Wearable device for identifying gesture of user

Abstract

According to one embodiment, a method performed by a wearable device worn on a first part of a user's body may comprise the operations of: receiving a radio frequency (RF) signal, for identifying a gesture performed through the user's body, from another wearable device, worn on a second part of the user's body, within a reference time interval through a communication circuit on the basis of a movement of the user's body; identifying first information about the strength of the received RF signal and second information, included in the received RF signal, about impedance characteristics of the other wearable device; recognizing a gesture, performed within the reference time interval according to the movement of the user's body, on the basis of the first information and the second information; and performing at least one function corresponding to the recognized gesture.

Description

Wearable device for identifying user gestures

[0001] The following descriptions relate to a wearable device for identifying user gestures.

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

[0003] The information described above may be provided as related art for the purpose of aiding understanding of the present disclosure. No claim or determination is made as to whether any of the foregoing may be applied as prior art related to the present disclosure.

[0004] According to one embodiment, a wearable device worn on a first part of a user's body may include a communication circuit, a memory including instructions and one or more storage media, and at least one processor including a processing circuit. When the instructions are executed individually or collectively by the at least one processor, the wearable device may receive, through the communication circuit, a radio frequency (RF) signal for identifying a gesture performed through the user's body from another wearable device worn on a second part of the user's body based on the movement of the user's body within a reference time interval, identify first information regarding the strength of the received RF signal and second information regarding the impedance characteristics of the other wearable device included in the received RF signal, and based on the first information and the second information, recognize a gesture performed within the reference time interval according to the movement of the body and cause the wearable device to perform at least one function corresponding to the recognized gesture.

[0005] According to one embodiment, a method performed by a wearable device worn on a first part of a user's body may include: receiving a radio frequency (RF) signal for identifying a gesture performed through the user's body from another wearable device worn on a second part of the user's body, based on the movement of the user's body, through a communication circuit within a reference time interval; identifying first information regarding the strength of the received RF signal and second information regarding the impedance characteristics of the other wearable device included in the received RF signal; recognizing a gesture performed within the reference time interval according to the movement of the body based on the first information and the second information; and performing at least one function corresponding to the recognized gesture.

[0006] According to one 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 communication circuit and worn on a first part of a user's body, receive a radio frequency (RF) signal for identifying a gesture performed through the user's body from another wearable device worn on a second part of the user's body based on the movement of the user's body within a reference time interval through the communication circuit, identify first information regarding the strength of the received RF signal and second information regarding the impedance characteristics of the other wearable device included in the received RF signal, recognize a gesture performed within the reference time interval according to the movement of the body based on the first information and the second information, and cause the wearable device to perform at least one function corresponding to the recognized gesture.

[0007] FIG. 1 is a block diagram of an electronic device in a network environment according to one embodiment.

[0008] FIGS. 2a and 2b illustrate perspective views of an electronic device that is an example according to one embodiment.

[0009] FIG. 3 shows an exploded perspective view of an exemplary electronic device according to one embodiment.

[0010] FIG. 4a shows a perspective view of an exemplary electronic device according to one embodiment.

[0011] FIG. 4b is an example of a partial cross-sectional view of an electronic device according to one embodiment.

[0012] FIG. 5 illustrates an example of an environment including a first wearable device and a second wearable device according to one embodiment.

[0013] FIG. 6 illustrates an example of a simplified block diagram of a first wearable device and a second wearable device according to one embodiment.

[0014] FIG. 7 illustrates an example of the operation of a first wearable device and a second wearable device according to one embodiment.

[0015] FIG. 8 illustrates a flowchart regarding the operation of a first wearable device for recognizing a user's gesture according to one embodiment.

[0016] FIG. 9a illustrates an example of a first Fresnel zone (FFZ) defined through a first wearable device and a second wearable device according to one embodiment.

[0017] FIG. 9b illustrates an example of a first Fresnel zone (FFZ) defined through a first wearable device and a second wearable device according to one embodiment.

[0018] FIG. 9c illustrates an example of a first Fresnel zone (FFZ) defined through a first wearable device and a second wearable device according to one embodiment.

[0019] FIG. 10a illustrates an example of the positional relationship between a first wearable device and a second wearable device according to one embodiment.

[0020] FIG. 10b illustrates an example of a transmission coefficient according to the positional relationship between a first wearable device and a second wearable device, according to one embodiment.

[0021] FIG. 10c illustrates an example of a graph showing the strength of a received RF signal according to one embodiment.

[0022] FIG. 10d illustrates an example of a graph showing the strength of a received RF signal according to one embodiment.

[0023] FIG. 10e illustrates an example of a graph showing the strength of a received RF signal according to one embodiment.

[0024] FIG. 11a illustrates an example of the positional relationship between a first wearable device and a second wearable device according to one embodiment.

[0025] FIG. 11b illustrates an example of a transmission coefficient according to the positional relationship between a first wearable device and a second wearable device, according to one embodiment.

[0026] FIG. 11c illustrates an example of a graph showing the strength of a received RF signal according to a gesture, according to one embodiment.

[0027] FIG. 11d illustrates an example of a graph showing the strength of a received RF signal according to a gesture, according to one embodiment.

[0028] FIG. 12 illustrates an example of a graph for representing the RSSI for an RF signal received by a first wearable device according to one embodiment.

[0029] FIG. 13 illustrates a flowchart regarding the operation of a first wearable device for recognizing a user's gesture according to one embodiment.

[0030] FIG. 14a illustrates an example of the operation of a first wearable device and a second wearable device according to one embodiment.

[0031] FIG. 14b illustrates an example of the operation of a first wearable device and a second wearable device according to one embodiment.

[0032] FIG. 15a illustrates an example of an artificial intelligence model according to one embodiment.

[0033] FIG. 15b illustrates an example of a confusion matrix for an artificial intelligence model according to one embodiment.

[0034] FIG. 16 illustrates a flowchart regarding the operation of a first wearable device for recognizing a user's gesture according to one embodiment.

[0035] Hereinafter, embodiments of the present disclosure are described in detail with reference to the drawings so that those skilled in the art can easily practice them. However, the present disclosure may be embodied in various different forms and is not limited to the embodiments described herein. In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components. Furthermore, in the drawings and related descriptions, descriptions of well-known functions and configurations may be omitted for clarity and brevity.

[0036] FIG. 1 is a block diagram of an electronic device in a network environment according to one embodiment.

[0037] Referring to FIG. 1, in a network environment (100), an electronic device (101) may communicate with an electronic device (102) through a first network (198) (e.g., a short-range wireless communication network) or with at least one of an electronic device (104) or a server (108) through a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) through a server (108). According to one embodiment, the electronic device (101) may include a processor (120), memory (130), input module (150), sound output module (155), display module (160), audio module (170), sensor module (176), interface (177), connection terminal (178), haptic module (179), camera module (180), power management module (188), battery (189), communication module (190), subscriber identification module (196), or antenna module (197). In some embodiments, at least one of these components (e.g., connection terminal (178)) may be omitted from the electronic device (101), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (176), camera module (180), or antenna module (197)) may be integrated into a single component (e.g., display module (160)).

[0038] The processor (120) can control at least one other component (e.g., a hardware or software component) of the electronic device (101) connected to the processor (120) by executing software (e.g., a program (140)), and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (120) can store commands or data received from other components (e.g., a sensor module (176) or a communication module (190)) in volatile memory (132), process the commands or data stored in volatile memory (132), and store the resulting data in non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., a central processing unit or an application processor) or an auxiliary processor (123) that can operate independently or together with it (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor). For example, if the electronic device (101) includes a main processor (121) and an auxiliary processor (123), the auxiliary processor (123) may be configured to use lower power than the main processor (121) or to be specialized for a designated function. The auxiliary processor (123) may be implemented separately from the main processor (121) or as part thereof.

[0039] The auxiliary processor (123) may control at least some of the functions or states associated with at least one component of the electronic device (101) (e.g., display module (160), sensor module (176), or communication module (190)) on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (123) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (180) or communication module (190)). According to one embodiment, the auxiliary processor (123) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or through a separate server (e.g., server (108)). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers.An artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to the hardware structure, an artificial intelligence model may include a software structure, either additionally or substantially.

[0040] The memory (130) can store various data used by at least one component of the electronic device (101) (e.g., processor (120) or sensor module (176)). The data may include, for example, input data or output data for software (e.g., program (140)) and related commands. The memory (130) may include volatile memory (132) or non-volatile memory (134).

[0041] The program (140) may be stored as software in memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0042] The input module (150) can receive commands or data to be used for a component of the electronic device (101) (e.g., processor (120)) from outside the electronic device (101) (e.g., user). The input module (150) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0043] The sound output module (155) can output a sound signal to the outside of the electronic device (101). The sound output module (155) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0044] The display module (160) can visually provide information to an external (e.g., user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0045] The audio module (170) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150) or output sound through the sound output module (155) or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (101).

[0046] The sensor module (176) can detect the operating state of the electronic device (101) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (176) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0047] The interface (177) may support one or more specified protocols that can be used for the electronic device (101) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (102)). According to one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0048] The connection terminal (178) may include a connector through which the electronic device (101) can be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0049] The haptic module (179) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that the user can perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module (179) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0050] The camera module (180) can capture still images and video. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0051] The power management module (188) can manage power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0052] The battery (189) can supply power to at least one component of the electronic device (101). According to one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0053] The communication module (190) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may include one or more communication processors that operate independently of the processor (120) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (194) (e.g., LAN (local area network) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device (104) through a first network (198) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (199) (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can identify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (196).

[0054] The wireless communication module (192) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. NR access technology can support high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and connection of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low-latency communications (URLLC)). The wireless communication module (192) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (192) can support various technologies for securing performance in the high-frequency band, such as beamforming, massive MIMO (multiple-input and multiple-output), full-dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large-scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), external electronic device (e.g., electronic device (104)), or network system (e.g., second network (199)). According to one embodiment, the wireless communication module (192) can support a Peak data rate (e.g., 20 Gbps or more) for realizing eMBB, loss coverage (e.g., 164 dB or less) for realizing mMTC, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) for realizing URLLC.

[0055] An antenna module (197) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (197) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as a first network (198) or a second network (199), may be selected from the plurality of antennas, for example, by a communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (197).

[0056] According to various embodiments, the antenna module (197) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0057] At least some of the above components can be connected to each other via a communication method between peripheral devices (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and exchange signals (e.g., commands or data) with each other.

[0058] According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) through a server (108) connected to a second network (199). Each of the external electronic devices (102, or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations performed on the electronic device (101) may be performed on one or more of the external electronic devices (102, 104, or 108). For example, if the electronic device (101) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (101) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (101) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device (104) or the server (108) may be included within the second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0059] FIGS. 2a and 2b illustrate perspective views of an electronic device that is an example according to one embodiment.

[0060] Referring to FIGS. 2a and 2b, an electronic device (200) according to one embodiment (e.g., electronic device (101) of FIG. 1) may include a housing (210) comprising a first surface (or front) (210A), a second surface (or rear) (210B), and a side (210C) surrounding the space between the first surface (210A) and the second surface (210B), and a fastening member (250, 260) connected to at least a part of the housing (210) and configured to detachably fasten the electronic device (200) to a part of a user's body (e.g., wrist or ankle). In another embodiment (not shown), the housing may refer to a structure forming some of the first surface (210A), the second surface (210B), and the side (210C) of FIGS. 2a and 2b. According to one embodiment, the first surface (210A) may be formed by a front plate (201) in which at least a portion is substantially transparent (e.g., a glass plate containing various coating layers, or a polymer plate). The second surface (210B) may be formed by a rear plate (207) in which it is substantially opaque. The rear plate (207) may be formed by, for example, coated or colored glass, ceramic, polymer, metal (e.g., aluminum, stainless steel (STS), or magnesium), or a combination of at least two of the above materials. The side surface (210C) may be formed by a side bezel structure (or “side member”) (206) comprising metal and / or polymer, which is combined with the front plate (201) and the rear plate (207). In some embodiments, the rear plate (207) and the side bezel structure (206) may be formed integrally and may comprise the same material (e.g., a metallic material such as aluminum). The above-mentioned connecting members (250, 260) can be formed in various materials and shapes. They can be formed such that an integral and a plurality of unit links are movable with each other by means of woven fabric, leather, rubber, urethane, metal, ceramic, or a combination of at least two of the above materials.

[0061] According to one embodiment, the electronic device (200) may include at least one of a display (220, see FIG. 3), an audio module (205, 208), a sensor module (211), a key input device (202, 203, 204), and a connector hole (209). In some embodiments, the electronic device (200) may omit at least one of the components (e.g., a key input device (202, 203, 204), a connector hole (209), or a sensor module (211)) or additionally include other components.

[0062] The display (220) may be visually exposed, for example, through a significant portion of the front plate (201). The shape of the display (220) may correspond to the shape of the front plate (201) and may be various shapes such as circular, elliptical, or polygonal. The display (220) may be combined with or placed adjacent to a touch detection circuit, a pressure sensor capable of measuring the intensity (pressure) of the touch, and / or a fingerprint sensor.

[0063] The audio module (205, 208) may include a microphone hole (205) and a speaker hole (208). A microphone for acquiring external sound may be placed inside the microphone hole (205), and in some embodiments, a plurality of microphones may be placed to detect the direction of sound. The speaker hole (208) may be used as an external speaker and a receiver for calls. In some embodiments, the speaker hole (208) and the microphone hole (205) may be implemented as a single hole, or a speaker may be included without the speaker hole (208) (e.g., a piezo speaker).

[0064] The sensor module (211) can generate an electrical signal or data value corresponding to an internal operating state of the electronic device (200) or an external environmental state. The sensor module (211) may include, for example, a biosensor module (211) (e.g., HRM sensor) disposed on the second surface (210B) of the housing (210). The electronic device (200) may further include at least one of the sensor modules not illustrated, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0065] The sensor module (211) may include electrode regions (213, 214) forming part of the surface of the electronic device (200) and a biosignal detection circuit (not shown) electrically connected to the electrode regions (213, 214). For example, the electrode regions (213, 214) may include a first electrode region (213) and a second electrode region (214) disposed on a second surface (210B) of the housing (210). The sensor module (211) may be configured such that the electrode regions (213, 214) acquire an electrical signal from a part of the user's body, and the biosignal detection circuit detects the user's biosignal information based on the electrical signal.

[0066] The key input device (202, 203, 204) may include a wheel key (202) disposed on a first surface (210A) of the housing (210) and rotatable in at least one direction, and / or a side key button (203, 204) disposed on a side (210C) of the housing (210). The wheel key may have a shape corresponding to the shape of the front plate (201). In another embodiment, the electronic device (200) may not include some or all of the aforementioned key input devices (202, 203, 204), and the key input devices (202, 203, 204) that are not included may be implemented in other forms, such as soft keys, on the display (220). The connector hole (209) may include other connector holes (not shown) that can accommodate a connector (e.g., a USB connector) for transmitting and receiving power and / or data with an external electronic device and a connector for transmitting and receiving audio signals with an external electronic device. The electronic device (200) may further include a connector cover (not shown) that covers at least a portion of the connector hole (209) and blocks the entry of external foreign matter into the connector hole.

[0067] The fastening member (250, 260) can be detachably fastened to at least a portion of the housing (210) using a locking member (251, 261). The fastening member (250, 260) may include one or more of a fixing member (252), a fixing member fastening hole (253), a band guide member (254), and a band fixing ring (255).

[0068] The fixing member (252) may be configured to fix the housing (210) and the fastening member (250, 260) to a part of the user's body (e.g., wrist or ankle). The fixing member fastening hole (253) may fix the housing (210) and the fastening member (250, 260) to a part of the user's body in correspondence with the fixing member (252). The band guide member (254) may be configured to limit the range of movement of the fixing member (252) when the fixing member (252) is fastened to the fixing member fastening hole (253), thereby allowing the fastening member (250, 260) to be fastened in close contact with a part of the user's body. The band fixing ring (255) may limit the range of movement of the fastening member (250, 260) when the fixing member (252) and the fixing member fastening hole (253) are fastened.

[0069] FIG. 3 shows an exploded perspective view of an exemplary electronic device according to one embodiment.

[0070] Referring to FIG. 3, an electronic device (300) (e.g., electronic device (101) of FIG. 1, or electronic device (200) of FIG. 2a to 2b) may include a side bezel structure (310), a wheel key (320) (e.g., wheel key (202) of FIG. 2), a front plate (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 plate (393) (e.g., rear plate (207) of FIG. 2), and a fastening member (395, 397) (e.g., fastening member (250, 260) of FIG. 2). At least one of the components of the electronic device (300) may be identical or similar to at least one of the components of the electronic device (200) of FIG. 1 or FIG. 2a to 2b, and redundant descriptions are omitted below. The support member (360) may be disposed inside the electronic device (300) and connected to the side bezel structure (310), or may be formed integrally with the side bezel structure (310). The support member (360) may be formed, for example, from a metal material and / or a non-metal (e.g., polymer) material. The support member (360) may have a display (220) attached to one side and a printed circuit board (380) attached to the other side. The printed circuit board (380) may be equipped with a processor, memory, and / or an interface. The processor may include, for example, one or more of a central processing unit, a GPU (graphic processing unit), an application processor, a sensor processor, or a communication processor.

[0071] The memory may include, for example, volatile memory or non-volatile memory. The interface may include, for example, an HDMI (high definition multimedia interface), a USB (universal serial bus) interface, an SD card interface, and / or an audio interface. The interface may, for example, 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.

[0072] The battery (370) is a device for supplying power to at least one component of the electronic device (300) and may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell. At least a portion of the battery (370) may be disposed substantially coplanar with, for example, a printed circuit board (380). The battery (370) may be disposed integrally within the electronic device (200) or may be disposed detachably from the electronic device (200).

[0073] The first antenna (350) may be positioned 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 magnetic secure transmission (MST) antenna. The first antenna (350) may, for example, communicate near field with an external device, wirelessly transmit and receive power required for charging, and transmit a magnetic-based signal including a near field communication signal or payment data. In another embodiment, the antenna structure may be formed by a part of the side bezel structure (310) and / or a combination thereof of the support member (360).

[0074] A second antenna (355) may be positioned between the printed circuit board (380) and the back plate (393). The second antenna (355) may include, for example, a near field communication (NFC) antenna, a wireless charging antenna, and / or a magnetic secure transmission (MST) antenna. The second antenna (355) may, for example, communicate near field with an external device, wirelessly transmit and receive power required for charging, and transmit a magnetic-based signal including a near field communication signal or payment data. In other embodiments, the antenna structure may be formed by a part of the side bezel structure (310) and / or the back plate (393) or a combination thereof.

[0075] The sealing member (390) may be positioned between the side bezel structure (310) and the rear plate (393). The sealing member (390) may be configured to block moisture and foreign matter from entering the space enclosed by the side bezel structure (310) and the rear plate (393) from the outside.

[0076] FIG. 4a shows a perspective view of an exemplary electronic device according to one embodiment.

[0077] Referring to FIG. 4a, an electronic device (400) (e.g., the electronic device (101) of FIG. 1) may include a housing (401) comprising a first surface (411) facing a part of the user's body (e.g., a finger) and a second surface (412) opposite to the first surface (411). For example, the electronic device (400) may include a ring-shaped housing (401). As an example, the electronic device (400) may be formed in a ring shape.

[0078] According to one embodiment, the electronic device (400) may be referred to as a wearable device that can be worn by a user. The electronic device (400) may be worn on a part of the user's body (e.g., a finger). For example, the electronic device (400) may be worn on a part of the user's body. For example, the electronic device (400) may be fastened to a part of the user's body. For example, the electronic device (400) may be detachable from a part of the user's body. For example, the electronic device (400) may have a shape corresponding to a part of the user's body in order to be worn on a part of the user's body.

[0079] For example, the electronic device (400) may come into contact with a part of the user's body by being worn by the user. For example, the electronic device (400) may be configured to obtain information about the user through a part of the user's body by being worn by the user. For example, the information about the user may include the user's health information. However, it is not limited thereto. For example, the electronic device (400) may provide information about the user through the electronic device (400) and / or an external electronic device connected to the electronic device (400). However, it is not limited thereto.

[0080] According to one embodiment, at least a portion of the first surface (411) may come into contact with a portion of the user's body when the electronic device (400) is worn by the user. For example, the first surface (411) may surround a portion of the user's body where the electronic device (400) is worn. For example, the first surface (411) may cover a portion of the user's body where the electronic device (400) is worn. For example, the first surface (411) may be configured so that the electronic device (400) is secured to a portion of the body by pressurizing a portion of the user's body when the electronic device (400) is worn by the user. For example, the first surface (411) may be deformable by a portion of the user's body. For example, the electronic device (400) may provide information about the user through the first surface (411) based on haptic technology.

[0081] For example, the second surface (412) can form the exterior of the electronic device (400) together with the first surface (411). For example, the second surface (412) can form a ring-shaped housing (401) together with the first surface (411). For example, the second surface (412) may be a surface spaced apart from a part of the user's body when the electronic device (400) is worn by the user. For example, the first surface (411) may be referred to as the inner circumference surface of the housing (401). The second surface (412), opposite to the first surface (411), may be referred to as the outer circumference surface of the housing (401).

[0082] For example, the second surface (412) may be exposed to the outside while the electronic device (400) is worn by the user. The second surface (412) may include at least one of titanium, stainless steel, and ceramic. The second surface (412) may include a material for protection against external impact and / or scratches. According to an embodiment, the second surface (412) may be coated with an additional material to protect the color and / or appearance of the electronic device (400).

[0083] For example, the first surface (411) may include the same and / or similar material as the second surface (412). According to an embodiment, at least a portion of the first surface (411) may include at least one of a molding material for acquiring data, a transparent plastic, and / or glass. According to an embodiment, at least a portion of the first surface (411) may be formed of a metal for identifying biosignals.

[0084] According to one embodiment, the electronic device (400) may further include a hole (470) formed by a first surface (411) to allow a part of the user's body to pass through when the electronic device (400) is worn by the user. For example, the hole (470) may be penetrated by a part of the user's body when the electronic device (400) is worn by the user. By including a hole (470) configured to allow said part of the user's body to pass through, the electronic device (400) may be configured to be fastened to a part of the user's body when the user wears the electronic device (400).

[0085] According to one embodiment, the electronic device (400) may further include one or more components between the first surface (411) and the second surface (412). For example, the electronic device (400) may include a communication circuit, one or more sensors, and / or a processor between the first surface (411) and the second surface (412). The arrangement of one or more components will be described later in FIG. 4b.

[0086] FIG. 4b is an example of a partial cross-sectional view of an electronic device according to one embodiment.

[0087] Referring to FIG. 4b, the electronic device (400) may be formed in a ring shape. For example, the housing (401) of the electronic device (400) may be formed in the shape of a ring that can be worn on a user's finger. FIG. 4a and FIG. 4b illustrate an electronic device (400) in a ring shape with a smooth surface as an example, but are not limited thereto. For example, the electronic device (400) may be implemented as a housing comprising a plurality of planes. For example, an electronic device (400) in a ring shape with a non-smooth surface may also be understood as an embodiment of the present disclosure.

[0088] According to one embodiment, the ring-shaped housing (401) may include a first surface (411) that contacts the user's body when worn by the user, a second surface (412) that is exposed to the outside, and a side between the first surface (411) and the second surface (412). For example, the space between the first surface (411) and the second surface (412) may include a space for including (or placing) at least one component (e.g., a processor (410), a communication circuit (420), a sensor (430), and / or a memory (440)).

[0089] According to one embodiment, a PCB (451) may be placed between a first surface (411) and a second surface (412) of an electronic device (400). For example, a processor (410), a communication circuit (420), an accelerometer (431), a gyroscope (432), a PPG sensor (433), a temperature sensor (434), a memory (440), and / or a PMIC (454) may be placed on the PCB (451). For example, the PCB (451) may include a rigid region and a flexible region. For example, the rigid region may be referred to as a rigid flexible printed circuit board (RFPCB). For example, the flexible region may be referred to as a flexible printed circuit board (FPCB).

[0090] For example, the PPG sensor (433) may include one or more light-emitting circuits (433-1), one or more light-receiving circuits (433-2), and a control circuit (433-3). For example, one or more light-emitting circuits (433-1) and one or more light-receiving circuits (433-2) may be positioned toward a first surface (411). For example, the control circuit (433-3) may be positioned toward a second surface (412).

[0091] For example, the PMIC (454) may be used to manage the power of the electronic device (400). The PMIC (454) may be used to provide (or distribute) power to components in the electronic device (400) that require power. The PMIC (454) may support a wired charging method (e.g., terminal, or pogo pin) or a wireless charging method (e.g., WPC (wireless power consortium), or NFC) for charging the electronic device (400) through the charging interface (453).

[0092] According to one embodiment, a battery (452) may be disposed between a first surface (411) and a second surface (412) of an electronic device (400). The battery (452) may include at least one battery (or battery pack). For example, the battery (452) may be configured such that at least one battery is connected in series and / or parallel. For example, the battery (452) may be formed as a flexible battery pack. For example, the battery (452) may be charged and / or discharged as a secondary battery. For example, the material forming the battery (452) may be varied. For example, the material included in the battery (452) may include at least one of lithium ion and mercury.

[0093] According to one embodiment, an antenna (455) may be disposed between a first surface (411) and a second surface (412) of an electronic device (400). For example, the antenna (455) may include a single antenna and / or a plurality of segmented antennas. According to an embodiment, the antenna (455) may be formed as part of the housing (401) of the electronic device (400). For example, the antenna (455) may be electrically connected to a communication circuit (420) via a PCB (451). Although not illustrated, the electronic device (400) may include a radio frequency (RF) coupler. The RF coupler may be disposed between the antenna (455) and the communication circuit (420). The RF coupler may be configured to acquire a feedback signal while a signal is transmitted and / or received through the antenna (455).

[0094] Although not illustrated, the electronic device (400) may include various additional components in addition to the illustrated components. For example, the electronic device (400) may include a display. The display may be placed on the outer surface of the housing (401).

[0095] According to one embodiment, a first wearable device (e.g., the electronic device (200) of FIG. 2a and 2b or the electronic device (300) of FIG. 3) and a second wearable device (e.g., the electronic device (400) of FIG. 4a and 4b) may be worn on a user's body. For example, the first wearable device may be worn on a first part of the user's body (e.g., the wrist). The second wearable device may be worn on a second part of the user's body (e.g., the finger).

[0096] For example, when a first wearable device and a second wearable device are worn on the same arm, the positional relationship between the first wearable device and the second wearable device may change depending on the movement of the first part and / or the second part of the user's body. The first wearable device can identify the positional relationship between the first wearable device and the second wearable device based on a signal transmitted from the second wearable device. The first wearable device can identify a user's gesture based on the positional relationship between the first wearable device and the second wearable device. In the specification below, a specific example of the first wearable device identifying a user's gesture based on a signal transmitted from the second wearable device will be described.

[0097] FIG. 5 illustrates an example of an environment including a first wearable device and a second wearable device according to one embodiment.

[0098] Referring to FIG. 5, the first wearable device (510) and the second wearable device (520) can operate while being worn by a user. The first wearable device (510) can be worn on a first part of the user's body (e.g., wrist). The second wearable device (520) can be worn on a second part of the user's body (e.g., finger).

[0099] For example, the first wearable device (510) and the second wearable device (520) may be worn on the same arm of the user. For example, the first wearable device (510) and the second wearable device (520) may be worn on the left arm of the user. The first wearable device (510) may be worn on the wrist of the left arm, and the second wearable device (520) may be worn on one of the fingers of the left arm. For example, the first wearable device (510) and the second wearable device (520) may be worn on the right arm of the user. The first wearable device (510) may be worn on the wrist of the right arm, and the second wearable device (520) may be worn on one of the fingers of the right arm.

[0100] According to one embodiment, the first wearable device (510) may correspond to the electronic device (200) of FIGS. 2a and 2b or the electronic device (300) of FIG. 3. The second wearable device (520) may correspond to the electronic device (400) of FIGS. 4a and 4b. For example, the first wearable device (510) may have a watch shape. The second wearable device (520) may have a ring shape.

[0101] For example, the user of the first wearable device (200) and the user of the second wearable device (520) may be the same. The first wearable device (510) and the second wearable device (520) may be owned (or used) by the same user.

[0102] According to one embodiment, the first wearable device (510) may be connected to the second wearable device (520) via wireless communication. For example, the second wearable device (520) may be a device connected to the first wearable device (510) at close range and used by the same user. For example, the first wearable device (510) may control the operation of the second wearable device (520). The user may change the setting information of the second wearable device (520) using the first wearable device (510).

[0103] For example, the first wearable device (510) may request the second wearable device (520) to transmit an RF signal to identify a gesture performed through the user's body (e.g., hand). The second wearable device (520) may transmit an RF signal to the first wearable device (510) based on the reception of the request. The first wearable device (510) may identify the user's gesture based on the received RF signal.

[0104] In the following specification, technical features for identifying a gesture performed by a user's body (e.g., hand) based on an RF signal transmitted from a second wearable device (520) will be described. However, it is not limited thereto. For example, the second wearable device (520) may identify a gesture performed by a user's body (e.g., hand) based on an RF signal transmitted from the first wearable device (510).

[0105] According to an embodiment, the first wearable device (510) and the second wearable device (520) may be connected to an electronic device (530) via wireless communication. The first wearable device (510) may be controlled by the electronic device (530). The second wearable device (520) may be controlled by the electronic device (530). According to an embodiment, at least some or all of the operations of the first wearable device (510) described below may be performed by the electronic device (530). At least some or all of the operations of the second wearable device (520) described below may be performed by the electronic device (530).

[0106] FIG. 6 illustrates an example of a simplified block diagram of a first wearable device and a second wearable device according to one embodiment.

[0107] Referring to FIG. 6, the second wearable device (520) can operate in a state connected to the first wearable device (510) via wireless communication. For example, the first wearable device (510) can be used to control the second wearable device (520).

[0108] For example, the first wearable device (510) may be worn on a first part of the user's body (e.g., wrist). The second wearable device (520) may be worn on a second part of the user's body (e.g., finger).

[0109] According to one embodiment, the first wearable device (510) may include a processor (511), a memory (512), and / or a communication circuit (513). According to an embodiment, the first wearable device (510) may include at least one of the processor (511), the memory (512), and the communication circuit (513). For example, at least some of the processor (511), the memory (512), and the communication circuit (513) may be omitted according to an embodiment.

[0110] According to one embodiment, the processor (511) may correspond to the processor (120) of FIG. 1. The processor (511) may be operatively coupled with or connected with the memory (512) and the communication circuit (513). That the processor (511) is operatively coupled with or connected with the memory (512) and the communication circuit (513) may mean that the processor (511) can control the display (312), the memory (512), and the communication circuit (513). For example, the display (312), the memory (512), and the communication circuit (513) may be controlled by the processor (511).

[0111] Although illustrated based on different blocks, the embodiment is not limited thereto, and some of the hardware of FIG. 6 (e.g., processor (511), and at least some of the communication circuit (513) and memory (512)) may be included in a single integrated circuit such as a system on a chip (SoC).

[0112] According to one embodiment, the processor (511) may be formed as at least one processor. For example, the processor (511) may be formed as a main processor that performs high-performance processing and an auxiliary processor that performs low-power processing.

[0113] According to one embodiment, the processor (511) may include a hardware component for processing data based on one or more instructions. The hardware component for processing data may include, for example, an arithmetic and logic unit (ALU), a field programmable gate array (FPGA), and / or a central processing unit (CPU).

[0114] For example, the processor (511) may include an application processor, a supplementary processor (e.g., a sensor hub, an MCU (microcontroller unit)), a CPU (central processor unit), an NPU (neural processing unit), a GPU (graphic processing unit), and / or a processor for IoT (e.g., a processor integrated with a communication module).

[0115] According to one embodiment, the first wearable device (510) may include a memory (512). The memory (512) may be used to store information or data. For example, the memory (512) may be used to store data (or information) received from the second wearable device (520). For example, the memory (512) may correspond to the memory (130) of FIG. 1. For example, the memory (512) may be a volatile memory unit or units. For example, the memory (512) may be a non-volatile memory unit or units. For example, the memory (512) may be another form of computer-readable medium, such as a magnetic or optical disk. For example, the memory (512) may store data acquired based on an operation performed by the processor (511) (e.g., an algorithm execution operation). According to an embodiment, the memory (512) may be formed in a form integrated with the processor (511).

[0116] According to one embodiment, the first wearable device (510) may include a communication circuit (513). The communication circuit (513) may correspond to at least a part of the communication module (190) of FIG. 1. For example, the communication circuit (513) may be used for various radio access technologies (RAT). For example, the communication circuit (513) may be used to perform Bluetooth communication, wireless local area network (WLAN) communication, Zigbee communication, near field communication (NFC), ultra-wideband (UWB) communication, ultra-wideband (UWB) communication, or ANT+ communication. For example, the communication circuit (513) may be used to perform cellular communication. For example, the processor (511) may establish a connection with another electronic device (e.g., the second wearable device (520)) through the communication circuit (513). For example, the processor (511) can identify (or measure) the location of the first wearable device (510) based on a received or transmitted wireless signal (e.g., a GPS (global positioning system) signal) using a communication circuit (513). According to an embodiment, the communication circuit (513) may be formed to be integrated with the processor (511).

[0117] For example, the communication circuit (513) may support multiple frequency bands. The communication circuit (513) may support at least one of a 2.4 GHz band, a 5 GHz band, a 6 GHz band, and / or an 8 GHz band. For example, at least one of the 2.4 GHz band, the 5 GHz band, and the 6 GHz band may be used for wireless LAN communication. For example, the 2.4 GHz band may be used for BLE (Bluetooth Low Energy) (or Bluetooth) communication. For example, the 2.4 GHz band and / or the 8 GHz band may be used for UWB communication.

[0118] According to one embodiment, the processor (511) of the first wearable device (510) can determine a frequency band for communicating with the second wearable device (520) among a plurality of frequency bands. For example, the processor (511) can determine a frequency band for communicating with the second wearable device (520) among a plurality of frequency bands based on a communication environment. For example, the processor (511) can determine a communication technique for communicating with the second wearable device (520).

[0119] According to one embodiment, the first wearable device (510) may include various additional components in addition to the components shown in FIG. 6. For example, the second wearable device (510) may include a display or at least one sensor (e.g., an accelerometer, a gyroscope, or a biosensor).

[0120] According to one embodiment, the second wearable device (520) may include a processor (521), a memory (522), a communication circuit (523), and / or an RF coupler (524). According to an embodiment, the second wearable device (520) may include at least one of a processor (521), a memory (522), a communication circuit (523), and an RF coupler (524). For example, at least some of the processor (521), the memory (522), the communication circuit (523), and the RF coupler (524) may be omitted according to an embodiment.

[0121] According to one embodiment, the second wearable device (520) may include a processor (521). For example, the processor (521) may correspond to the processor (120) of FIG. 1. The processor (521) may be operatively coupled with or connected with the memory (522) and the communication circuit (523). That the processor (521) is operatively coupled with or connected with the memory (522) and the communication circuit (523) may mean that the processor (521) can control the memory (522) and the communication circuit (523). For example, the memory (522) and the communication circuit (523) may be controlled by the processor (521).

[0122] According to one embodiment, the processor (521) may include at least one processor. For example, the processor (521) may include a main processor that performs high-performance processing and an auxiliary processor that performs low-power processing. At least some of the sensors (322) may be connected to the auxiliary processor. At least some of the sensors connected to the auxiliary processor may acquire data regarding the user for 24 hours. According to one embodiment, one of the main processor and the auxiliary processor may be activated depending on the state and / or operation of the second wearable device (520). For example, the auxiliary processor may be activated when the battery of the second wearable device (520) is low. For example, the main processor may be activated when accurate data regarding the user is required.

[0123] According to one embodiment, the second wearable device (520) may include a memory (522). For example, the memory (522) may correspond to the memory (130) of FIG. 1. For example, the memory (522) may correspond to the memory (512) of the first wearable device (510).

[0124] According to one embodiment, the second wearable device (520) may include a communication circuit (523). For example, the communication circuit (523) may correspond to at least a part of the communication module (190) of FIG. 1. For example, the communication circuit (523) may correspond to the communication circuit (513) of the first wearable device (510).

[0125] According to one embodiment, the second wearable device (520) may include an RF coupler (524) connected to a communication circuit (523). For example, the RF coupler (524) may be used to obtain a feedback signal while a signal is transmitted and / or received through a conductive part (or antenna). For example, the RF coupler (524) may be configured to obtain a feedback signal while a feed signal is provided to the conductive part through a feed part. Specific examples of the RF coupler (524) will be described later in FIG. 7.

[0126] According to one embodiment, the second wearable device (520) may include various additional components in addition to the components shown in FIG. 6. For example, the second wearable device (520) may include at least one sensor (e.g., an accelerometer, a gyroscope, or a biosensor).

[0127] FIG. 7 illustrates an example of the operation of a first wearable device and a second wearable device according to one embodiment.

[0128] Referring to FIG. 7, the first wearable device (510) may include at least one antenna (701) connected to a communication circuit (513). The second wearable device (520) may include at least one antenna (702) connected to a communication circuit (523). For example, the at least one antenna (701) may include at least one conductive part (or conductive pattern) placed on the first wearable device (510). The at least one antenna (702) may include at least one conductive part (or conductive pattern) placed on the second wearable device (520).

[0129] According to one embodiment, the second wearable device (520) may include an RF coupler (524) disposed between at least one antenna (702) and a communication circuit (523) (or a front-end module). For example, a processor (521) of the second wearable device (520) may obtain a feedback signal through the RF coupler (524) while a signal is transmitted and / or received through at least one antenna (702). For example, the RF coupler (524) may obtain a feedback signal based on the transmission (or radiation) of a signal through at least one antenna (702). The RF coupler (524) may provide a feedback signal to the communication circuit (523). The communication circuit (523) may obtain information regarding impedance characteristics through the feedback signal. For example, the information regarding impedance characteristics may include at least one S-parameter. For example, information regarding impedance characteristics may include information regarding the reflection coefficient (S11).

[0130] According to one embodiment, the second wearable device (520) (or the processor (521) of the second wearable device (520)) may transmit an RF signal containing information regarding impedance characteristics to the first wearable device (510). The first wearable device (510) may receive the RF signal transmitted from the second wearable device (520) using at least one antenna (701). For example, the information regarding impedance characteristics may change according to the posture (or gesture) of the user's body.

[0131] For example, the processor (511) can obtain first information regarding the strength of an RF signal received from a second wearable device (520) using a communication circuit (513). For example, the first information regarding the strength of the RF signal may include information about the received signal strength indicator (RSSI) and / or information about the rate of change of the RSSI.

[0132] For example, the first wearable device (510) (or the processor (511) of the first wearable device (510)) can obtain second information regarding the impedance characteristics of the second wearable device (520) based on an RF signal received from the second wearable device (520) using a communication circuit (513).

[0133] According to one embodiment, the processor (511) can identify a gesture (or posture of the user) performed through the user's body based on first information regarding the strength of an RF signal and / or second information regarding the impedance characteristics of a second wearable device (520).

[0134] In FIGS. 8 to 12, technical features for identifying a gesture (or posture of the user) performed through the user's body based on first information regarding the strength of an RF signal will be described.

[0135] In FIGS. 13 to 16, technical features for recognizing a gesture (or posture of the user) performed through the user's body will be described based on first information regarding the strength of an RF signal and / or second information regarding the impedance characteristics of a second wearable device (520).

[0136] FIG. 8 illustrates a flowchart regarding the operation of a first wearable device for recognizing a user's gesture according to one embodiment. In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0137] Referring to FIG. 8, in operation 801, the first wearable device (510) (or the processor (511) of the first wearable device (510)) may receive an RF signal for identifying a gesture from the second wearable device (520). For example, the first wearable device (510) worn on a first part of the user's body (e.g., wrist) may receive, through a communication circuit (513), an RF signal for identifying a gesture performed through the user's body from the second wearable device (520) worn on a second part of the user's body, based on the movement of the user's body, within a reference time interval.

[0138] According to one embodiment, the first wearable device (510) can identify an input for executing a function for gesture recognition. Based on the input, the first wearable device (510) can request the second wearable device (520) to transmit an RF signal. Based on the request, the first wearable device (510) can receive the RF signal transmitted from the second wearable device (520).

[0139] According to one embodiment, the first wearable device (510) can receive an RF signal within a reference time interval. For example, while the movement of the user's body is performed within the reference time interval, the first wearable device (510) can receive an RF signal.

[0140] In operation 802, the first wearable device (510) can identify first information regarding the strength of an RF signal. For example, the first wearable device (510) can identify first information regarding the strength of an RF signal based on an RF signal received within a reference time interval. For example, the first information regarding the strength of an RF signal may include information regarding the received signal strength indicator (RSSI) of the RF signal and / or information regarding the rate of change of the RSSI. For example, the first information regarding the strength of an RF signal may include information regarding S parameters. As an example, the first information regarding the strength of an RF signal may include information regarding a transmission coefficient (S21).

[0141] In operation 803, the first wearable device (510) can recognize a user's gesture based on the first information. For example, the first wearable device (510) can recognize (or identify) a gesture performed within a reference time interval based on the first information.

[0142] According to one embodiment, the first wearable device (510) may store information regarding the strength of an RF signal (or a change in the strength of an RF signal) according to a user's gesture in memory (512). For example, the first wearable device (510) may store information regarding the strength of an RF signal (or a change in the strength of an RF signal) according to a user's gesture in memory (512) based on log data (or history data). In one embodiment, the first wearable device (510) may generate a table regarding a user's gesture according to the strength of an RF signal (or a change in the strength of an RF signal). The first wearable device (510) may identify a user's gesture based on the generated table and the first information.

[0143] According to one embodiment, the first wearable device (510) may include an artificial intelligence model. For example, the first wearable device (510) may identify (or acquire) information regarding the strength of an RF signal (or a change in the strength of an RF signal) according to a user's gesture based on log data (or history data). The first wearable device (510) may train the artificial intelligence model based on information regarding the strength of an RF signal (or a change in the strength of an RF signal) according to a user's gesture. For example, the first wearable device (510) may set the first information as input data for the artificial intelligence model. The first wearable device (510) may input the first information into the artificial intelligence model. The first wearable device (510) may set the user's gesture as output data for the artificial intelligence model. The first wearable device (510) may recognize the user's gesture based on the output of the artificial intelligence model.

[0144] In operation 804, the first wearable device (510) can perform at least one function corresponding to the recognized gesture. For example, the first wearable device (510) can perform at least one function specified according to the recognized gesture. For example, the first wearable device (510) can transmit a signal to control the electronic device (530) based on the recognized gesture. For example, the first wearable device (510) can transmit information regarding the recognized gesture to the electronic device (530).

[0145] For example, the recognized gesture can be used to control a media playback application. Based on the recognized gesture, a playback function (or pause function) can be performed. For example, the recognized gesture can be used to control a stopwatch application. Based on the recognized gesture, a stopwatch pause function (or resume function) can be performed. For example, the recognized gesture can be used to perform a click function. Based on the recognized gesture, a click function of an activated icon on the watch face can be performed. For example, the recognized gesture can be used to perform a scroll function. Based on the recognized gesture, a screen scroll function of the display of the first wearable device (510) or the display of the electronic device (530) can be performed.

[0146] According to one embodiment, in operations 801 to 804, an operation for the first wearable device (510) to perform at least one function corresponding to a recognized gesture based on the first information has been described, but is not limited thereto. According to an embodiment, the second wearable device (520) may perform operations 801 to 804.

[0147] According to one embodiment, the first wearable device (510) may transmit first information to the electronic device (530). The electronic device (530) may recognize a user's gesture based on the first information. The electronic device (530) may perform at least one function corresponding to the recognized gesture. For example, an artificial intelligence model may be included in the electronic device (530) (or in the memory of the electronic device (530)). The first wearable device (510) may transmit first information to the electronic device (530). The electronic device (530) may identify a user's gesture based on the first information using an artificial intelligence model.

[0148] FIG. 9a illustrates an example of a first Fresnel zone (FFZ) defined through a first wearable device and a second wearable device according to one embodiment.

[0149] FIG. 9b illustrates an example of a first Fresnel zone (FFZ) defined through a first wearable device and a second wearable device according to one embodiment.

[0150] FIG. 9c illustrates an example of a first Fresnel zone (FFZ) defined through a first wearable device and a second wearable device according to one embodiment.

[0151] Referring to FIGS. 9a through 9c, an ellipse focusing on the first wearable device (510) and the second wearable device (520) may be defined. For example, an ellipse (910) to ellipse (930) including a path between the first wearable device (510) and the second wearable device (520) may be defined. The ellipse (910) may be defined based on a first frequency within a first frequency band (e.g., 2.4 GHz band). The ellipse (920) may be defined based on a second frequency within a second frequency band (e.g., 5 GHz band). The ellipse (930) may be defined based on a third frequency within a third frequency band (e.g., 8 GHz band). The ellipses (910) to ellipses (930) may be defined on the yz plane.

[0152] Referring to the ellipse (910), the distance (901) may correspond to the distance between the first wearable device (510) and the second wearable device (520). The distance (902) may correspond to the distance from a point on the ellipse (910) to the first wearable device (510). The distance (903) may correspond to the distance from the said point on the ellipse (910) to the second wearable device (520). For example, the sum of the distance (902) and the distance (903) may be set to be greater than the distance (901) by half the wavelength according to the first frequency. As described above, the ellipse (920) and the ellipse (930) may be defined. For example, each of the ellipses (910) to (930) may be referred to as the first Fresnel zone (FFZ).

[0153] Within the ellipse (910), most of the electromagnetic energy of the first frequency band (or the first frequency) can be transmitted. Within the ellipse (920), most of the electromagnetic energy of the second frequency band (or the second frequency) can be transmitted. Within the ellipse (930), most of the electromagnetic energy of the third frequency band (or the third frequency) can be transmitted. Accordingly, if the area occupied by an obstacle within the ellipse (910) to the ellipse (930) is large, the reception sensitivity of the signal identified by the first wearable device (510) may be lowered. If the area occupied by the user's body within the ellipse (910) to the ellipse (930) is large, the reception sensitivity of the signal identified by the first wearable device (510) may be lowered.

[0154] While the posture (952) illustrated in FIG. 9b is being performed, the area occupied by the user's body within the ellipse (910) to the ellipse (930) may be larger compared to other postures. While the posture (953) illustrated in FIG. 9c is being performed, the area occupied by the user's body within the ellipse (910) to the ellipse (930) may be smaller compared to other postures.

[0155] The size of the area occupied by the user's body within the ellipse (910) to the ellipse (930) while the posture (952) is being performed may be larger than the size of the area occupied by the user's body within the ellipse (910) to the ellipse (930) while the posture (951) shown in FIG. 9a is being performed.

[0156] The size of the area occupied by the user's body within the ellipse (910) to the ellipse (930) while the posture (953) is being performed may be smaller than the size of the area occupied by the user's body within the ellipse (910) to the ellipse (930) while the posture (951) shown in FIG. 9a is being performed.

[0157] As described above, depending on the user's posture, the size of the area occupied by the user's body within the ellipse (910) to the ellipse (930) may change. Since the user's body acts as an obstacle in the path of the signal, the reception sensitivity of the signal identified by the first wearable device (510) may change depending on the user's posture. Accordingly, the first wearable device (510) can identify (or recognize) a gesture (or posture of the user's body) performed through the user's body based on the strength of the RF signal received from the second wearable device (520).

[0158] As described above, the ellipse (910) to the ellipse (930) may change in size or shape depending on the frequency (or frequency band). Since the size of the body varies depending on the user, the first wearable device (510) can determine the frequency (or frequency band) of the signal for recognizing the user's gesture. For example, the second wearable device (520) can transmit a reference signal through each of the plurality of frequencies. The first wearable device (510) can identify the reference signal received through each of the plurality of frequencies. Among the plurality of frequencies, the first wearable device (510) can determine the frequency of the reference signal having the largest amount of change according to the user's movement as the frequency of the signal for recognizing the user's gesture. For example, when the first wearable device (510) and the second wearable device (520) are worn on the body of the first user, if the reference signal of the first frequency among the plurality of frequencies changes most significantly according to the movement of the first user, the frequency of the signal used to recognize the gesture of the first user can be determined as the first frequency. For example, when the first wearable device (510) and the second wearable device (520) are worn on the body of the second user, if the reference signal of the second frequency among the plurality of frequencies changes most significantly according to the movement of the second user, the frequency of the signal used to recognize the gesture of the second user can be determined as the second frequency.

[0159] FIG. 10a illustrates an example of the positional relationship between a first wearable device and a second wearable device according to one embodiment.

[0160] FIG. 10b illustrates an example of a transmission coefficient according to the positional relationship between a first wearable device and a second wearable device, according to one embodiment.

[0161] FIG. 10c illustrates an example of a graph showing the strength of a received RF signal according to one embodiment.

[0162] FIG. 10d illustrates an example of a graph showing the strength of a received RF signal according to one embodiment.

[0163] FIG. 10e illustrates an example of a graph showing the strength of a received RF signal according to a gesture, according to one embodiment.

[0164] Referring to FIG. 10a, a first wearable device (510) and a second wearable device (520) may be worn on a user's body. The first wearable device (510) may be worn on a first part of the user's body (e.g., wrist). The second wearable device (520) may be worn on a second part of the user's body (e.g., finger).

[0165] For example, while the user's posture corresponds to posture (1010), the position of the first wearable device (510) may correspond to position (1001). The position of the second wearable device (520) may correspond to position (1002). Position (1005) may correspond to the position of the wrist joint. The distance between position (1001) and position (1005) may be distance (1011). The distance between position (1005) and position (1002) may be distance (1012).

[0166] According to one embodiment, the user's hand may be rotated counterclockwise around the user's wrist joint. For example, the user's posture may change from posture (1010) to posture (1020). Based on the user's posture changing from posture (1010) to posture (1020), the position of the second wearable device (520) may change from position (1002) to position (1003). For example, the distance between position (1005) and position (1003) may be distance (1012).

[0167] For example, while the user's posture is maintained in posture (1020), the second wearable device (520) can transmit an RF signal to the first wearable device (510). The first wearable device (510) can receive the RF signal. As illustrated in FIG. 9c, when the user's posture changes from posture (1010) to posture (1020), the size of the area occupied by the user's body within the FFZ, defined by position (1001), position (1003), and the frequency of the RF signal, may decrease. Accordingly, the reception sensitivity of the RF signal received by the first wearable device (510) may increase.

[0168] According to one embodiment, the user's hand may be rotated clockwise around the user's wrist joint. For example, the user's posture may change from posture (1010) to posture (1030). Based on the user's posture changing from posture (1010) to posture (1030), the position of the second wearable device (520) may change from position (1002) to position (1004). For example, the distance between position (1005) and position (1004) may be distance (1012).

[0169] For example, while the user's posture is maintained in posture (1030), the second wearable device (520) can transmit an RF signal to the first wearable device (510). The first wearable device (510) can receive the RF signal. As illustrated in FIG. 9b, when the user's posture changes from posture (1010) to posture (1030), the size of the area occupied by the user's body within the FFZ, defined by position (1001), position (1004), and the frequency of the RF signal, may increase. Accordingly, the reception sensitivity of the RF signal received by the first wearable device (510) may decrease.

[0170] Referring to FIG. 10b, graph (1041) shows the change in the transmission coefficient (S21) according to frequency when the second wearable device (520) transmits an RF signal to the first wearable device (510) while the user's posture is posture (1010). Graph (1042) shows the change in the transmission coefficient (S21) according to frequency when the second wearable device (520) transmits an RF signal to the first wearable device (510) while the user's posture is posture (1020). Graph (1043) shows the change in the transmission coefficient (S21) according to frequency when the second wearable device (520) transmits an RF signal to the first wearable device (510) while the user's posture is posture (1030).

[0171] Referring to graphs (1041) to (1043), when an RF signal in the approximately 2.4 GHz band is transmitted, the change in the transmission coefficient (S21) may be greatest depending on the user's posture. Therefore, the frequency band of the RF signal transmitted between the first wearable device (510) and the second wearable device (520) can be determined to be the approximately 2.4 GHz band. The first wearable device (510) can set the frequency band of the RF signal transmitted from the second wearable device (520) to the approximately 2.4 GHz band.

[0172] For example, when an RF signal of approximately 2.45 GHz is transmitted from the second wearable device (520) to the first wearable device (510), the transmission coefficient (S21) measured while the user's posture is posture (1010) may be approximately -53 [dB]. For example, when an RF signal of approximately 2.45 GHz is transmitted from the second wearable device (520) to the first wearable device (510), the transmission coefficient (S21) measured while the user's posture is posture (1020) may be approximately -43 [dB]. For example, when an RF signal of approximately 2.45 GHz is transmitted from the second wearable device (520) to the first wearable device (510), the transmission coefficient (S21) measured while the user's posture is posture (1030) may be approximately -57 [dB].

[0173] For example, since the transmission coefficient (S21) represents the transmission gain, the transmission coefficient (S21) may be proportional to the strength of the RF signal (e.g., RSSI) measured at the first wearable device (510).

[0174] Referring to FIG. 10c, while the user's first gesture is being performed, the second wearable device (520) can transmit an RF signal to the first wearable device (510). Graph (1051) shows the change in the strength of the RF signal received by the first wearable device (510) while the user's first gesture is being performed. For example, the first gesture may be performed from time point (1061) to time point (1063).

[0175] The first wearable device (510) can identify the strength of the RF signal as strength (1091) at time point (1061). The first wearable device (510) can identify the strength of the RF signal as strength (1092) at time point (1062). The first wearable device (510) can identify the strength of the RF signal as strength (1091) at time point (1063).

[0176] The first wearable device (510) can identify that the user's posture has changed from posture (1010) to posture (1020) based on identifying that the strength of the RF signal has changed from strength (1091) to strength (1092).

[0177] The first wearable device (510) can identify that the user's posture has changed from posture (1020) to posture (1010) based on identifying that the strength of the RF signal has changed from strength (1092) to strength (1091).

[0178] The first wearable device (510) can identify that the user has performed a first gesture of raising and lowering the hand using the wrist based on a change in the strength of an RF signal such as a graph (1051).

[0179] Referring to FIG. 10d, while the user's second gesture is being performed, the second wearable device (520) can transmit an RF signal to the first wearable device (510). Graph (1052) shows the change in the strength of the RF signal received by the first wearable device (510) while the user's second gesture is being performed. For example, the second gesture may be performed from time point (1064) to time point (1066).

[0180] The first wearable device (510) can identify the strength of the RF signal as strength (1091) at time point (1064). The first wearable device (510) can identify the strength of the RF signal as strength (1093) at time point (1065). The first wearable device (510) can identify the strength of the RF signal as strength (1091) at time point (1066).

[0181] The first wearable device (510) can identify that the user's posture has changed from posture (1010) to posture (1030) based on identifying that the strength of the RF signal has changed from strength (1091) to strength (1093).

[0182] The first wearable device (510) can identify that the user's posture has changed from posture (1030) to posture (1010) based on identifying that the strength of the RF signal has changed from strength (1093) to strength (1091).

[0183] The first wearable device (510) can identify that the user has performed a second gesture of lowering and raising the hand using the wrist based on a change in the strength of an RF signal such as a graph (1052).

[0184] Referring to FIG. 10e, while the user's third gesture is being performed, the second wearable device (520) can transmit an RF signal to the first wearable device (510). Graph (1053) shows the change in the strength of the RF signal received by the first wearable device (510) while the user's third gesture is being performed. For example, the third gesture may be performed from time point (1081) to time point (1085).

[0185] The first wearable device (510) can identify the strength of the RF signal as strength (1091) at time point (1081). The first wearable device (510) can identify the strength of the RF signal as strength (1093) at time point (1082). The first wearable device (510) can identify the strength of the RF signal as strength (1091) at time point (1083). The first wearable device (510) can identify the strength of the RF signal as strength (1093) at time point (1084). The first wearable device (510) can identify the strength of the RF signal as strength (1091) at time point (1085).

[0186] The first wearable device (510) can identify that the user's posture has changed from posture (1010) to posture (1030) based on identifying that the strength of the RF signal has changed from strength (1091) to strength (1093).

[0187] The first wearable device (510) can identify that the user's posture has changed from posture (1030) to posture (1010) based on identifying that the strength of the RF signal has changed from strength (1093) to strength (1091).

[0188] The first wearable device (510) can identify that the user has performed a third gesture of lowering and raising the hand twice using the wrist, based on a change in the strength of an RF signal such as a graph (1053).

[0189] FIG. 11a illustrates an example of the positional relationship between a first wearable device and a second wearable device according to one embodiment.

[0190] FIG. 11b illustrates an example of a transmission coefficient according to the positional relationship between a first wearable device and a second wearable device, according to one embodiment.

[0191] FIG. 11c illustrates an example of a graph showing the strength of a received RF signal according to a gesture, according to one embodiment.

[0192] FIG. 11d illustrates an example of a graph showing the strength of a received RF signal according to a gesture, according to one embodiment.

[0193] Referring to FIG. 11a, a first wearable device (510) and a second wearable device (520) may be worn on a user's body. The first wearable device (510) may be worn on a first part of the user's body (e.g., wrist). The second wearable device (520) may be worn on a second part of the user's body (e.g., finger).

[0194] For example, while the user's posture corresponds to posture (1110), the position of the first wearable device (510) may correspond to position (1101). The position of the second wearable device (520) may correspond to position (1102). Position (1105) may correspond to the position of the first joint of the finger. The distance between position (1101) and position (1105) may be distance (1111). The distance between position (1105) and position (1102) may be distance (1112).

[0195] According to one embodiment, the user's hand may be rotated clockwise around the user's finger joint. For example, the user's posture may change from posture (1110) to posture (1120). Based on the user's posture changing from posture (1110) to posture (1120), the position of the second wearable device (520) may change from position (1102) to position (1103). For example, the distance between position (1105) and position (1103) may be distance (1112).

[0196] For example, while the user's posture is maintained in posture (1120), the second wearable device (520) can transmit an RF signal to the first wearable device (510). The first wearable device (510) can receive the RF signal. When the user's posture changes from posture (1110) to posture (1120), the size of the area occupied by the user's body within the FFZ defined by position (1101), position (1103), and the frequency of the RF signal may increase. Accordingly, the reception sensitivity of the RF signal received by the first wearable device (510) may decrease.

[0197] Referring to FIG. 11b, graph (1141) shows the change in the transmission coefficient (S21) according to frequency when the second wearable device (520) transmits an RF signal to the first wearable device (510) while the user's posture is posture (1110). Graph (1142) shows the change in the transmission coefficient (S21) according to frequency when the second wearable device (520) transmits an RF signal to the first wearable device (510) while the user's posture is an intermediate posture (not shown) between posture (1110) and posture (1120). Graph (1143) shows the change in the transmission coefficient (S21) according to frequency when the second wearable device (520) transmits an RF signal to the first wearable device (510) while the user's posture is posture (1120).

[0198] Referring to graphs (1141) to (1143), when an RF signal in the approximately 2.4 GHz band is transmitted, the change in the transmission coefficient (S21) may be greatest depending on the user's posture. Therefore, the frequency band of the RF signal transmitted between the first wearable device (510) and the second wearable device (520) can be determined to be the approximately 2.4 GHz band. The first wearable device (510) can set the frequency band of the RF signal transmitted from the second wearable device (520) to the inverse 2.4 GHz band.

[0199] For example, when an RF signal of about 2.45 GHz is transmitted from the second wearable device (520) to the first wearable device (510), the transmission coefficient (S21) measured while the user's posture is posture (1110) may be about -56 [dB]. For example, when an RF signal of about 2.45 GHz is transmitted from the second wearable device (520) to the first wearable device (510), the transmission coefficient (S21) measured while the user's posture is an intermediate posture (not shown) between posture (1110) and posture (1120) may be about -62 [dB]. For example, when an RF signal of about 2.45 GHz is transmitted from the second wearable device (520) to the first wearable device (510), the transmission coefficient (S21) measured while the user's posture is posture (1120) may be about -69 [dB].

[0200] For example, since the transmission coefficient (S21) represents the transmission gain, the transmission coefficient (S21) may be proportional to the strength of the RF signal (e.g., RSSI) measured at the first wearable device (510).

[0201] Referring to FIG. 11c, while the user's first gesture is being performed, the second wearable device (520) can transmit an RF signal to the first wearable device (510). Graph (1151) shows the change in the strength of the RF signal received by the first wearable device (510) while the user's first gesture is being performed. For example, the first gesture may be performed from time point (1161) to time point (1163).

[0202] The first wearable device (510) can identify the strength of the RF signal as strength (1191) at time point (1161). The first wearable device (510) can identify the strength of the RF signal as strength (1192) at time point (1162). The first wearable device (510) can identify the strength of the RF signal as strength (1191) at time point (1163).

[0203] The first wearable device (510) can identify that the user's posture has changed from posture (1110) to posture (1120) based on identifying that the strength of the RF signal has changed from strength (1191) to strength (1192).

[0204] The first wearable device (510) can identify that the user's posture has changed from posture (1120) to posture (1110) based on identifying that the strength of the RF signal has changed from strength (1192) to strength (1191).

[0205] The first wearable device (510) can identify that the user has performed a first gesture of lowering and raising the finger using the joint of the finger based on a change in the strength of an RF signal such as a graph (1151).

[0206] Referring to FIG. 11d, while the user's second gesture is being performed, the second wearable device (520) can transmit an RF signal to the first wearable device (510). Graph (1152) shows the change in the strength of the RF signal received by the first wearable device (510) while the user's second gesture is being performed. For example, the second gesture may be performed from time point (1181) to time point (1185).

[0207] The first wearable device (510) can identify the strength of the RF signal as strength (1191) at time point (1181). The first wearable device (510) can identify the strength of the RF signal as strength (1192) at time point (1182). The first wearable device (510) can identify the strength of the RF signal as strength (1191) at time point (1183). The first wearable device (510) can identify the strength of the RF signal as strength (1192) at time point (1184). The first wearable device (510) can identify the strength of the RF signal as strength (1191) at time point (1185).

[0208] The first wearable device (510) can identify that the user's posture has changed from posture (1110) to posture (1120) based on identifying that the strength of the RF signal has changed from strength (1191) to strength (1192).

[0209] The first wearable device (510) can identify that the user's posture has changed from posture (1120) to posture (1110) based on identifying that the strength of the RF signal has changed from strength (1192) to strength (1191).

[0210] The first wearable device (510) can identify that the user has performed a second gesture of lowering and raising the finger twice using the joints of the finger, based on a change in the strength of an RF signal such as a graph (1153).

[0211] FIG. 12 illustrates an example of a graph for representing the RSSI for an RF signal received by a first wearable device according to one embodiment.

[0212] Referring to FIG. 12, a first wearable device (510) worn on a first part of a user's body (e.g., wrist) can receive an RF signal from a second wearable device (520) worn on a second part of a user's body (e.g., finger). The first wearable device (510) can identify (or measure) the RSSI for the RF signal.

[0213] According to one embodiment, a graph (1210) represents the RSSI for an RF signal according to a user's gesture (or posture). Referring to the graph (1210), while the user's posture is posture (1211), the RSSI may be within the range (1221). While the user's posture is posture (1212), the RSSI may be within the range (1222). While the user's posture is posture (1213), the RSSI may be within the range (1223).

[0214] For example, the first wearable device (510) can identify that the RSSI for the RF signal transmitted from the second wearable device (520) is within the range (1221) during the time interval (1231), the time interval (1233), and the time interval (1235). The first wearable device (510) can recognize (or identify) that the posture of the user's body is posture (1211) within the time interval (1231), the time interval (1233), and the time interval (1235).

[0215] For example, the first wearable device (510) can identify that the RSSI for the RF signal transmitted from the second wearable device (520) is within the range (1222) during the time interval (1232) and the time interval (1236). The first wearable device (510) can recognize (or identify) that the posture of the user's body is posture (1212) within the time interval (1232) and the time interval (1236).

[0216] For example, the first wearable device (510) can identify that the RSSI for the RF signal transmitted from the second wearable device (520) is within the range (1223) during the time interval (1234). The first wearable device (510) can recognize (or identify) that the posture of the user's body is posture (1213) within the time interval (1234).

[0217] For example, the first wearable device (510) can identify that the user's body posture changes from posture (1211) to posture (1212) within time intervals (1241) and (1245). The first wearable device (510) can identify the user's gestures according to the change in the user's body posture.

[0218] For example, the first wearable device (510) can identify that the user's body posture changes from posture (1212) to posture (1211) within a time interval (1242). The first wearable device (510) can identify the user's gestures according to the change in the user's body posture.

[0219] For example, the first wearable device (510) can identify that the user's body posture changes from posture (1211) to posture (1213) within a time interval (1243). The first wearable device (510) can identify the user's gestures in response to the change in the user's body posture.

[0220] For example, the first wearable device (510) can identify that the user's body posture changes from posture (1213) to posture (1211) within a time interval (1244). The first wearable device (510) can identify the user's gestures in response to the change in the user's body posture.

[0221] FIG. 13 illustrates a flowchart regarding the operation of a first wearable device for recognizing a user's gesture according to one embodiment. In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0222] In operation 1301, the first wearable device (510) (or the processor (511) of the first wearable device (510)) may receive an RF signal for identifying a gesture from the second wearable device (520). For example, the first wearable device (510) worn on a first part of the user's body (e.g., wrist) may receive, through a communication circuit (513), an RF signal for identifying a gesture performed through the user's body from the second wearable device (520) worn on a second part of the user's body (e.g., finger) based on the movement of the user's body, within a reference time interval. Operation 1310 may correspond to operation 801 of FIG. 8.

[0223] In operation 1302, the first wearable device (510) can identify first information regarding the strength of an RF signal and second information regarding the impedance characteristics of the second wearable device (520). For example, the first wearable device (510) can identify first information regarding the strength of a received RF signal and second information regarding the impedance characteristics of the second wearable device (520) included in the received RF signal.

[0224] According to one embodiment, the first wearable device (510) can identify first information regarding the strength of an RF signal. For example, the operation of identifying first information regarding the strength of an RF signal may correspond to operation 802 of FIG. 8.

[0225] According to one embodiment, the RF signal may include second information regarding the impedance characteristics of the second wearable device (520). The second information regarding the impedance characteristics of the second wearable device (520) may be included in the payload of the RF signal. The first wearable device (510) may identify (or acquire) the second information regarding the impedance characteristics of the second wearable device (520) based on the RF signal.

[0226] According to one embodiment, the second wearable device (520) may transmit an RF signal containing second information regarding impedance characteristics to the first wearable device (510). For example, the second information regarding impedance characteristics may be identified within a reference time interval. The second wearable device (520) may obtain the second information regarding impedance characteristics by using an RF coupler (524). The second wearable device (520) may transmit an RF signal containing the second information to the first wearable device (510). The first wearable device (510) may receive an RF signal containing the second information from the second wearable device (520).

[0227] For example, the second information regarding impedance characteristics may include information regarding the reflection coefficient (S11) identified using the RF coupler (524) of the second wearable device (520).

[0228] In operation 1303, the first wearable device (510) can recognize a user's gesture based on the first information and / or the second information. For example, the first wearable device (510) can recognize a gesture performed within a reference time interval based on the user's body movement based on the first information and / or the second information.

[0229] Unlike operation 803 of FIG. 8, the first wearable device (510) can recognize a user's gesture based on the first information and / or the second information.

[0230] For example, depending on the posture of the user's body, the second information regarding the impedance characteristics of the second wearable device (520) may change. For example, depending on the posture of the user's body, the part of the user's body that comes into contact with the antenna (or conductive part) of the second wearable device (520) may change. Accordingly, the second information regarding the impedance characteristics of the second wearable device (520) may change. The first wearable device (510) may use the second information regarding the impedance characteristics of the second wearable device (520) to recognize the user's gesture.

[0231] According to one embodiment, the first wearable device (510) may store information regarding the strength of an RF signal (or a change in the strength of an RF signal) according to a user's gesture and information regarding the impedance characteristics of the second wearable device (520) in the memory (512). For example, the first wearable device (510) may store information regarding the strength of an RF signal (or a change in the strength of an RF signal) according to a user's gesture and / or information regarding the impedance characteristics of the second wearable device (520) in the memory (512) based on log data (or history data). The first wearable device (510) may generate a table regarding the user's gesture according to the strength of the RF signal (or a change in the strength of the RF signal) and / or the impedance characteristics of the second wearable device (520). The first wearable device (510) can identify a user's gesture based on a generated table, first information, and / or second information.

[0232] According to one embodiment, the memory (512) of the first wearable device (510) may include an artificial intelligence model. For example, the first wearable device (510) may identify (or acquire) information regarding the strength of an RF signal (or change in the strength of an RF signal) according to a user's gesture and information regarding the impedance characteristics of the second wearable device (520) based on log data (or history data). The first wearable device (510) may train the artificial intelligence model based on information regarding the strength of an RF signal (or change in the strength of an RF signal) according to a user's gesture and information regarding the impedance characteristics of the second wearable device (520). For example, the first wearable device (510) may set the first information and the second information as input data for the artificial intelligence model. The first wearable device (510) may input the first information and the second information into the artificial intelligence model. The first wearable device (510) can set the user's gesture as output data of an artificial intelligence model. The first wearable device (510) can recognize the user's gesture based on the output of the artificial intelligence model.

[0233] According to an embodiment, the first wearable device (510) can recognize a user's gesture based on at least one of the first information and the second information. For example, the first wearable device (510) can recognize a user's gesture based on the first information, such as operation 803 of FIG. 8. For example, the first wearable device (510) may also recognize a user's gesture based on the second information regarding the impedance characteristics of the second wearable device (520).

[0234] In operation 1304, the first wearable device (510) can perform at least one function corresponding to the recognized gesture. For example, the first wearable device (510) can perform at least one function specified according to the recognized gesture. As an example, the first wearable device (510) can transmit a signal to control an electronic device (530) based on the recognized gesture. Operation 1304 may correspond to operation 804 of FIG. 8.

[0235] FIG. 14a illustrates an example of the operation of a first wearable device and a second wearable device according to one embodiment.

[0236] FIG. 14b illustrates an example of the operation of a first wearable device and a second wearable device according to one embodiment.

[0237] Referring to FIGS. 14a and 14b, a first wearable device (510) and a second wearable device (520) may be worn on a user's body. The first wearable device (510) may be worn on a first part of the user's body (e.g., wrist). The second wearable device (520) may be worn on a second part of the user's body (e.g., finger). The second wearable device (520) may transmit an RF signal to the first wearable device (510) to identify a gesture performed through the user's body (e.g., hand). The second wearable device (520) may transmit an RF signal to the first wearable device (510) that includes second information regarding the impedance characteristics of the second wearable device (520). For example, the second information regarding the impedance characteristics of the second wearable device (520) may include a reflection coefficient (S11). As an example, the second wearable device (520) may identify contact with a third part of the user's body (e.g., thumb) while being worn on a second part of the user's body (e.g., index finger). The second wearable device (520) may identify a changed impedance characteristic based on contact with the third part. The second wearable device (520) may acquire the second information regarding the impedance characteristics and transmit an RF signal containing the second information to the first wearable device (510). The second wearable device (520) may identify a change in the user's posture based on a change in the impedance characteristics identified in the posture (1410), as illustrated in FIGS. 14a and 14b.

[0238] Referring to FIG. 14a, the user's posture can be changed from posture (1410) to posture (1420). For example, the user can perform gesture 1. When the user's posture is changed from posture (1410) to posture (1420), the strength of the RF signal (e.g., RSSI) received by the first wearable device (510) can be increased. When the user's posture is changed from posture (1410) to posture (1420), the impedance characteristics (e.g., reflection coefficient (S11)) of the second wearable device (520) can be changed.

[0239] Referring to FIG. 14b, the user's posture can be changed from posture (1410) to posture (1430). For example, the user can perform gesture 2. When the user's posture is changed from posture (1410) to posture (1430), the strength of the RF signal (e.g., RSSI) received by the first wearable device (510) may be reduced. When the user's posture is changed from posture (1410) to posture (1430), the impedance characteristics (e.g., reflection coefficient (S11)) of the second wearable device (520) may be changed.

[0240] Referring to FIGS. 14a and 14b, the first information regarding the strength of the RF signal and the second information regarding the impedance characteristics of the second wearable device (520) may change depending on the user's posture. Accordingly, the first wearable device (510) can recognize (or identify) the user's gesture (or posture) based on at least one of the first information regarding the strength of the RF signal and the second information regarding the impedance characteristics of the second wearable device (520).

[0241] FIG. 15a illustrates an example of an artificial intelligence model according to one embodiment.

[0242] FIG. 15b illustrates an example of a confusion matrix for an artificial intelligence model according to one embodiment.

[0243] Referring to FIG. 15a, first information regarding the strength of an RF signal and / or second information regarding the impedance characteristics of a second wearable device (520) can be set as input data for an artificial intelligence model (1500). Gestures performed through the user's body can be obtained based on the output of the artificial intelligence model (1500).

[0244] For example, the first information regarding the strength of an RF signal may include information regarding the received signal strength indicator (RSSI) of the RF signal or information regarding the rate of change of said RSSI. For example, the second information regarding the impedance characteristics of the second wearable device (520) may include information regarding S-parameters regarding the second wearable device (520). For example, the second information regarding the impedance characteristics of the second wearable device (520) may include at least one of a reflection coefficient (S11), a transmission coefficient (S21), a reverse transmission coefficient (S12), and / or an output reflection coefficient (S22).

[0245] According to one embodiment, at least one of the first information and the second information, as well as the user's biometric information and / or the orientation information of the first wearable device (510) or the second wearable device (520), may be set as input data for the artificial intelligence model (1500).

[0246] According to one embodiment, the artificial intelligence model (1500) may be included in the first wearable device (510) and / or the second wearable device (520). For example, the first wearable device (510) may include the artificial intelligence model (1500). For example, the second wearable device (520) may include the artificial intelligence model (1500). For example, the first wearable device (510) may include a portion of the artificial intelligence model (1500). The second wearable device (520) may include the remainder of the artificial intelligence model (1500).

[0247] According to one embodiment, the artificial intelligence model (1500) may be included in an electronic device (530) that is distinct from the first wearable device (510) and the second wearable device (520). For example, the first wearable device (510) may transmit first information and second information to the electronic device (530). Based on the first information and second information, the electronic device (530) may recognize (or identify) a user's gesture using the artificial intelligence model (1500). For example, the first wearable device (510) may transmit the first information to the electronic device (530). The second wearable device (520) may transmit the second information to the electronic device (530). Based on the first information and second information, the electronic device (530) may recognize (or identify) a user's gesture using the artificial intelligence model (1500).

[0248] According to one embodiment, the artificial intelligence model (1500) may be implemented based on at least one of a rule-based model, a pattern-based model and / or a deep model. However, it is not limited thereto.

[0249] For example, the artificial intelligence model (1500) may be implemented based on a generative model (or a generative artificial intelligence model). In one embodiment, the generative model may include a generative model comprising a plurality of parameters related to a neural network having a structure based on an encoder and a decoder, such as a transformer. In one embodiment, the generative model may include a bidirectional model based on learning about an encoder (e.g., BERT (bidirectional encoder representations from transformers)), or an auto-encoding model (e.g., a diffusion model). In one embodiment, the generative model may include an auto-regressor model based on learning about a decoder (e.g., GPT (generative pre-trained transformer)). In one embodiment, the generative model may include a sequence-to-sequence model based on learning of an encoder and a decoder (e.g., stable diffusion, DALL-E 2). In one embodiment, the generative model may include a large language model (LLM) for processing natural language based on massive parameters, but is not limited thereto. The generative model may include parameters for driving neural networks such as a convolutional neural network (CNN), a recurrent neural network (RNN), a feedforward neural network (FNN), and / or a long short-term memory (LSTM).

[0250] Referring to FIG. 15b, an artificial intelligence model (1500) can be trained based on first information and second information. FIG. 15b may show a confusion matrix (1520) regarding the artificial intelligence model (1500).

[0251] For example, the horizontal axis of the confusion matrix (1520) may represent a gesture predicted by an artificial intelligence model. The vertical axis of the confusion matrix (1520) may represent an actual gesture. By referring to the confusion matrix (1520), since both the predicted gesture and the actual gesture match, the artificial intelligence model (1500) can have high accuracy.

[0252] FIG. 16 illustrates a flowchart regarding the operation of a first wearable device for recognizing a user's gesture according to one embodiment. In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0253] Referring to FIG. 16, a user's gesture may consist of a set of one or more sub-gestures. For example, a user's gesture may include a first sub-gesture and at least one second sub-gesture performed consequentially to the first sub-gesture.

[0254] In operation 1601, the first wearable device (510) can recognize a first sub-gesture based on first information regarding the strength of an RF signal and second information regarding the impedance characteristics of the second wearable device (520). For example, within a first time interval of the reference time interval of the first wearable device (510), the first sub-gesture can be recognized based on the first information and the second information.

[0255] According to one embodiment, a first sub-gesture among the user's gestures may be performed within a first time interval of a reference time interval. At least one second sub-gesture among the user's gestures may be performed within a second time interval after the first time interval of the reference time interval.

[0256] For example, the first wearable device (510) may use first information and second information to recognize a first sub-gesture. For example, a user's gesture may start with the first sub-gesture. The first wearable device (510) may receive an RF signal within a first time interval. Based on the RF signal, the first wearable device (510) may identify (or obtain) first information regarding the strength of the signal and second information regarding the impedance characteristics of the second wearable device (520). For example, the first wearable device (510) may recognize (or identify) the first sub-gesture based on both the first information and the second information.

[0257] In operation 1602, the first wearable device (510) can recognize at least one second sub-gesture based on second information regarding the impedance characteristics of the second wearable device (520). For example, the first wearable device (510) can recognize (or identify) at least one second sub-gesture based on the second information within a second time interval following a first time interval among reference time intervals.

[0258] For example, the first wearable device (510) can identify at least one second sub-gesture that is performed sequentially to the first sub-gesture after the first sub-gesture is recognized. The first wearable device (510) can recognize at least one second sub-gesture based on the second information.

[0259] For example, the first wearable device (510) may cease identifying first information regarding the strength of an RF signal based on recognizing a first sub-gesture. For example, the first wearable device (510) may bypass identifying first information regarding the strength of an RF signal based on recognizing a first sub-gesture. For example, the first wearable device (510) may refrain from identifying first information regarding the strength of an RF signal based on recognizing a first sub-gesture.

[0260] The first wearable device (510) can recognize at least one second sub-gesture based on second information regarding the impedance characteristics of the second wearable device (520) within the second time interval without identifying the first information.

[0261] According to an embodiment, the first sub-gesture may correspond to at least one second sub-gesture. For example, a user's gesture may consist of a set of identical sub-gestures. The first wearable device (510) may recognize the first sub-gesture performed among the user's gestures based on the first information and the second information. After recognizing the first sub-gesture performed, the first wearable device (510) may recognize the remaining gestures based on the second information.

[0262] According to one embodiment, a wearable device (e.g., a first wearable device (510)) worn on a first part of a user's body may include a communication circuit (e.g., a communication circuit (513)), a memory (e.g., a memory (512)) including instructions and one or more storage media, and at least one processor (e.g., a processor (511)) including a processing circuit. When the above instructions are executed individually or collectively by the at least one processor, they may receive a radio frequency (RF) signal for identifying a gesture performed through the user's body from another wearable device (e.g., a second wearable device (520)) worn on a second part of the user's body, based on the movement of the user's body, through the communication circuit within a reference time interval, identify first information regarding the strength of the received RF signal and second information regarding the impedance characteristics of the other wearable device included in the received RF signal, and based on the first information and the second information, recognize a gesture performed within the reference time interval according to the movement of the body and cause the wearable device to perform at least one function corresponding to the recognized gesture.

[0263] For example, the second information regarding the impedance characteristics may include information regarding the reflection coefficient identified through the coupler of the other wearable device.

[0264] For example, the first information regarding the strength of the received RF signal may include information regarding the received signal strength indicator (RSSI) of the RF signal or information regarding the rate of change of the RSSI.

[0265] For example, when the above instructions are executed individually or collectively by the at least one processor, they may cause the wearable device to identify an input for executing a function for gesture recognition and, based on the input, request the other wearable device to transmit the RF signal.

[0266] For example, when the above instructions are executed individually or collectively by the at least one processor, the wearable device may be enabled to recognize the gesture performed within the reference time interval using an artificial intelligence model based on the first information and the second information.

[0267] For example, when the above instructions are executed individually or collectively by the at least one processor, the first information and the second information are input into the artificial intelligence model, and based on the output of the artificial intelligence model, the wearable device may be enabled to recognize the gesture performed within the reference time interval.

[0268] For example, the artificial intelligence model may be included in an external electronic device connected to the wearable device.

[0269] For example, the recognized gesture may include a first sub-gesture and at least one second sub-gesture performed consequentially to the first sub-gesture. When the instructions are executed individually or collectively by the at least one processor, the wearable device may be caused to recognize the first sub-gesture based on the first information and the second information within a first time interval of the reference time interval, and to recognize the at least one second sub-gesture based on the second information within a second time interval after the first time interval of the reference time interval.

[0270] For example, the above instructions may cause the wearable device to identify a reference signal received through each of the plurality of frequencies when executed individually or collectively by the at least one processor, and to determine the frequency of the reference signal having the largest amount of change according to the user's movement among the plurality of frequencies as the frequency of the RF signal.

[0271] For example, the first part of the body (or wearable device) and the second part of the body (or other wearable device) may be located within the first Fresnel zone (FFZ) defined based on the determined frequency.

[0272] According to one embodiment, a method performed by a wearable device (e.g., a first wearable device (510)) worn on a first part of a user's body may include: receiving a radio frequency (RF) signal for identifying a gesture performed through the user's body from another wearable device (e.g., a second wearable device (520)) worn on a second part of the user's body, based on the movement of the user's body, through the communication circuit within a reference time interval; identifying first information regarding the strength of the received RF signal and second information regarding the impedance characteristics of the other wearable device included in the received RF signal; recognizing a gesture performed within the reference time interval according to the movement of the body based on the first information and the second information; and performing at least one function corresponding to the recognized gesture.

[0273] For example, the second information regarding the impedance characteristics may include information regarding the reflection coefficient identified through the coupler of the other wearable device.

[0274] For example, the first information regarding the strength of the received RF signal may include information regarding the received signal strength indicator (RSSI) of the RF signal or information regarding the rate of change of the RSSI.

[0275] For example, the above method may include an operation of identifying an input for executing a function for gesture recognition, and an operation of requesting another wearable device to transmit the RF signal based on the input.

[0276] For example, the above method may include an operation of recognizing the gesture performed within the reference time interval using an artificial intelligence model based on the first information and the second information.

[0277] For example, the above method may include the operation of inputting the first information and the second information into the artificial intelligence model, and the operation of recognizing the gesture performed within the reference time interval based on the output of the artificial intelligence model.

[0278] For example, the artificial intelligence model may be included in an external electronic device connected to the wearable device.

[0279] For example, the recognized gesture may include a first sub-gesture and at least one second sub-gesture performed consequentially to the first sub-gesture. The method may include an operation of recognizing the first sub-gesture based on the first information and the second information within a first time interval of the reference time interval, and an operation of recognizing the at least one second sub-gesture based on the second information within a second time interval after the first time interval of the reference time interval.

[0280] For example, the above method may include an operation of identifying a reference signal received through each of a plurality of frequencies, and an operation of determining the frequency of the reference signal having the largest change amount according to the user's movement among the plurality of frequencies as the frequency of the RF signal.

[0281] According to one embodiment, a non-transitory computer-readable storage medium can store one or more programs. The above one or more programs may include instructions that, when executed by at least one processor of a wearable device that is worn on a first part of a user's body and has a communication circuit (e.g., communication circuit (513)), receive a radio frequency (RF) signal for identifying a gesture performed through the user's body from another wearable device worn on a second part of the user's body, based on the movement of the user's body, through the communication circuit within a reference time interval, identify first information regarding the strength of the received RF signal and second information regarding the impedance characteristics of the other wearable device included in the received RF signal, recognize a gesture performed within the reference time interval according to the movement of the body based on the first information and the second information, and cause the wearable device to perform at least one function corresponding to the recognized gesture.

[0282] The electronic device according to the embodiments disclosed in this document may be of various forms. The electronic device may include, for example, a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a consumer electronics device. The electronic device according to the embodiments of this document is not limited to the aforementioned devices.

[0283] The embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, each of 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 of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used simply to distinguish a component from another component and do not limit the components in any other aspect (e.g., importance or order). Where any component (e.g., the first) is referred to as "coupled" or "connected" to another component (e.g., the second), with or without the terms "functionally" or "communicationally," it means that said component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0284] In one embodiment of this document, the term “module” used may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0285] One embodiment of the present document may be implemented as software (e.g., program (140)) comprising one or more instructions stored in a storage medium (e.g., internal memory (136) or external memory (138)) readable by a machine (e.g., electronic device (101)). For example, a processor (e.g., processor (120)) of the machine (e.g., electronic device (101)) may call at least one of the one or more instructions stored in the storage medium and execute it. This enables the machine to be operated to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily.

[0286] According to one embodiment, the method according to the embodiments disclosed herein may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., CD-ROM (compact disc read-only memory)), or distributed online (e.g., download or upload) through an application store (e.g., Play Store™) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0287] According to one embodiment, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to one embodiment, one or more of the components or operations among the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to one embodiment, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. A wearable device worn on a first part of a user's body, Communication circuit; Memory comprising instructions and one or more storage media; and It includes at least one processor including a processing circuit, and When the above instructions are executed individually or collectively by the at least one processor, Based on the movement of the user's body, an RF (radio frequency) signal for identifying a gesture performed through the user's body is received via the communication circuit within a reference time interval from another wearable device worn on a second part of the user's body. Identifying first information regarding the strength of the received RF signal and second information regarding the impedance characteristics of the other wearable device included in the received RF signal, and Based on the first information and the second information, recognize a gesture performed within the reference time interval according to the movement of the body, and Causing the wearable device to perform at least one function corresponding to the above-mentioned recognized gesture, Wearable device.

2. In claim 1, the second information regarding the impedance characteristics is, including information regarding the reflection coefficient identified through the coupler of the other wearable device, Wearable device.

3. In claim 1, the first information regarding the strength of the received RF signal is, Information regarding the RSSI (received signal strength indicator) of the above RF signal or information regarding the rate of change of the above RSSI, Wearable device.

4. In claim 1, when the instructions are executed individually or collectively by the at least one processor, Identify inputs for executing a function for gesture recognition, and Causing the wearable device to request the other wearable device to transmit the RF signal based on the above input, Wearable device.

5. In claim 1, when the instructions are executed individually or collectively by the at least one processor, Based on the first information and the second information, using an artificial intelligence model, causing the wearable device to recognize the gesture performed within the reference time interval, Wearable device.

6. In claim 5, when the instructions are executed individually or collectively by the at least one processor, Input the above first information and the above second information into the above artificial intelligence model, and A wearable device that causes the gesture performed within the reference time interval to be recognized based on the output of the artificial intelligence model, Wearable device.

7. In claim 5, the artificial intelligence model is, Included in an external electronic device connected to the above-mentioned wearable device, Wearable device.

8. In claim 1, the recognized gesture is, It includes a first sub-gesture and at least one second gesture performed consequentially to the first sub-gesture, and When the above instructions are executed individually or collectively by the at least one processor, Within the first time interval of the above reference time interval, the first sub-gesture is recognized based on the first information and the second information, and A wearable device that causes to recognize at least one second sub-gesture based on the second information within the second time interval following the first time interval among the reference time intervals. Wearable device.

9. In claim 1, when the instructions are executed individually or collectively by the at least one processor, Identifying a reference signal received through each of multiple frequencies, and A wearable device that causes the frequency of a reference signal having the largest amount of change according to the user's movement among the plurality of frequencies above to be determined as the frequency of the RF signal. Wearable device.

10. In claim 9, the first part of the body and the second part of the body are, Located within the first Fresnel zone (FFZ) defined based on the above-determined frequency, Wearable device.

11. A method performed by a wearable device worn on a first part of a user's body, The operation of receiving an RF (radio frequency) signal within a reference time interval for identifying a gesture performed through the user's body from another wearable device worn on a second part of the user's body, based on the movement of the user's body; An operation to identify first information regarding the strength of the received RF signal and second information regarding the impedance characteristics of the other wearable device included in the received RF signal; An action of recognizing a gesture performed within the reference time interval according to the movement of the body, based on the first information and the second information; and A motion comprising at least one function corresponding to the above-mentioned recognized gesture, method.

12. In claim 11, the second information regarding the impedance characteristics is, including information regarding the reflection coefficient identified through the coupler of the other wearable device, method.

13. In claim 11, the first information regarding the strength of the received RF signal is, Information regarding the RSSI (received signal strength indicator) of the above RF signal or information regarding the rate of change of the above RSSI, method.

14. In claim 11, the above method is, An action for identifying an input for executing a function for gesture recognition; and Based on the above input, the operation of requesting the other wearable device to transmit the RF signal, method.

15. A non-transitory computer-readable storage medium for storing one or more programs, wherein the one or more programs are executed by at least one processor of a wearable device having a communication circuit and worn on a first part of a user's body, Based on the movement of the user's body, an RF (radio frequency) signal for identifying a gesture performed through the user's body is received via the communication circuit within a reference time interval from another wearable device worn on a second part of the user's body. Identifying first information regarding the strength of the received RF signal and second information regarding the impedance characteristics of the other wearable device included in the received RF signal, and Based on the first information and the second information, recognize a gesture performed within the reference time interval according to the movement of the body, and Instructions comprising causing the wearable device to perform at least one function corresponding to the recognized gesture, Non-transient computer-readable storage media.

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