Electronic device for measuring biometric signal, operation method thereof, and storage medium

Abstract

An electronic device according to one embodiment comprises: a housing; a plurality of sensors disposed inside or outside the housing; an actuator configured to adjust a sensing direction of each of the plurality of sensors; a memory for storing instructions; and at least one processor including a processing circuit, wherein the instructions, when executed individually or collectively by the at least one processor, may instruct the electronic device to acquire situation information, identify information related to the sensing direction of each of the plurality of sensors acquired by inputting the situation information to an artificial intelligence model, and control the actuator to align the sensing direction of each of the plurality of sensors with a blood vessel on the basis of the information related to the sensing direction of each of the plurality of sensors.

Description

Electronic device for measuring biosignals, method of operation thereof, and storage medium

[0001] The present disclosure relates to an electronic device for measuring biosignals, a method of operation thereof, and a storage medium.

[0002] The term "electronic device" may refer to devices that perform specific functions according to an installed program, ranging from home appliances to electronic notebooks, portable multimedia players, mobile communication terminals, tablet PCs (personal computers), video / audio devices, desktop / laptop computers, or in-vehicle navigation systems. For example, these electronic devices can output stored information as sound or video. As the integration density of electronic devices increases and ultra-high-speed, high-capacity wireless communication becomes commonplace, various functions can be integrated into a single electronic device, such as a mobile communication terminal. For example, not only communication functions but also entertainment functions such as games, multimedia functions such as music / video playback, communication and security functions for mobile banking, or functions such as schedule management or electronic wallets are being integrated into a single electronic device.

[0003] Electronic devices are evolving into various forms for user convenience and are becoming smaller so that users can carry them conveniently. For example, a smart ring is a ring-shaped wearable electronic device that can be worn on a user's finger and can provide health-related information by measuring the user's biometric information.

[0004] 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.

[0005] According to one embodiment, the electronic device may include a housing, a plurality of sensors disposed inside or outside the housing, an actuator configured to adjust the sensing direction of each of the plurality of sensors, a memory for storing instructions, and at least one processor including a processing circuit.

[0006] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to acquire situation information.

[0007] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to input the situation information into an artificial intelligence model to verify information related to the sensing direction of each of the plurality of sensors acquired.

[0008] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the actuator to control the sensing direction of each of the plurality of sensors to align the sensing direction of each of the plurality of sensors with the blood vessel based on information related to the sensing direction of each of the plurality of sensors.

[0009] According to one embodiment, the method of operating an electronic device may include an operation of acquiring situation information.

[0010] According to one embodiment, the method of operating an electronic device may include the operation of inputting the situation information into an artificial intelligence model to check information related to the sensing direction of each of the acquired multiple sensors.

[0011] According to one embodiment, the method of operating an electronic device may include controlling an actuator to align the sensing direction of each of the plurality of sensors with a blood vessel based on information related to the sensing direction of each of the plurality of sensors.

[0012] According to one embodiment, in a storage medium for storing computer-readable instructions, the instructions cause the electronic device to perform at least one operation when executed by at least one processor of the electronic device, and the at least one operation may include an operation of acquiring situation information.

[0013] According to one embodiment, in a storage medium for storing computer-readable instructions, the instructions cause the electronic device to perform at least one operation when executed by at least one processor of the electronic device, and the at least one operation may include an operation of checking information related to the sensing direction of each of a plurality of sensors obtained by inputting the situation information into an artificial intelligence model.

[0014] According to one embodiment, in a storage medium for storing computer-readable instructions, the instructions cause the electronic device to perform at least one operation when executed by at least one processor of the electronic device, and the at least one operation may include controlling an actuator to align the sensing direction of each of the plurality of sensors with a blood vessel based on information related to the sensing direction of each of the plurality of sensors.

[0015] The technical problems that the present disclosure aims to solve are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by those skilled in the art from the description below.

[0016] In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0017] FIG. 1 is a block diagram of an electronic device in a network environment according to one embodiment.

[0018] FIG. 2 is a perspective view of an electronic device according to one embodiment.

[0019] FIG. 3 is a cross-sectional view of an electronic device according to one embodiment.

[0020] FIG. 4a is a cross-sectional view of an electronic device according to one embodiment.

[0021] FIG. 4b is a cross-sectional view of an electronic device according to one embodiment.

[0022] FIG. 4c is a cross-sectional view of a finger according to one embodiment.

[0023] FIG. 4d is a cross-sectional view of an electronic device according to one embodiment.

[0024] FIG. 5 is a block diagram of an electronic device according to one embodiment.

[0025] FIG. 6 is a flowchart of an operation for measuring a biosignal in an electronic device according to one embodiment.

[0026] FIG. 7a is a diagram showing the control of an actuator according to one embodiment.

[0027] FIG. 7b is a diagram showing the control of an actuator according to one embodiment.

[0028] FIG. 7c is a diagram showing the control of an actuator according to one embodiment.

[0029] FIG. 8a is a diagram showing the control of an actuator according to one embodiment.

[0030] FIG. 8b is a diagram showing the control of an actuator according to one embodiment.

[0031] FIG. 8c is a diagram showing the control of an actuator according to one embodiment.

[0032] FIG. 9a is a cross-sectional view of an electronic device according to one embodiment.

[0033] FIG. 9b is a drawing showing a sensor of an electronic device according to one embodiment.

[0034] FIG. 9c is a drawing showing a blood vessel image according to one embodiment.

[0035] FIG. 10a is a cross-sectional view of an electronic device according to one embodiment.

[0036] FIG. 10b is a diagram showing the control of an actuator according to one embodiment.

[0037] FIG. 11a is a drawing showing a sensor before alignment according to one embodiment.

[0038] FIG. 11b is a drawing showing the calculation of a tilting angle according to one embodiment.

[0039] FIG. 11c is a drawing showing a sensor after alignment according to one embodiment.

[0040] FIG. 12a is a drawing showing a change in the wearing state according to one embodiment.

[0041] FIG. 12b is a diagram showing sensor realignment according to a change in wearing state, according to one embodiment.

[0042] FIG. 12c is a diagram showing sensor realignment according to a change in wearing state according to one embodiment.

[0043] FIG. 13 is a diagram showing sensor realignment according to user state, according to one embodiment.

[0044] FIG. 14 is a block diagram of an electronic device according to one embodiment.

[0045] FIG. 15 is a block diagram of an electronic device according to one embodiment.

[0046] FIG. 16a is a flowchart of an operation for measuring a biosignal in an electronic device according to one embodiment.

[0047] FIG. 16b is a flowchart of an operation for measuring a biosignal in an electronic device according to one embodiment.

[0048] FIG. 17 is a diagram showing sensor realignment and guide information output according to a change in the wearing state, according to one embodiment.

[0049] FIG. 18a is a diagram showing measurement enhancement according to user activity status according to one embodiment.

[0050] FIG. 18b is a diagram showing measurement enhancement according to user activity status according to one embodiment.

[0051] FIG. 18c is a diagram showing measurement enhancement according to user activity status according to one embodiment.

[0052] 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.

[0053] FIG. 1 is a block diagram of an electronic device (101) in a network environment (100) according to one embodiment.

[0054] 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)).

[0055] 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.

[0056] 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, the artificial intelligence model may include a software structure, either additionally or substantially.

[0057] The number of processors (120) may be one or more. For example, the processor (120) may have the structure of a multi-core processor such as a dual core, a quad core, or a hexa core.

[0058] The processor (120) can control the operations of the electronic device (101) by executing instructions stored in memory (130). For example, the processor (120) may correspond to a plurality of processors that divide and collectively perform a plurality of operations among the processors.

[0059] 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).

[0060] 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).

[0061] 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).

[0062] 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.

[0063] 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.

[0064] 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).

[0065] 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.

[0066] 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.

[0067] 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).

[0068] The haptic module (179) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that can be perceived by the user 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.

[0069] 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.

[0070] 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).

[0071] 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.

[0072] 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).

[0073] 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) may support a Peak data rate (e.g., 20 Gbps or more) for eMBB realization, loss coverage (e.g., 164 dB or less) for mMTC realization, 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 URLLC realization.

[0074] 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).

[0075] 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.

[0076] 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.

[0077] According to one embodiment, commands or data may be transmitted or received between an electronic device (101) and an external electronic device (104) through a server (108) connected to a second network (199). Each of the external electronic devices (102, or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations performed on the electronic device (101) may be performed on one or more of the external electronic devices (102, 104, or 108). For example, if the electronic device (101) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (101) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (101) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device (104) or the server (108) may be included within a second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0078] The embodiments described below describe wearable electronic devices as examples of electronic devices. Additionally, ring-shaped electronic devices are described as examples of wearable electronic devices. However, the embodiments of electronic devices described below are not limited to wearable electronic devices. Furthermore, the embodiments of wearable electronic devices described below are not limited to ring-shaped electronic devices and may include smart watches, smart bracelets, or head-mounted display devices (e.g., AR (augmented reality) glasses, VR (virtual reality) glasses) that can be worn on a user's wrist in the form of a watch.

[0079] FIG. 2 is a perspective view of an electronic device according to one embodiment.

[0080] FIG. 3 is a cross-sectional view of an electronic device according to one embodiment.

[0081] Referring to FIGS. 2 and FIGS. 3, in one embodiment, the electronic device (201) may be included in the electronic device (101) of FIG. 1.

[0082] In one embodiment, an electronic device (201, e.g., a wearable electronic device) may include a housing (210). The housing (210) may form the overall appearance of the electronic device (201).

[0083] In one embodiment, the electronic device (201) may be in the form of a ring. The housing (210) may include an opening configured to receive a user's finger. For example, the opening may be defined as a hole formed in the housing (210).

[0084] In one embodiment, the housing (210) may include an outer housing portion (211) or an inner housing portion (212). The inner housing portion (212) may be coupled to the outer housing portion (211). In one embodiment, the outer housing portion (211) and the inner housing portion (212) may be manufactured separately and assembled, or formed integrally.

[0085] In one embodiment, the outer housing portion (211) may comprise a material capable of withstanding external impact and / or scratches and enabling the implementation of design features. For example, the outer housing portion (211) may comprise at least one of titanium, stainless steel, or ceramic. The outer housing portion (211) may be colored or coated to enable the implementation of the design.

[0086] In one embodiment, the inner housing portion (212) may be a portion that comes into contact with the user's finger when the user wears the electronic device (201). The inner housing portion (212) may be made of a material such as a molding material for sensing, transparent plastic, or glass. For example, the inner housing portion (212) may be configured to be at least partially transparent. For example, the inner housing portion (212) may include a material that allows light to pass through for measuring biometric information. At least a portion of the inner housing portion (212) may be made of a material substantially the same or similar to the outer housing portion (211). Additionally, at least a portion of the inner housing portion (212) may include a metallic material for measuring biometric information.

[0087] In one embodiment, an outer housing portion (211) and an inner housing portion (212) may be combined to provide an internal space of the housing (210). Various electrical / electronic components of the electronic device (201) may be placed and / or mounted in the internal space of the housing (210). For example, the housing (210) may accommodate various electrical / electronic components.

[0088] In one embodiment, the electronic device (201) may include a processor (320) (e.g., the processor (120) of FIG. 1). For example, the processor (320) may be an application processor (AP), a supplementary processor (SP, e.g., a sensor hub), a central processor unit (CPU), a neural processor unit (NPU), a graphic processor unit (GPU), or an Internet of Things (IoT) processor.

[0089] In one embodiment, the electronic device (201) may include a communication module (310). The communication module (310) may include an NFC module and / or a Bluetooth module. However, the communication module included in the communication module (310) is not limited to an NFC module and / or a Bluetooth module.

[0090] In one embodiment, the electronic device (201) may include an antenna (313). The antenna (313) may be an antenna for wireless communication. The antenna (313) may include a single or multiple segmented antennas. A portion of the housing (210) of the electronic device (201) may be utilized as the antenna (313).

[0091] In one embodiment, the electronic device (201) may include a memory (330). The electronic device (201) may store data (e.g., sensing data, communication data) in the memory (330). The memory (330) may be integrated with the processor (320).

[0092] In one embodiment, the electronic device (201) may include a PPG (photoplethysmography) sensor (341, 342, 343). The PPG sensor (341, 342, 343) may be a sensor that receives light absorbed, scattered, or reflected by irradiating light onto a living organism. The electronic device (201) can verify a biological signal by using the PPG sensor (341, 342, 343). One or more light-emitting parts (341) of the PPG sensor emit light of various bands and may be composed of elements such as an LED (light emitting diode), a laser, or a VCSEL (vertical cavity surface emitting laser). The bands of the light-emitting part (341) may include G (green), R (red), and IR (infrared). One or more light-receiving parts (342) of the PPG sensor may receive light that is reflected and / or transmitted by the light irradiated from the light-emitting part (341). A signal (e.g., light) obtained through the light receiving unit (342) can be converted through an analog-to-digital converter (ADC) and stored in a memory (330) or sensor buffer. The light receiving unit (342) can be composed of a photodiode (PD) or a CMOS (complementary metal oxide semiconductor). The control unit (343) of the PPG sensor can be an integrated circuit (IC) or an analog front end (AFE), and can control the light emitting unit (341) and the light receiving unit (342), process the received data, and transmit it to a processor (320) or store it in memory (330).

[0093] In one embodiment, the electronic device (201) may include an inertial sensor (351). The inertial sensor (351) may be a sensor that detects inertia, such as an accelerometer or a gyroscope. The inertial sensor (351) may include only an accelerometer (e.g., a 3-axis sensor) or may include both an accelerometer and a gyroscope (e.g., a 6-axis sensor). By using the inertial sensor (351), the electronic device (201) can sense motion, gesture, impact, posture, and activity (sedentary, moving, sports) of the electronic device (201).

[0094] In one embodiment, the electronic device (201) may include a temperature sensor (352). The temperature sensor (352) may be a sensor that measures the temperature of a body or a part. Depending on the method, the temperature sensor (352) may be contact-type or non-contact-type. A temperature value measured through the temperature sensor (352) may be stored in a memory (330) or transmitted to a processor (320). By using the temperature sensor (352), the electronic device (201) may estimate the temperature of a body (e.g., a user's body temperature), estimate the temperature of the electronic device (201), or perceive the surrounding conditions of the electronic device (201).

[0095] In one embodiment, the electronic device (201) may include a battery (360). The battery (360) may be a device that converts and stores chemical energy into electricity to supply power to the electronic device (201). The battery (360) (e.g., a secondary battery) is charged and discharged and may be configured in various ways depending on the material, such as lithium-ion, mercury, or dry cell. The battery (360) may include a flexible battery pack to correspond to the housing (210). The battery (360) may include a plurality of non-flexible battery packs. The battery (360) may include a flexible battery pack and a non-flexible battery pack.

[0096] In one embodiment, the electronic device (201) may include a charging circuit (370). The charging circuit (370) may be configured to support wired charging (e.g., terminal, pogo pin) and / or wireless charging (e.g., WPC (wireless power consortium), NFC) methods for charging the electronic device (201, e.g., battery (360)). The electronic device (201) may charge the battery (360) through the charging circuit (370).

[0097] In one embodiment, the electronic device (201) may include a power management module (380). The power management module (380) may be a module that manages the power of the electronic device (201). The electronic device (201) can distribute and control power appropriately to a processor (320) and sensors (e.g., 341, 342, 343, 351, 352) through the power management module (380).

[0098] In one embodiment, the electronic device (201) may include a substrate (390). For example, the substrate (390) may be a flexible printed circuit board (FPCB). Various components such as a communication module (310), a processor (320), a memory (330), sensors (e.g., 341, 342, 343, 351, 352), a battery (360), and a power management module (380) may be placed on the substrate (390). Various components placed on the substrate (390) may be electrically connected.

[0099] In one embodiment, the electronic device (201) may include an acoustic output module, a haptic module, a light output module (e.g., a light emitting diode; LED) or other components (399).

[0100] FIG. 4a is a cross-sectional view of an electronic device according to one embodiment.

[0101] Referring to FIG. 4a, an electronic device (400) (e.g., the electronic device (101) of FIG. 1 or the electronic device (201) of FIG. 2) may include a plurality of sensors (401a, 401b, 402a, 402b) disposed outside or inside a housing (e.g., the internal space of a housing (210) in which the outer housing portion (211) and the inner housing portion (212) of FIG. 2 are combined). According to various embodiments, the electronic device (400) may include multi-channel sensors to acquire a biosignal of relatively high intensity (e.g., signal-to-noise ratio (SNR)). For example, the electronic device (400) may include a first light-emitting part (401a), a first light-receiving part (402a), a second light-emitting part (401b), and a second light-receiving part (402b). The light-emitting part of the above sensor may be referred to as a source, and the light-receiving part may be referred to as a detector. The electronic device (400) can obtain a blood vessel signal by irradiating ultrasound of various frequency bands, electrical signals, and light energy of various wavelength bands as a source beam into the blood vessel through the light-emitting part (e.g., a first light-emitting part (401a), a second light-emitting part (401b)), and measuring the corresponding signal generated through the light-receiving part (e.g., a first light-receiving part (402a), a second light-receiving part (402b)). When a user wears the electronic device (400), the location of the blood vessel to be measured may change irregularly depending on the wearing position; therefore, a multi-channel sensor may be used to cover the entire space where the blood vessel exists, or the multi-channel sensor may be moved to align with the blood vessel.

[0102] According to various embodiments, when the sensor is configured as a multi-channel system, the source beam generated from the light-emitting part can cover a wide area even without specifying the location of the blood vessel, making it easier to acquire blood vessel signals compared to a single channel. However, even if the sensor is configured as a multi-channel system, if the light-emitting part and the blood vessel are not aligned, most sensors other than the aligned ones may not be used to acquire biosignals, and there is a limitation in that the signal becomes relatively low relative to the number of sensors used. According to various embodiments, if the entire multi-channel sensor is moved to align with the target, a relatively stronger biosignal can be acquired compared to when it is not aligned. However, if the entire multi-channel sensor is moved to align, individual sensors may not be aligned, resulting in some sensors being discarded because they are still not aligned with the blood vessel, and the efficiency of acquiring biosignals may decrease. For example, even if the device is configured as a multi-channel system to obtain relatively strong biosignals generated from blood vessels during non-invasive biosignal acquisition, if precise alignment between the blood vessel and the sensor is not achieved, the source beam incident on the actual blood vessel may be relatively small compared to the total source output energy. In such cases, not only are the generated vascular signals weak, but unwanted signals from fat, muscle, nerves, and bone located around the blood vessels may also be mixed in during measurement. Consequently, the strength of the received signal (e.g., SNR) is low, measurement efficiency decreases, and the accuracy of acquiring bio-information may be reduced.

[0103] In the various embodiments described below, when acquiring biosignals non-invasively from blood vessels within the body, biosignals can be efficiently measured and corrected based on information obtained from various devices to provide highly accurate biosignals to the user. For example, in the various embodiments described below, high-intensity biosignals can be acquired by using an artificial intelligence model to locate a blood vessel advantageous for acquiring biosignals and aligning a biosignal acquisition sensor to that blood vessel.

[0104] According to various embodiments, if the user's device wearing state changes from the initial sensor alignment state, the electronic device can detect such change by utilizing information from various surrounding sensors through an artificial intelligence model and notify (or provide) the user with notifications and guidance on proper wearing. Additionally, the electronic device can automatically realign the biosignal measurement sensors to match the user's wearing state to maintain the acquisition of relatively high-intensity biosignals. According to various embodiments, in addition to the wearing state, the electronic device can adjust the sensor alignment values ​​by predicting changes in the size and location of blood vessels through analysis of the user's current behavior and physical condition. The high-intensity biosignals acquired in this way can be corrected based on information obtained through surrounding external devices to further enhance signal accuracy and provide various services to the consumer. For example, in the various embodiments described below, a tiltable multi-channel sensor may be placed in the electronic device so that the sensor can be aligned with the blood vessels. In the embodiments described below, the location of blood vessels that changes according to the usage environment and the user's physical characteristics can be automatically tracked and inferred using an artificial intelligence model, and the accuracy of the biosignals can be enhanced through the process of acquiring and correcting high-intensity biosignals.

[0105] FIG. 4b is a cross-sectional view of an electronic device according to one embodiment.

[0106] Referring to FIG. 4b, an electronic device (400, e.g., the electronic device (101) of FIG. 1 or the electronic device (201) of FIG. 2) may include a plurality of sensors (411a, 411b, 412a, 412b, 421a, 421b, 422a, 422b, 431a, 431b, 432a, 432b) disposed in the exterior or interior of a housing (e.g., the interior space of a housing (210) in which the exterior housing portion (211) and the interior housing portion (212) of FIG. 2 are combined). Depending on various embodiments, the electronic device (400) may include multi-channel sensors to acquire a biosignal of relatively high intensity (e.g., signal-to-noise ratio (SNR)). For example, the electronic device (400) may include a first-1 light-emitting part (411a), a first-1 light-receiving part (412a), a second-1 light-emitting part (411b), a second-1 light-receiving part (412b), a first-2 light-emitting part (421a), a first-2 light-receiving part (422a), a second-2 light-emitting part (421b), a second-2 light-receiving part (422b), a first-3 light-emitting part (431a), a first-3 light-receiving part (432a), a second-3 light-emitting part (431b), and a second-3 light-receiving part (432b). The electronic device (400) can obtain a blood vessel signal by irradiating ultrasound of various frequency bands, electrical signals, and light energy of various wavelength bands into the blood vessel through a emitting part (e.g., a first-1 emitting part (411a), a second-1 emitting part (411b), a first-2 emitting part (421a), a second-2 emitting part (421b), a first-3 emitting part (431a), a second-3 emitting part (431b)), and measuring the corresponding signal through a receiving part (e.g., a first-1 receiving part (412a), a second-1 receiving part (412b), a first-2 receiving part (422a), a second-2 receiving part (422b), a first-3 receiving part (432a), a second-3 receiving part (432b)). For convenience of explanation, each emitting part and / or each receiving part will be referred to as a sensor.

[0107] According to various embodiments, the electronic device (400) can image a blood vessel and determine the location of the blood vessel using the aforementioned multi-channel sensors. The electronic device (400) can calculate alignment values ​​for aligning individual sensors to the blood vessel and can correct the alignment values ​​by considering the user's state and surrounding environment information. The electronic device (400) can control the operation of an actuator to align with the blood vessel by adjusting the sensing direction of each of the multiple sensors using the calculated alignment values.

[0108] FIG. 4c is a cross-sectional view of a finger according to one embodiment.

[0109] Referring to FIG. 4c, if the electronic device is a ring-shaped wearable electronic device, the user can obtain biometric information through the blood vessels within the finger by wearing the electronic device on the finger. For example, as shown in FIG. 4c, it can be seen that the first vein (451a), the first artery (451b), the second vein (452a), and the second artery (452b) pass through the cross-section of the finger (450). The electronic device can obtain biometric information by irradiating a source beam onto the first vein (451a) or the second vein (452a) through a sensor and measuring the corresponding signal generated.

[0110] FIG. 4d is a cross-sectional view of an electronic device according to one embodiment.

[0111] Referring to FIG. 4d, since the finger vein located inside the finger (450) is located across two regions to the left and right below the finger bone, it may be advantageous to place the sensor for measuring blood signals (e.g., a light-emitting part and / or a light-receiving part) (first-1 light-emitting part (411a), first-1 light-receiving part (412a), second-1 light-emitting part (411b), second-1 light-receiving part (412b), first-2 light-emitting part (421a), first-2 light-receiving part (422a), second-2 light-emitting part (421b), second-2 light-receiving part (422b), first-3 light-emitting part (431a), first-3 light-receiving part (432a), second-3 light-emitting part (431b), second-3 light-receiving part (432b)) to the left and right below the center of the finger. Since the location of the above blood vessels (e.g., arteries, veins, or nerves) varies slightly from person to person, when measuring biosignals using fixed-position sensors, even if multi-channel sensors are used, there may be sensors that fail to acquire biosignals and are discarded, making it difficult to effectively acquire biosignals.

[0112] FIG. 5 is a block diagram of an electronic device according to one embodiment.

[0113] Referring to FIG. 5, in one embodiment, the electronic device (101) may be included in the electronic device (101) of FIG. 1 or the electronic device (201) of FIG. 2 and FIG. 3. For example, the electronic device (101) may be a ring-shaped smart ring that can be worn on a user's finger, as shown in FIG. 2 and FIG. 3. However, it is not limited thereto. For example, the electronic device (101) may include a smart watch that can be worn on a user's wrist in the form of a watch or a head-mounted display (HMD) that can be worn on a user's head (e.g., AR (augmented reality) glasses, VR (virtual reality) glasses). In the following description, it is assumed that the electronic device (101) is a smart ring, but the operations of the electronic device (101) described below may be applied in at least some of the same or similar ways even if the electronic device (101) is a smart watch or an HMD device.

[0114] In one embodiment, the electronic device (101) may include a communication module (e.g., a communication circuit) (550), a sensor (540), a memory (530), an actuator (560), or a processor (520).

[0115] In one embodiment, the communication module (550) may be included in the communication module (190) of FIG. 1, or the communication module (310) of FIG. 2 and FIG. 3. In one embodiment, the communication module (550) may include an NFC circuit or a Bluetooth circuit. The electronic device (101) may communicate with an external electronic device (102) or server (108) through the communication module (550).

[0116] In one embodiment, a near field communication (NFC) circuit can enable the electronic device (101) and the external electronic device to communicate when the electronic device (101) comes into contact with (or comes into contact with) the external electronic device (e.g., a smartphone). For example, the NFC circuit can enable the electronic device (101) and the external electronic device to communicate as the electronic device (101) comes into contact with the external electronic device within a distance where NFC communication is possible.

[0117] In one embodiment, the electronic device (101) may include another near-field communication circuit capable of performing communication between electronic devices by contactless or contact, in addition to or in place of the NFC circuit. For example, the electronic device (101) may include a magnetic secure transmission (MST) circuit in addition to or in place of the NFC circuit. If the electronic device (101) includes the other near-field communication circuit (e.g., MST circuit), the operation using the NFC circuit described below may be performed using the other near-field communication circuit.

[0118] In one embodiment, the Bluetooth circuit may cause the electronic device (101) to perform Bluetooth communication with an external electronic device. The Bluetooth circuit may support Bluetooth low energy (BLE) communication and / or Bluetooth classic communication.

[0119] In one embodiment, the sensor (540) may be included in the sensor module (176) of FIG. 1. The sensor may include at least one of the sensors of FIG. 4b or FIG. 4d (e.g., a light-emitting part and / or a light-receiving part) (a first-1 light-emitting part (411a), a first-1 light-receiving part (412a), a second-1 light-emitting part (411b), a second-1 light-receiving part (412b), a first-2 light-emitting part (421a), a first-2 light-receiving part (422a), a second-2 light-emitting part (421b), a second-2 light-receiving part (422b), a first-3 light-emitting part (431a), a first-3 light-receiving part (432a), a second-3 light-emitting part (431b), a second-3 light-receiving part (432b)).

[0120] In one embodiment, the sensor (540) may include a fingerprint sensor. In one embodiment, the fingerprint sensor may be configured to acquire sensing data for a user's finger joint fingerprint. A finger joint fingerprint may be a fingerprint formed on a finger joint by the joint movement of each finger. Based on acquiring sensing data for a user's finger joint fingerprint, the fingerprint sensor may transmit the acquired sensing data to a processor (520). The processor (520) may acquire information about the finger joint fingerprint by analyzing the wrinkles of the finger joint or the pattern formed by the finger joint fingerprint based on the sensing data.

[0121] In one embodiment, the sensor (540) may be configured to acquire sensing data related to various biometric information of the user. For example, if the sensor (540) includes a PPG sensor, biometric information including at least one of blood pressure, heart rate, stress index, or blood oxygen concentration may be acquired based on the sensing data acquired through the PPG sensor. However, the sensor included in the sensor (540) is not limited to a PPG sensor. For example, the sensor (540) may further include an ECG (electrocardiogram) sensor capable of acquiring biometric signals using electrodes.

[0122] Although not illustrated in FIG. 5, in one embodiment, the sensor (540) may further include a temperature sensor (e.g., the temperature sensor (352) of FIG. 3) that enables the electronic device (101) to acquire (or estimate) the temperature of the user.

[0123] In one embodiment, the memory (530) may be included in the memory (130) of FIG. 1 or may be the memory (330) of FIG. 2 and FIG. 3.

[0124] In one embodiment, the memory (530) may store situational information obtained from within the electronic device (101) or from outside the electronic device (101). The memory (530) may store information related to the sensing direction of each of the plurality of sensors included in the sensor (540). The information stored in the memory (530) will be described in detail later. The memory (530) may store instructions. When executed by one or more processors (e.g., processor (520)), the instructions may cause the electronic device (101) to perform an operation (e.g., the operations described below in FIG. 6) to control the sensing direction of each of the plurality of sensors. In one embodiment, the actuator (560) may be configured to adjust the sensing direction of each of the plurality of sensors based on a control signal received from the processor (520).

[0125] In one embodiment, the processor (520) may be the processor (120) of FIG. 1, or the processor (320) of FIG. 2 and FIG. 3. In one embodiment, the processor (520) may control overall operations for controlling the operation of an electronic device. The processor (520) may include one or more processors. The one or more processors (520) may execute the instructions that cause the electronic device (101) to perform operations for controlling the electronic device (101), either individually or collectively.

[0126] In FIG. 5, the electronic device (101) is shown to include, but is not limited to, a communication module (550), a sensor (540), a memory (530), a processor (520), and an actuator (560). For example, the electronic device (101) may further include at least one component of the components included in the electronic device of FIG. 1, or components included in the electronic device (101) of FIG. 2 and FIG. 3. For example, the electronic device (101) may not include some of the components shown in FIG. 5.

[0127] According to various embodiments, various embodiments for controlling the sensing direction of each of the plurality of sensors by the electronic device (101) will be described in detail below in the description of FIG. 6.

[0128] The operations of the electronic device (101) described in the drawings below may be performed by a processor (520). However, for the sake of convenience of explanation, the operations performed by the processor (520) will be described as being performed by the electronic device (101).

[0129] FIG. 6 is a flowchart of an operation for measuring a biosignal in an electronic device according to one embodiment.

[0130] 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.

[0131] Referring to FIG. 6, according to one embodiment, in operation 602, an electronic device (101) (e.g., the electronic device (101, 201, 400) of FIG. 1, FIG. 2, FIG. 3, FIG. 4a, FIG. 4b, FIG. 4d, FIG. 5) can obtain situational information. The situational information may include information related to the wearing status of the electronic device. The situational information may include information related to the movement of a user wearing the electronic device. The situational information may include schedule information of the user. The situational information may include voice information of the user. The situational information may include biometric information of the user wearing the electronic device. The biometric information may include information related to at least one of heart rate, blood pressure, oxygen saturation, blood sugar, or body temperature.

[0132] According to one embodiment, in operation 604, the electronic device (101) can input the situation information into an artificial intelligence model to verify information related to the sensing direction of each of the acquired sensors. The artificial intelligence model may be included within the electronic device (101) or may be included within an external electronic device (e.g., electronic device (102), or server (108)) connected to the electronic device (101).

[0133] According to one embodiment, in operation 606, the electronic device (101) can control the actuator (530) to align the sensing direction of each of the plurality of sensors to the blood vessel based on information related to the sensing direction of each of the plurality of sensors. According to one embodiment, the electronic device (101) can acquire a signal sensed from the plurality of sensors, each sensing direction of which is aligned to the blood vessel, and can acquire a corrected sensing signal by inputting the acquired signal and the situation information into the artificial intelligence model. According to one embodiment, the electronic device (101) can output (or provide) information to guide the re-wearing of the electronic device based on information related to the sensing direction of each of the plurality of sensors. According to one embodiment, the electronic device (101) can check the blood vessel size prediction information acquired by inputting the situation information into the artificial intelligence model, and can control the actuator (530) to align the sensing direction of each of the plurality of sensors to the blood vessel based on the blood vessel size prediction information.

[0134] In the embodiments described below, the actuator (530) may be used in a broad sense to refer to a mechanism or device that operates a desired action by applying electrical, hydraulic, or pneumatic energy. According to one embodiment, the actuator (530) refers to an actuator for converting an electrical physical quantity into mechanical momentum, and may include various forms of structures depending on the function and purpose of use. For example, the actuator (530) may be understood as a comprehensive concept including nano actuators, hydraulic actuators, and piezoelectric actuators. Hereinafter, with reference to FIGS. 7a, 7b, 7c, 8a, 8b, and 8c, an example of an actuator that tilts a sensor in an electrical manner will be described as an example of an actuator (530).

[0135] FIGS. 7a, FIGS. 7b, FIGS. 7c, FIGS. 8a, FIGS. 8b, FIGS. 8c are drawings illustrating the control of an actuator according to one embodiment.

[0136] Referring to FIGS. 7a, 7b, 7c, 8a, 8b, and 8c, magnets (701, 702) may be attached to the lower surface of the sensor (700), and a coil (710) may be formed on the fixed surface of the sensor. The electronic device may control the tilting direction of the sensor (700) by adjusting the strength and direction of the electricity applied to the coil (710). According to various embodiments, if hydraulic or pneumatic pressure is utilized in a manner similar to the electronic method, the electronic device may tilt the sensor by placing a tube on the lower surface of the sensor (700) and supplying and discharging air or liquid through the tube. As another embodiment, the tilting direction and degree of the sensor (700) may be controlled by placing a piezoelectric element, whose volume changes according to an electrical signal, on the lower surface of the sensor (700). For example, the sensing direction of the sensor may be controlled by adjusting the tilting direction (or tilting angle) of the sensor (700).

[0137] FIG. 9a is a cross-sectional view of an electronic device according to one embodiment. FIG. 9b is a drawing showing a sensor of an electronic device according to one embodiment. FIG. 9c is a drawing showing a blood vessel image according to one embodiment.

[0138] Referring to FIG. 9a and FIG. 9b, a three-dimensional (3D) blood vessel image illustrated in FIG. 9c can be obtained using a sensor structure comprising a plurality of sensors (e.g., a light-emitting part and / or a light-receiving part) (a first-1 light-emitting part (411a), a first-1 light-receiving part (412a), a second-1 light-emitting part (411b), a second-1 light-receiving part (412b), a first-2 light-emitting part (421a), a first-2 light-receiving part (422a), a second-2 light-emitting part (421b), a second-2 light-receiving part (422b), a first-3 light-emitting part (431a), a first-3 light-receiving part (432a), a second-3 light-emitting part (431b), and a second-3 light-receiving part (432b)). For example, an electronic device can acquire biosignals generated in blood vessels by scanning a multi-channel sensor at various angles, comprising a plurality of sensors capable of tilting each sensor (e.g., light-emitting part), as illustrated in FIG. 9a. The processor of the electronic device can acquire biosignals arriving at each sensor (e.g., each light-receiving part) and transmit them to an artificial intelligence model. The artificial intelligence model can beam-form the received biosignals to convert them into a blood vessel image such as FIG. 9c. The blood vessel image acquired by the artificial intelligence model can be used to coordinate the initial location of the blood vessels and to calculate the alignment values ​​of each sensor using the artificial intelligence model. According to various embodiments, the electronic device can also utilize the blood vessel image for a user identification function by performing user authentication based on the acquired blood vessel image.

[0139] FIG. 10a is a cross-sectional view of an electronic device according to one embodiment.

[0140] Referring to FIG. 10a, as described above, the artificial intelligence model can output information related to the sensing direction of each of the multiple sensors based on input situational information. The electronic device can align the sensing direction of each sensor to the blood vessel based on the information related to the sensing direction of each sensor output through the artificial intelligence model. As an example, as shown in FIG. 10a, the electronic device can align the sensing direction of the second-third light-emitting part (431b) to the blood vessel located on the right side of the finger by means of an actuator.

[0141] FIG. 10b is a diagram showing the control of an actuator according to one embodiment.

[0142] Referring to FIG. 10b, according to one embodiment, a processor (520) of an electronic device controls actuators (1011, 1021, 1031) based on information related to the sensing direction of each sensor output by an artificial intelligence model, and actuators (1011, 1021, 1031) can control the tilting angle of each sensor based on the information related to the sensing direction. As the tilting angle of each sensor is controlled, the sensing direction of each sensor can be aligned with the blood vessel. For example, a first actuator (1011) receives a control signal related to the sensing direction received from the processor (520), and can adjust the tilting angle to control the sensing direction of the first-1 light-emitting part (411a) based on the received control signal related to the sensing direction. The second actuator (1021) receives a control signal related to the sensing direction received from the processor (520) and can adjust the tilting angle to control the sensing direction of the first-second light-emitting unit (421a) based on the control signal related to the receiving sensing direction. The third actuator (1031) receives a control signal related to the sensing direction received from the processor (520) and can adjust the tilting angle to control the sensing direction of the first-third light-emitting unit (431a) based on the control signal related to the receiving sensing direction. Although FIG. 10b illustrates that each sensor is controlled through a separate actuator, it may be implemented so that a single actuator controls multiple sensors.

[0143] Referring to FIG. 10a, as shown in FIG. 10b, the sensing direction of each sensor is aligned by actuators (1011, 1021, 1031) based on an artificial intelligence model, so that a source beam can be emitted from each sensor (411a, 421a, 431a) to the accurate location of the blood vessel. As each sensor is aligned with the blood vessel, the source beam emitted from each sensor is focused on the blood vessel, and since the biosignal is acquired without any unused sensors, a high-intensity biosignal with a high SNR can be acquired. By efficiently acquiring biosignals without unused sensors, the minimum number of sensors required for biosignal acquisition is reduced, thereby reducing the unit cost, mounting space, and power consumption in device fabrication. In addition, compared to a fixed sensor structure, since beamforming-capable sensors are utilized, there is an advantage that the area covered by the sensor for biosignal acquisition is wide. Biosignals with a high SNR increase the accuracy of the biosignal, allowing the device to be used in more diverse and specialized fields, thereby increasing the utility of the device. For example, by applying the aforementioned method to fields where the low accuracy of blood glucose measurement makes it difficult to manufacture commercial devices, various blood glucose application services can be provided.

[0144] Hereinafter, with reference to FIGS. 11a, 11b, and 11c, embodiments for calculating the alignment value of a sensor using an artificial intelligence model will be described.

[0145] FIG. 11a is a drawing showing a sensor before alignment according to one embodiment. FIG. 11b is a drawing showing the calculation of a tilting angle according to one embodiment. FIG. 11c is a drawing showing a sensor after alignment according to one embodiment.

[0146] Referring to FIG. 11a, the state before the sensor (e.g., the second-third light-emitting part (431b)) is aligned at the measurement point (1101) of the blood vessel (1100) is shown. For example, it can be seen that the source beam is not accurately radiated at the measurement point (1101) of the blood vessel (110) before the sensing direction of the sensor is aligned.

[0147] Referring to FIG. 11b, the relative positions of the sensor and the blood vessel can be represented as coordinates. For example, the position of the sensor can be set to the origin at (0, 0), and the measurement position (1101) of the blood vessel (1100) can be set to (x1, y1). By setting the coordinates of the blood vessel to (x1, y1) based on the blood vessel image, the angle (θ) between the line connecting the center coordinates of each sensor and the coordinates of the blood vessel and the surface of the sensor can be substantially perpendicular, as shown in FIG. 11c, thereby aligning the sensing direction of the sensor so that it is relatively accurately directed toward the blood vessel. The artificial intelligence model can calculate the respective θ values ​​for each element and store those values ​​in memory along with the blood vessel image, the current user's wearing status, or surrounding environment information at the time of measurement.

[0148] FIG. 12a is a drawing showing a change in the wearing state according to one embodiment. FIG. 12b and FIG. 12c are drawings showing sensor realignment according to a change in the wearing state according to one embodiment.

[0149] Referring to FIGS. 12a, 12b, and 12c, the sensor can be realigned when the wearing state of the sensor changes. For example, as shown in FIG. 12a, a user may wear a ring-shaped electronic device (101) on their finger. The user may also wear a watch-shaped electronic device (102) together. By comparing the left and right sides of FIG. 12a, it can be seen that the position of the ring-shaped electronic device (101) on the finger has changed. As the wearing position of the electronic device (101) changes, the measurement direction of the sensor aligned with the blood vessels (451a, 452a) may change. As shown in FIG. 12a, when the wearing state of the electronic device (101) that measures biosignals changes, the electronic device (101) can check the change in the wearing state and / or the degree of change in the wearing state based on situational information (e.g., the wearing state of a camera / measurement device, information obtained through various sensors). When a change in the above-mentioned wearing state is confirmed, the current location of the blood vessel (451a, 452a) can be re-predicted based on the blood vessel image and biosignal stored at the time of initial wearing, and the sensor can be realigned to that location.

[0150] According to various embodiments, as shown in FIG. 12b, if the degree of change in the wearing state is relatively small and the sensor can be realigned to the blood vessel (451a, 452a) by tilting the sensor alone, a high-intensity biosignal can be obtained by controlling the sensor to be realigned to the recalculated position of the blood vessel.

[0151] According to various embodiments, as shown in FIG. 12c, if the degree of change in the wearing state is relatively large and it is impossible to realign the sensor to the blood vessel (451a, 452a) by tilting the sensor alone, the user may be guided to re-wear the device. For example, the electronic device (101) transmits information to guide re-wearing to an external electronic device (e.g., a watch-type electronic device (102)) for re-wearing, and the external electronic device may notify the user of re-wearing through a display or speaker. According to various embodiments, until the user re-wears the electronic device (101), the alignment value of the sensor may be recalculated to the blood vessel where the most optimal biosignal measurable with the current sensor structure can be obtained, as shown in FIG. 12c, and the sensor may be newly realigned. For example, the electronic device (101) can align the sensing direction of the sensors so that the three sensors on the left sense a blood vessel located on the left (e.g., the first vein (451a)) and the three sensors on the right sense a blood vessel located on the right (e.g., the second vein (452a)). As illustrated in FIG. 12c, if the degree of change in the wearing state is relatively large, the sensing direction can be realigned so that some of the three sensors on the left sense a blood vessel located on the right (e.g., the second vein (452a)).

[0152] FIG. 13 is a diagram showing sensor realignment according to user state, according to one embodiment.

[0153] Referring to FIG. 13, when the size of a blood vessel changes due to changes in the user's body temperature and blood pressure, the artificial intelligence model can predict the size of the blood vessel using the user's information (e.g., body temperature information, blood pressure information) and realign the sensor so that it can cover the blood vessel to acquire a biosignal. For example, it can be seen that the size of the blood vessel (451a, 452a) during or after exercise, as shown on the right side of FIG. 13, becomes larger than the size of the blood vessel (451a, 452a) before exercise, as shown on the left side of FIG. 13. As shown in FIG. 13, when the electronic device detects that the user's body temperature and blood pressure rise as the user exercises, the artificial intelligence model can predict the size of the blood vessel based on the user's information (e.g., body temperature information or blood pressure information) and realign the sensor so that the sensor's focusing point is formed large enough to cover the entire predicted size of the blood vessel.

[0154] FIG. 14 is a block diagram of an electronic device according to one embodiment.

[0155] Referring to FIG. 14, the electronic device (101) may include a communication module (550), an application (1410), an AI module (1420), and a memory (530). Although FIG. 14 illustrates the AI ​​module (1420) being included within the electronic device (101), according to various embodiments, at least some or all of the components within the AI ​​module (1420) may be stored in an external electronic device of the electronic device (e.g., a wearable electronic device (102a), a smartphone (102b), or a server (108)). According to one embodiment, the electronic device (101) may communicate with the wearable electronic device (102a) or the smartphone (102b) through the communication module (550). The wearable electronic device (102a) or the smartphone (102b) may have an on-device AI embedded therein. The wearable electronic device (102a) or smartphone (102b) may collect relevant data necessary for obtaining biosignals, such as biosignals, user behavior information, device wearing status information, or surrounding environment information. The electronic device (101) may receive relevant data collected from the wearable electronic device (102a) or smartphone (102b) through a communication module (550). For example, the biosignals may include the user's heart rate, blood pressure, oxygen saturation, blood glucose, or body temperature data measured through a biosignal sensor embedded in the electronic device. User behavior information may include data such as motion information, real-time camera images, and voice recordings that can infer the user's behavior obtained using sensors embedded in the electronic device. Device wearing status information may include real-time camera images, biosignals, and motion information data that can infer the wearing position and wearing status of the device obtained using sensors embedded in the electronic device. Surrounding environment information may include temperature, humidity, real-time images, and illuminance information obtained using sensors embedded in the electronic device.

[0156] According to various embodiments, the communication circuit (550) may provide a communication method based on BT, WIFI, or UWB (ultra wide band) communication protocols, but is not limited to the above methods. The application (1410) may process data and classify features before transmitting information collected and received from an external device (e.g., a wearable electronic device (102a)) or an electronic device (101) to the optimization system module (1422). The application (1410) may include a wearable app, a camera app, a microphone app, a scheduler app, and a healthcare app. The wearable app may request the collection of signals corresponding to biosignals, user behavior information, device wearing status information, and surrounding environment information from an external electronic device (e.g., a wearable electronic device (102a) or a smartphone (102b)), analyze the received signals, and perform the function of transmitting features for each category to the AI ​​module (1420). The camera app can perform the function of classifying and transmitting features that help the AI ​​module (1420) check user behavior information, device wearing status, and surrounding environment information through a real-time camera. The microphone app can perform the function of analyzing voice and ambient sound signals to request the collection of various information necessary for optimizing biosignal acquisition and transmitting the features to the AI ​​module (1420). The scheduler app can perform the function of checking the user's schedule to extract information that can infer the user's behavior at the current time of use and transmitting it to the AI ​​module (1420). The healthcare app can perform the function of correcting biosignals acquired through the user's healthcare information in an artificial intelligence model and extracting features to transmit to the AI ​​module (1420) so that a biosignal acquisition strategy can be established.

[0157] According to various embodiments, the AI ​​module (1420) may include a service framework (1421) and an optimization system module (1422). The service framework (1421) may transmit various feature information extracted from the application (1410) to a memory (530) (e.g., flash memory) and to an optimization system module (1422). The service framework (1421) may provide the results received from the optimization system module (1422) to a user to provide a wearing status guide service and / or an optimized biosignal service.

[0158] According to various embodiments, the service framework (1421) may include a guide service (1421a), a healthcare service (1421b), and a sensor alignment service (1421c). The guide service (1421a) manages to store information for determining the user's device wearing status periodically or under specific conditions, and may provide a guide popup or notification to enable the user to reach an appropriate wearing status. For example, the guide service (1421a) is a user interaction service that informs the user of the current device wearing status and may provide guidance to modify the wearing status to obtain optimal biosignals. The guide service (1421a) is a data scheduling management service that controls the cycle for checking the wearing status and may be called together according to the cycle for acquiring various biosignals, and may perform an out-of-cycle call when there is a possibility of a change in the wearing status or when a change in the wearing status is necessary based on environmental changes and schedule information.

[0159] According to various embodiments, the sensor alignment service (1421c) can adjust the biosignal acquisition cycle as a data scheduling management service and can be called according to the acquisition cycle of each of the various biosignals. The sensor alignment service (1421c) can be called for one-time measurements in addition to the basic cycle when the wearing state and changes in the surrounding environment are detected. As a sensor operation management service, the sensor alignment service (1421c) can control the acquisition of biosignals by adjusting the driving intensity, driving frequency, driving cycle, and driving repetition rate of the biosignal sensor according to the type of biosignal to be acquired or the user's surrounding environment. As a sensor alignment management service, the sensor alignment service (1421c) can align the sensors to a position where the optimal biosignal can be acquired by considering the location of the blood vessel, the device wearing state, and the user's surrounding environment. According to various embodiments, the healthcare service (1421b) can provide various services utilizing biosignals to the user by utilizing user interaction.

[0160] According to various embodiments, the optimization system module (1422) may include at least one AI model, and each of the at least one AI model may include weight information. For example, the optimization system module (1422) may include a virtual AI model (1422a), a language AI model (1422b), a sensor AI model (1422c), an imaging AI model (1422d), an alignment AI model (1422e), and a correction AI model (1422f). The optimization system module (1422) may include an artificial intelligence model as a core model that calculates the alignment value of a sensor for acquiring bio-information and corrects the acquired bio-information by utilizing bio-signals, speech language interpretation information, surrounding environment images, user motion information, user pattern information, user health history, or blood vessel images received from the service framework (1421). Depending on the type of input information, each artificial intelligence model may be used in conjunction with the optimization system module (1422) individually or in combination. For example, a virtual AI model (1422a) can receive real-time camera image data as input and infer the current usage environment and the device wearing status. A language AI model (1422b) can analyze ambient noise or user voice data to infer the current user behavior and usage environment. A sensor AI model (1422c) can analyze biosignals and electrical signals collected from electronic devices (101, 102a, 102b) to infer the device wearing status, usage environment, and user behavior. An imaging AI model (1422d) can form a 3D blood vessel image based on biosignals collected from electronic devices and infer changes in the blood vessel image according to the user state and the device wearing environment.The alignment AI model (1422e) receives inference results received from each AI model and existing user information / vascular image information / sensor alignment value information as input, calculates alignment values ​​for aligning blood vessels and each biosensor, and transmits the results to the sensor alignment service (1421c) within the service framework (1421). The correction AI model (1422f) receives inference results received from each AI model and existing user information as input, corrects the acquired high-intensity biosignals to increase accuracy, and provides them to the user.

[0161] According to various embodiments, the memory (530) may store a blood vessel image (531), health history data (532), sensor tilting data (533), and user pattern data (534). The memory (530) may store various data generated during the process of obtaining biosignal correction and sensor alignment values. The sensor tilting data (533) may include the alignment value of an existing sensor, the health history data (532) may include the user's health information, the user pattern data (534) may include information related to the user's behavioral pattern, and the blood vessel image (531) may include the user's blood vessel image. The data stored in the memory (530) may be provided to the service framework (1421) of the AI ​​module (1420).

[0162] FIG. 15 is a block diagram of an electronic device according to one embodiment.

[0163] Referring to FIG. 15, a structure for correcting high-intensity biosignals using a correction AI model (1422f) included in the AI ​​module (1420) in FIG. 14 is shown. As described above, after acquiring high-intensity biosignals through sensor alignment, the biosignals can be corrected by referring to features acquired through external devices (102a, 102b) to increase the accuracy of the biosignals, and then delivered to the user.

[0164] According to various embodiments, user health and biosignal information (1501), ambient environment information (1502) at the time of measurement, user motion information (1503), or blood vessel image (1504) stored in memory (530) may be transmitted to an AI module (1420). According to various embodiments, if a blood vessel image is acquired, the electronic device (101) may recognize the user through blood vessel image matching and retrieve the user's information from memory (530). If the sensor is aligned by measuring only the change in the wearing state without acquiring a blood vessel image, the electronic device (101) may retrieve the data of the person set by the user from memory (530). Based on the various transmitted information, various AI models included in the AI ​​module (1420) may infer information necessary for biosignal correction. Such information may include the user's existing biosignal records, ambient temperature and humidity at the time of measurement, the user's activity state, the user's emotional state, or the device wearing state, and the AI ​​model (1420) may collect the above information and transmit it to a correction AI model (1422f). A correction AI model (1422f) that receives correction element information and high-intensity biosignals corrects the value of the biosignal and converts it into a highly accurate value, and can provide it to the user as information on blood pressure, blood sugar, or heart rate that the user can check.

[0165] FIGS. 16a and FIGS. 16b are flowcharts of an operation for measuring a biosignal in an electronic device according to one embodiment.

[0166] 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.

[0167] Referring to FIGS. 16a and 16b, according to various embodiments, the electronic device may acquire data from an external electronic device (e.g., a wearable electronic device (102a) or a smartphone (102b)) in operation 1602.

[0168] According to various embodiments, in operation 1604, the electronic device may extract features by processing data to be used for biosignal correction and sensor alignment value calculation collected through external electronic devices. The features may be classified into external device wearing status information or biosignal correction element information. The external device status information may be collected through images using a real-time camera, a wearing status detection sensor within the wearable device, biosignals, and vascular image information. The biosignal correction elements may be collected from the user's motion patterns, ambient voice information, biosignals, ambient environment information, and user schedule information.

[0169] According to various embodiments, the electronic device may store the acquired data or extracted features in memory in operation 1606.

[0170] According to various embodiments, the electronic device may check the service operation scheduler in operation 1608. The service operation scheduler may schedule the realignment of the biosignal sensor and biosignal correction to be performed at specific intervals. According to various embodiments, the electronic device may cause the AI ​​module (1420) to operate when a change in the external device wearing state is detected in addition to the corresponding intervals. For example, if the period of the scheduling arrives in operation 1610 (operation 1610-Yes), the electronic device may operate the AI ​​module and load features from memory in operation 1614. Even if the period of the scheduling does not arrive in operation 1610 (operation 1610-No), the electronic device may check whether the wearing state has changed in operation 1612. If the wearing state has not changed in operation 1612 (operation 1612-No), the electronic device may continue to check the service operation scheduler in operation 1608. If the electronic device detects that the wearing state has changed in operation 1612 (operation 1612-yes), it can operate the AI ​​module in operation 1614 and load features from memory.

[0171] According to various embodiments, each AI model that receives features from memory (e.g., a virtual AI model (1616a), a language AI model (1616b), a sensor AI model (1616c), or an imaging AI model (1616d)) can generate reference data to be utilized in an alignment AI model or a correction AI model. For example, the virtual AI model (1616a) can infer the wearing status of a biosignal acquisition device through real-time camera images. The virtual AI model (1616a) can collect surrounding environment data to perform user behavior prediction and inference, user state inference, and external environment inference. The language AI model (1616b) can analyze voice signals to analyze the user's surrounding environment and infer the user's behavior. The language AI model (1616b) can also infer the user's emotions by interpreting words that may affect the user's emotions. The sensor AI model (1616c) can infer the wearing status of the biosignal acquisition device and the user's behavior. The imaging AI model (1616d) can infer user blood vessel imaging and blood vessel images under various conditions.

[0172] According to various embodiments, the electronic device may acquire reference data in operation 1618. In operation 1622, the electronic device may estimate the location and condition of the blood vessel and estimate the realignment value of the sensor based on the reference data inferred from the four AI models from the previous alignment data (1620). In operation 1624, the electronic device may realign the sensor by controlling the actuator based on the estimated realignment value.

[0173] According to various embodiments, in operation 1626, the electronic device may acquire an enhanced bio-signal by the realigned sensor. In operation 1630, the electronic device may perform bio-signal correction from previous bio-signal data (1628) using an AI model (e.g., a correction AI model). In operation 1632, the electronic device may store the corrected bio-signal and the realigned value of the sensor in memory. For example, the electronic device may correct the enhanced bio-signal based on the user's condition, measurement environment information, and the user's previous healthcare information, and provide the user with values ​​of heart rate, blood pressure, blood glucose, and oxygen saturation that the user can verify. The user may receive a highly accurate bio-signal service and a wearing condition adjustment guide service.

[0174] FIG. 17 is a diagram showing sensor realignment and guide information output according to a change in the wearing state, according to one embodiment.

[0175] Referring to FIG. 17, the left diagram illustrates a case where a left-handed user wears a smart ring-shaped electronic device (101) on their left hand and plays tennis. As described above, according to various embodiments, an AI model (e.g., the AI ​​module (1420) of FIG. 14) infers that the alignment of blood vessels and sensors will be misaligned by the racket held in the hand through the analysis of user motion and the surrounding environment. The AI ​​module infers the pressure of gripping the racket and the degree of finger compression to reconfirm the current location of the blood vessels and realign the sensors to the corresponding blood vessels to acquire high-intensity biosignals. According to various embodiments, the electronic device may correct the acquired signals based on ambient temperature, the user's exercise level, or body temperature information. The corrected information may be provided to the user. For example, since frequent misalignment of blood vessels and sensors is predicted during exercise, according to various embodiments, the AI ​​model may guide the user to wear a biosignal measuring device (e.g., the smart ring-shaped electronic device (101)) on the hand not used for exercise.

[0176] FIGS. 18a, FIGS. 18b, and FIGS. 18c are drawings illustrating measurement enhancement according to user activity status according to one embodiment.

[0177] Referring to FIGS. 18a, 18b, and 18c, according to various embodiments, the electronic device may enhance and apply measurement elements based on the user's activity status. For example, the AI ​​model may infer what activity the user is currently performing by utilizing various information and focus on measuring biosignals suitable for that activity. For example, as shown in FIG. 18a, if the AI ​​model determines that the user is exercising, the electronic device may increase the frequency of heart rate and oxygen saturation measurements or increase the frequency of collecting information on external environments (e.g., temperature, humidity) that may affect the signals. As shown in FIG. 18b, if the AI ​​model confirms that the user is eating, the electronic device may enhance blood glucose measurement, and if biosignals can be acquired with various types of sensors, it may adjust to primarily use the sensor suitable for the biosignal. As shown in FIG. 18c, if the user is drinking alcohol, the AI ​​model may determine this and begin measuring alcohol levels, which are not normally measured.

[0178] As described above, according to various embodiments, the electronic device is structured so that each of the multi-channel sensors can be tilted, allowing each sensor to be aligned with the blood vessel. This improves the efficiency of acquiring high-intensity biosignals and measuring signals. The alignment of the blood vessel and the sensor may shift depending on the user's device wearing status and the signal measurement environment. As described above, the AI ​​model can predict this in advance and infer the current state to realign the sensors, thereby enabling the continuous acquisition of high-intensity biosignals. Furthermore, based on various information acquired from the electronic device, the biosignals can be corrected to provide the user with highly accurate information, and a device wearing status guide can be used to guide the user to wear the device in an optimal state for acquiring biosignals.

[0179] According to one embodiment, the electronic device may include a housing, a plurality of sensors disposed inside or outside the housing, an actuator configured to adjust the sensing direction of each of the plurality of sensors, a memory for storing instructions, and at least one processor including a processing circuit.

[0180] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to acquire situation information.

[0181] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to input the situation information into an artificial intelligence model to verify information related to the sensing direction of each of the plurality of sensors acquired.

[0182] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may cause the actuator to control the sensing direction of each of the plurality of sensors to align the sensing direction of each of the plurality of sensors with the blood vessel based on information related to the sensing direction of each of the plurality of sensors.

[0183] According to one embodiment, the situation information may include information related to the wearing status of the electronic device.

[0184] According to one embodiment, the situation information may include information related to the movement of a user wearing the electronic device.

[0185] According to one embodiment, the situation information may include biometric information of a user wearing the electronic device.

[0186] According to one embodiment, the bio-information may include information related to at least one of heart rate, blood pressure, oxygen saturation, blood glucose, or body temperature.

[0187] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may acquire a signal sensed from the plurality of sensors and input the acquired signal and the situation information into the artificial intelligence model to acquire a corrected sensing signal.

[0188] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to output information for guiding the re-wearing of the electronic device based on information related to the sensing direction of each of the plurality of sensors.

[0189] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to check the blood vessel size prediction information obtained by inputting the situation information into an artificial intelligence model, and to control the actuator to align the sensing direction of each of the plurality of sensors to the blood vessel based on the blood vessel size prediction information.

[0190] According to one embodiment, the situation information may include the user's schedule information.

[0191] According to one embodiment, the situation information may include user voice information.

[0192] According to one embodiment, the method of operating an electronic device may include an operation of acquiring situation information.

[0193] According to one embodiment, the method of operating an electronic device may include the operation of inputting the situation information into an artificial intelligence model to check information related to the sensing direction of each of the acquired multiple sensors.

[0194] According to one embodiment, the method of operating an electronic device may include controlling an actuator to align the sensing direction of each of the plurality of sensors with a blood vessel based on information related to the sensing direction of each of the plurality of sensors.

[0195] According to one embodiment, the situation information may include information related to the wearing status of the electronic device.

[0196] According to one embodiment, the situation information may include information related to the movement of a user wearing the electronic device.

[0197] According to one embodiment, the situation information may include biometric information of a user wearing the electronic device.

[0198] According to one embodiment, the bio-information may include information related to at least one of heart rate, blood pressure, oxygen saturation, blood glucose, or body temperature.

[0199] According to one embodiment, the method may include: an operation of acquiring a signal sensed from the plurality of sensors; and an operation of acquiring a corrected sensing signal by inputting the acquired signal and the situation information into the artificial intelligence model.

[0200] According to one embodiment, the method may include an operation of outputting information to guide the re-wearing of the electronic device based on information related to the sensing direction of each of the plurality of sensors.

[0201] According to one embodiment, the method may include: an operation of inputting the situation information into an artificial intelligence model to verify the acquired blood vessel size prediction information; and an operation of controlling the actuator to align the sensing direction of each of the plurality of sensors with the blood vessel based on the blood vessel size prediction information.

[0202] According to one embodiment, the situation information may include the user's schedule information.

[0203] According to one embodiment, in a storage medium for storing computer-readable instructions, the instructions cause the electronic device to perform at least one operation when executed by at least one processor of the electronic device, and the at least one operation may include an operation of acquiring situation information.

[0204] According to one embodiment, in a storage medium for storing computer-readable instructions, the instructions cause the electronic device to perform at least one operation when executed by at least one processor of the electronic device, and the at least one operation may include an operation of checking information related to the sensing direction of each of a plurality of sensors obtained by inputting the situation information into an artificial intelligence model.

[0205] According to one embodiment, in a storage medium for storing computer-readable instructions, the instructions cause the electronic device to perform at least one operation when executed by at least one processor of the electronic device, and the at least one operation may include controlling an actuator to align the sensing direction of each of the plurality of sensors with a blood vessel based on information related to the sensing direction of each of the plurality of sensors.

[0206] The electronic device according to the various embodiments disclosed in this document may be of various forms. The electronic device may include, for example, a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a consumer electronics device. The electronic device according to the embodiments of this document is not limited to the devices described above.

[0207] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, 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 (e.g., first) component is referred to as “coupled” or “connected” to another (e.g., second) component, 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.

[0208] The term “module” as used in the various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0209] Various embodiments of this 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, 301)). For example, a processor (e.g., processor (120, 320)) of the machine (e.g., electronic device (101, 301)) may call at least one of the one or more instructions stored from 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-transitory' is a device in which the storage medium is tangible, and It merely means that it does not contain a signal (e.g., electromagnetic waves), and this term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily on a storage medium.

[0210] According to one embodiment, the method according to the various embodiments disclosed herein may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or distributed online (e.g., download or upload) through an application store (e.g., Play Store™) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0211] According to various embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In an electronic device (101), Housing (210); A plurality of sensors (540) disposed inside or outside the housing; An actuator (560) configured to adjust the sensing direction of each of the plurality of sensors; Memory for storing instructions (530); and It includes at least one processor (520) including a processing circuit, and When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Acquire situational information, The above situation information is input into an artificial intelligence model to verify information related to the sensing direction of each of the plurality of sensors obtained, and An electronic device that causes the actuator to control the sensing direction of each of the plurality of sensors to align the sensing direction of each of the plurality of sensors to a blood vessel based on information related to the sensing direction of each of the plurality of sensors.

2. In paragraph 1, the above situation information is, An electronic device comprising information related to the wearing status of the above electronic device.

3. In Paragraph 1, the above situation information is, An electronic device comprising information related to the movement of a user wearing the electronic device.

4. In paragraph 1, the above situation information is, An electronic device comprising biometric information of a user wearing the above electronic device.

5. In paragraph 4, the above biometric information is, An electronic device comprising information related to at least one of heart rate, blood pressure, oxygen saturation, blood glucose, or body temperature.

6. In any one of paragraphs 1 through 5, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, A signal sensed from the above plurality of sensors is obtained, and An electronic device that inputs the above-mentioned acquired signal and the above-mentioned situation information into the above-mentioned artificial intelligence model to obtain a corrected sensing signal.

7. In any one of paragraphs 1 through 6, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that causes information to be output to guide the re-wearing of the electronic device based on information related to the sensing direction of each of the plurality of sensors.

8. In any one of paragraphs 1 through 7, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Check the blood vessel size prediction information obtained by inputting the above situation information into an artificial intelligence model, and An electronic device that causes the actuator to control the sensing direction of each of the plurality of sensors to align with the blood vessel based on the above blood vessel size prediction information.

9. In Paragraph 8, The above situation information is an electronic device including user schedule information.

10. In Paragraph 8, The above situation information is an electronic device including user voice information.

11. In a method of operating an electronic device, Action of acquiring situational information; The operation of inputting the above situation information into an artificial intelligence model to verify information related to the sensing direction of each of the acquired multiple sensors; and A method of operation of an electronic device comprising controlling an actuator to align the sensing direction of each of the plurality of sensors to a blood vessel based on information related to the sensing direction of each of the plurality of sensors.

12. In Paragraph 11, The operation of acquiring signals sensed from the plurality of sensors; and A method of operation of an electronic device comprising the operation of inputting the acquired signal and the situation information into the artificial intelligence model to acquire a corrected sensing signal.

13. In Paragraph 11 or 12, A method of operating an electronic device, comprising the operation of outputting information to guide the re-wearing of the electronic device based on information related to the sensing direction of each of the plurality of sensors.

14. In any one of paragraphs 11 through 13, The operation of inputting the above situation information into an artificial intelligence model to verify the acquired blood vessel size prediction information; and A method of operation of an electronic device comprising controlling the actuator to align the sensing direction of each of the plurality of sensors to the blood vessel based on the above blood vessel size prediction information.

15. A storage medium for storing computer-readable instructions, wherein the instructions cause the electronic device to perform at least one operation when executed by at least one processor of the electronic device, and the at least one operation is: Action of acquiring situational information; The operation of inputting the above situation information into an artificial intelligence model to verify information related to the sensing direction of each of the acquired multiple sensors; and A storage medium comprising an operation to control an actuator to align the sensing direction of each of the plurality of sensors to a blood vessel based on information related to the sensing direction of each of the plurality of sensors.

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