represents the level associated with each of the specified actions.

11. The wearable device according to claim 2, wherein, The user's workout is performed through multiple sets based on repetitions of a specified action according to specified values, and... The instructions, when executed individually or jointly by the at least one processor, cause the wearable device to identify the first group of the plurality of groups as being executed based on a first value corresponding to a specified value.

12. The wearable device according to claim 11, wherein, When the instructions are executed individually or jointly by the at least one processor, the wearable device provides a notification indicating the end of the first group based on a first value corresponding to a specified value.

13. The wearable device according to claim 11, wherein, When the instructions are executed individually or jointly by the at least one processor, the wearable device: based on the input for the second value, identifies a third value using a second threshold, the third value indicating the number of times a specified action of the second group, which is the next group after the first group, is performed in the plurality of groups.

14. A method performed by a wearable device, the method comprising: Identify the start of a user's workout based on a specified action. Obtain second information about the specified action. Based on a first threshold related to the first information, a first value indicating the number of times a specified action for the second information is performed is obtained. Based on a second threshold related to the first information, a second value indicating the number of times a specified action for the second information is performed is obtained, and Display the first and second values ​​on the monitor.

15. A non-transitory computer-readable storage medium storing one or more programs, wherein, The one or more programs include instructions that, when executed individually and / or jointly by at least one processor of a wearable device having a display, cause the wearable device to: Identify the start of a user's workout based on a specified action. Obtain second information about the specified action. Based on a first threshold related to the first information, a first value indicating the number of times a specified action for the second information is performed is obtained. Based on a second threshold related to the first information, a second value indicating the number of times a specified action for the second information is performed is obtained, and Display the first and second values ​​on the monitor.

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