Electronic device for detecting heart rate on basis of biometric information, control method therefor, and non-transitory computer-readable storage medium

Abstract

An electronic device according to the present disclosure comprises: at least one processor including a first sensor, a second sensor, a display, and a processing circuit; and a memory, which stores instructions and includes at least one storage medium, wherein, when individually or collectively executed by the at least one processor, the instructions instruct the electronic device to: acquire biometric information of a user by using the first sensor and / or the second sensor; acquire a first parameter group from among a plurality of parameter groups on the basis of the biometric information; configure an analysis algorithm for a heart rate on the basis of the first parameter group; acquire first sensing data by controlling the first sensor; acquire a first analysis result by applying the first sensing data to the analysis algorithm; and identify, on the basis of the first analysis result, whether the heart rate corresponding to the first sensing data is irregular.

Description

An electronic device for detecting heart rate based on biometric information, a control method thereof, and a non-transitory computer-readable storage medium

[0001] The present disclosure relates to an electronic device for detecting irregularities in heart rate based on a user's condition, such as biometric information and context information, a control method thereof, and a non-transitory computer-readable storage medium.

[0002] With recent advancements in electronic technology, various types of electronic devices are being developed.

[0003] In particular, wearable devices that can come into contact with parts of the user's body are being developed and distributed.

[0004] Wearable devices can acquire and provide biometric information by coming into contact with a part of the user's body. Recently, there has been a growing demand for methods to more accurately detect heart rate irregularities based on the user's condition, such as biometric information and contextual information.

[0005] The above information may be provided as background art to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above-described matters constitute prior art related to the present disclosure.

[0006] According to an embodiment of the present disclosure, an electronic device includes a first sensor, a second sensor, a display, at least one processor including a processing circuit, and a memory storing instructions and including one or more storage media, wherein the instructions, when individually or collectively executed by the at least one processor, are configured to cause the electronic device to obtain biometric information of a user using at least one of the first sensor and the second sensor, obtain a first parameter group from among a plurality of parameter groups based on the biometric information, set an analysis algorithm for heart rate based on the first parameter group, control the first sensor to obtain first sensing data, apply the first sensing data to the analysis algorithm to obtain a first analysis result, and identify whether a heart rate corresponding to the first sensing data is irregular based on the first analysis result.

[0007] In a control method of an electronic device according to an embodiment, the electronic device includes a first sensor and a second sensor, and the method includes an operation of obtaining biometric information of a user using at least one of the first sensor and the second sensor, an operation of obtaining a first parameter group from among a plurality of parameter groups based on the biometric information, an operation of setting an analysis algorithm for a heart rate based on the first parameter group, an operation of controlling the first sensor to obtain first sensing data, an operation of applying the first sensing data to the analysis algorithm to obtain a first analysis result, and an operation of identifying whether a heart rate corresponding to the first sensing data is irregular based on the first analysis result.

[0008] In a storage medium storing computer-readable instructions according to an embodiment, the instructions are configured to, when individually or collectively executed by at least one processor of an electronic device, cause the electronic device to obtain biometric information of a user using at least one of a first sensor and a second sensor, obtain a first parameter group from among a plurality of parameter groups based on the biometric information, set an analysis algorithm for heart rate based on the first parameter group, control the first sensor to obtain first sensing data, apply the first sensing data to the analysis algorithm to obtain a first analysis result, and identify whether a heart rate corresponding to the first sensing data is irregular based on the first analysis result.

[0009] In connection with the description of the drawings, the same or similar reference numerals may be used for the same or similar components.

[0010] FIG. 1 illustrates an electronic device according to an embodiment of the present disclosure.

[0011] FIG. 2 is a block diagram of an electronic device according to an embodiment of the present disclosure.

[0012] FIG. 3 is a perspective view of the front of an electronic device according to an embodiment of the present disclosure.

[0013] FIG. 4 is a perspective view of the rear surface of an electronic device according to an embodiment of the present disclosure.

[0014] FIG. 5 is an exploded perspective view of an electronic device according to an embodiment of the present disclosure.

[0015] FIG. 6 is a diagram illustrating an electronic device for analyzing heart rate at preset time intervals according to an embodiment of the present disclosure.

[0016] FIG. 7 is a flowchart illustrating a control method of an electronic device for obtaining a parameter group corresponding to biometric information according to an embodiment of the present disclosure.

[0017] FIG. 8 is a flowchart illustrating a control method of an electronic device that provides a notification when an irregular heart rate is identified based on a plurality of analysis results according to an embodiment of the present disclosure.

[0018] FIG. 9 is a diagram illustrating an ROC curve according to an embodiment of the present disclosure.

[0019] FIG. 10 is a diagram illustrating an electronic device that identifies whether a heartbeat is irregular using an electronic device and an external electronic device, respectively, according to an embodiment of the present disclosure.

[0020] FIG. 11 is a drawing illustrating the configuration of an external electronic device according to an embodiment of the present disclosure.

[0021] FIG. 12 is a front view of an external electronic device according to an embodiment of the present disclosure.

[0022] FIG. 13 is an exploded perspective view of an external electronic device according to an embodiment of the present disclosure.

[0023] FIG. 14 is a drawing illustrating the configuration of an external electronic device according to an embodiment of the present disclosure.

[0024] FIG. 15 is a diagram illustrating an electronic device for obtaining a parameter group using a neural network model according to an embodiment of the present disclosure.

[0025] FIG. 16 is a drawing illustrating an electronic device displaying a notification according to an embodiment of the present disclosure.

[0026] Hereinafter, the present disclosure will be described in detail with reference to the attached drawings.

[0027] The terms used in the embodiments of this disclosure have been selected from widely used, current terms, taking into account the functions of this disclosure. However, these terms may vary depending on the intentions of those skilled in the art, precedents, or the emergence of new technologies. Furthermore, in certain cases, the applicant may arbitrarily select terms, in which case their meanings will be described in detail in the relevant description of the disclosure. Therefore, the terms used in this disclosure should not be defined simply as names, but rather based on the meanings of the terms and the overall content of this disclosure.

[0028] In this specification, expressions such as “has,” “can have,” “includes,” or “may include” indicate the presence of a feature (e.g., a number, function, operation, or component such as a part), and do not exclude the presence of additional features.

[0029] The expression "at least one of A and / or B" should be understood to mean either "A" and "B" or "A or B".

[0030] As used herein, the expressions “first,” “second,” “first,” or “second,” etc., may describe various components, regardless of order and / or importance, and are only used to distinguish one component from another, but do not limit the components.

[0031] When it is said that a component (e.g., a first component) is “(operatively or communicatively) coupled with / to” or “connected to” another component (e.g., a second component), it should be understood that the component may be directly coupled to the other component, or may be connected through another component (e.g., a third component).

[0032] Singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, terms such as "comprise" or "consist of" are intended to indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but should be understood not to preclude the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0033] In this disclosure, the term user may refer to a person using an electronic device or a device using an electronic device (e.g., an artificial intelligence electronic device).

[0034] Hereinafter, embodiments of the present disclosure will be described in more detail with reference to the attached drawings.

[0035] FIG. 1 illustrates an electronic device according to an embodiment of the present disclosure.

[0036] The electronic device (100) according to various embodiments of the present disclosure may include a wearable device or a portable device. Here, a wearable device refers to a device that includes a flexible material (e.g., silicone rubber, fiber) and can be worn by a user or can come into contact with a part of the user's body. For example, various types of devices that can be worn on the body by a person or an animal, such as watches, clothing, shoes, gloves, glasses, hats, and accessories (e.g., rings), may be included in the wearable device. However, these are merely examples and the present invention is not limited thereto.

[0037] According to an embodiment, the electronic device (100) may come into contact with a part of the user's body to measure the user's body information.

[0038] The electronic device (100) can measure the user's physical activity (e.g., number of steps, calories consumed, distance traveled), body temperature, and bioelectrical impedance.

[0039] According to an embodiment, the electronic device (100) can identify sleep patterns such as deep sleep, light sleep, and REM (rapid eye movement) sleep based on heart rate, physical activity, and body temperature. According to an embodiment, the electronic device (100) can measure impedance by applying a micro-electrical signal to the human body, and can measure the amount of water and body fat in the user's body through bioelectrical impedance analysis (BIA). In addition, the electronic device (100) includes an electrocardiogram (ECG) measurement sensor, and can measure the user's electrocardiogram using the ECG measurement sensor.

[0040] According to an embodiment, the electronic device (100) includes a PPG (photoplethysmogram) sensor (or, photoplethysmogram sensor, photoplethysmogram sensor), and can measure heart rate and blood oxygen saturation (SpO2) using the PPG sensor.

[0041] An electronic device (100) according to an embodiment of the present disclosure can measure pulse waves using light via a PPG sensor. Pulse waves are pulsatile waveforms generated by cardiac contraction and relaxation, and cause changes in blood vessel volume as they propagate along blood vessels. For example, a PPG sensor can measure pulse waves by detecting changes in optical properties, such as reflection, absorption, and transmittance, that appear in biological tissues according to changes in blood vessel volume.

[0042] According to an embodiment, the electronic device (100) may identify a heart rate based on a periodic waveform according to a measured pulse wave. For example, the electronic device (100) may identify a heart rate based on the time interval between peaks of a periodic waveform according to a measured pulse wave.

[0043] According to an embodiment, the electronic device (100) may apply sensing data including pulse waves measured using a PPG sensor to an analysis algorithm for heart rate to obtain analysis results. According to an embodiment, the analysis results may include whether the heart rate is irregular.

[0044] For example, the electronic device (100) may measure pulse waves at preset time intervals using a PPG sensor, and apply sensing data including the measured pulse waves to an analysis algorithm to identify the user's heart rate based on the measured pulse waves. According to an embodiment, the electronic device (100) may identify whether the user's heart rate is irregular based on the analysis results output by the analysis algorithm.

[0045] Conventionally, electronic devices have not modified the parameter groups that comprise analysis algorithms to more sensitively identify heart rate irregularities based on the user's condition (e.g., the user's biometric information, contextual information), and instead have identified heart rate irregularities using only analysis algorithms comprised of fixed parameter groups. Therefore, conventional electronic devices have been limited in their inability to provide analysis results appropriate to the user's condition (e.g., whether the heart rate is irregular).

[0046] An electronic device (100) according to an embodiment of the present disclosure can obtain a parameter group based on a user's condition, set an analysis algorithm for heart rate with the obtained parameter group, and provide an analysis result suitable for the user's condition.

[0047]

[0048] FIG. 2 is a block diagram of an electronic device according to an embodiment of the present disclosure.

[0049] FIG. 2 is a block diagram of an exemplary electronic device capable of performing the operations described in accordance with an embodiment of the present disclosure.

[0050] Referring to FIG. 2, the electronic device (100) may be implemented in various wearable forms, such as a smartwatch, a smart band, a smart ring, wireless earphones, or smart glasses. The components, their relationships, and their functions illustrated in FIG. 2 are merely exemplary and do not limit the implementations described or claimed in this document. The electronic device (100) may be referred to as a mobile device, a user device, a multi-function device, a portable device, or a server.

[0051] The electronic device (100) may include components including at least one processor (110) (hereinafter referred to as processor (110)), at least one memory (120) (hereinafter referred to as memory (120)), at least one display (140) (hereinafter referred to as display (140)), at least one image sensor (150) (hereinafter referred to as image sensor (150)), at least one communication circuit (160) (hereinafter referred to as communication circuit (160)), and / or at least one sensor (170) (hereinafter referred to as sensor (170)). The above components are merely exemplary. For example, the electronic device (100) may include other components (e.g., power management integrated circuitry (PMIC), audio processing circuitry, an antenna, a rechargeable battery, or an input / output interface). For example, some components may be omitted from the electronic device (100). For example, some components may be integrated into one component.

[0052] The processor (110) may be implemented as one or more IC (integrated circuit (or circuitry)) chips and may perform various data processing. The processor (110) may include at least one electrical circuit and may individually or collectively perform distributed processing of instructions (or programs, data) stored in the memory (120). The processor (110) may include a processor assembly including one or more processing circuits. The processor (110) may include any processing circuit operative to control the performance and operations of one or more components of the electronic device (100) (e.g., the memory (120), the microphone (130), the display (140), the image sensor (150), the communication circuit (160), the sensor (170), and / or the speaker (180)). For example, the processor (110) (e.g., an application processor (AP)) may be implemented as a system on chip (SoC) (e.g., a single chip or chipset). For example, the processor (110) may be implemented as multiple cores (or at least one core circuit), multiple chips, or multiple chipsets. For example, the processor (110) may include one or more processing circuits. For example, the processor (110) may include one or more processing circuits configured to individually and / or collectively perform various functions of the present disclosure. As a non-limiting example, at least a portion of the processor (110) may be included in a first chip of the electronic device (100), and at least another portion of the processor (110) may be included in a second chip of the electronic device (100) that is different from the first chip of the electronic device (100).

[0053] For example, the processor (110) may include a central processing unit (CPU) (111), a graphics processing unit (GPU) (112), a neural processing unit (NPU) (113), an image signal processor (ISP) (114), a display controller (115), a memory controller (116), a storage controller (117), a communication processor (CP) (118), and / or a sensor interface (119). These components of the processor (110) are merely exemplary. For example, the processor (110) may further include other components. For example, some components of the processor (110) may be omitted from the processor (110). For example, some components of the processor (110) may be included as separate components of the electronic device (100) outside the processor (110). For example, some components of the processor (110) (e.g., memory controller (116)) may be included within other components (e.g., at least a portion of memory (120), an interface (e.g., available for connection to at least one component of the electronic device (100)), a display (140) and / or an image sensor (150)).

[0054] The processor (110) may cause other components of the electronic device (100) to perform various operations by executing instructions stored in the memory (120). The CPU (111) (or central processing circuit) may be configured to control components of the processor (110) based on the execution of instructions stored in the memory (120) (e.g., volatile memory (121) and / or non-volatile memory (122)). The GPU (112) (or graphics processing circuit) may be configured to execute parallel operations (e.g., rendering). The NPU (113) (or neural processing circuit, or AI (artificial intelligence) chip) may be configured to execute operations for an artificial intelligence model (e.g., convolution computation). The ISP (114) (or image signal processing circuit) may be configured to process a raw image acquired through the image sensor (150) into a format suitable for a component within the electronic device (100) or a component of the processor (110). The display controller (115) (or display control circuit, or display processing unit (DPU)) may be configured to process an image acquired from the CPU (111), the GPU (112), the ISP (114), or the memory (120) (e.g., the volatile memory (121)) into a format suitable for the display (140). The memory controller (116) (or memory control circuit) may be configured to control reading data from the volatile memory (121) and writing data to the volatile memory (121). The storage controller (117) (or storage control circuit) may be configured to control reading data from the nonvolatile memory (122) and writing data to the nonvolatile memory (122).The CP (118) (communication processing circuit) may be configured to process data acquired from a component of the processor (110) into a format suitable for transmission to another electronic device via the communication circuit (160), or to process data acquired from another electronic device via the communication circuit (160) into a format suitable for processing by the component of the processor (110). For example, the communication circuit (160) may include one or more communication circuits. The sensor interface (119) (or sensing data processing circuit, sensor hub) may be configured to process data about the state of the electronic device (100) and / or the state of the surroundings of the electronic device (100), acquired via the sensor (170), into a format suitable for the component of the processor (110).

[0055] The memory (120) may include one or more storage media (or one or more storage devices). For example, the memory (120) may include a memory assembly including one or more storage media. For example, the one or more storage media may include permanent memory (e.g., non-volatile memory (122)) such as a hard drive, flash memory, read-only memory (ROM), semi-permanent memory (e.g., volatile memory (121)) such as random access memory (RAM), any other suitable type of storage (or storage assembly), or any combination thereof. The memory (120) may include cache memory, which is one or more different types of memory used to temporarily store data for a function or feature of the electronic device (100). As a non-limiting example, the cache memory may be included within the processor (110). The memory (120) may be fixedly embedded within the electronic device (100) or incorporated into one or more suitable types of components (e.g., a subscriber identity module (SIM) card and / or a secure digital (SD) card) that may be repeatedly inserted into and removed from the electronic device (100).

[0056] For example, the memory (120) may store one or more software applications, such as an operating system (or system) software application, a firmware software application, a driver software application, a plug-in (e.g., add-in, add-on, and / or applet) software application, and / or any other suitable software applications. For example, the one or more software applications may include instructions executable by the processor (110). For example, the memory (120) may store instructions callable by an application programming interface (API). For example, the memory (120) may store instructions within a library.

[0057] The microphone (130) can acquire sound output from an external object. Depending on the embodiment, the number of microphones (130) may be one or more. The speaker (180) can output sound to the outside. Depending on the embodiment, the number of speakers (180) may be one or more.

[0058] The display (140) is controlled by the processor (110) and can output visualized information to the user. The visual information may include visual objects displayed on the display (140). For example, the visual objects may include screens, images, icons, graphical user interfaces (GUIs), and user interface (UI) elements. For example, the display (140) may be implemented as a flat panel display (FPD), a curved display, or a flexible display. For example, the display (140) may be implemented as various types of displays, such as a liquid crystal display (LCD), an active matrix organic light emitting diodes (AMOLED), a light emitting diodes (LED), a micro LED, or a Mini LED.

[0059] The display (140) may include a touch-sensitive circuit configured to detect a touch. The touch-sensitive circuit may acquire a user input to the display (140). For example, the touch-sensitive circuit may detect an input (e.g., a touch input or a hovering input) at a specific location of the display (140) by measuring a change in a signal (e.g., voltage, light intensity, resistance, or charge) at the specific location, and provide information about the detected input to the processor (110).

[0060] The communication circuit (160) can perform data communication with other electronic devices under the control of the processor (110). For example, the communication circuit (160) can transmit and receive control commands or data with other electronic devices. For example, the communication circuit (160) can support transmission and / or reception of electrical signals based on various types of protocols, such as Ethernet, LAN (local area network), WAN (wide area network), WiFi (wireless fidelity), Bluetooth, BLE (bluetooth low energy), ZigBee, NFC (Near Field Communication), ANT+, Cellular (LTE, 5G, 6G, NB-IoT), RFID, UWB (ultra wide band), GNSS (global navigation satellite system), or RF communication.

[0061] The sensor (170) can generate electrical information that can be processed by the processor (110) and / or the memory (120) from non-electronic information related to the electronic device (100). The information can be referred to as sensing data. The sensor (170) can detect the operating status of the electronic device (100) (e.g., power or temperature) or the external environmental status (e.g., the user's status) and generate electrical information corresponding to the detected status.

[0062] According to one embodiment, the sensor (170) may include a first sensor (171) and a second sensor (172). For example, the first sensor (171) may include a biosensor, and the second sensor (172) may include an electrode sensor.

[0063] A biometric sensor may be configured to detect a user's biometric information. The biometric information may include various data indicating the user's physical or physiological state. For example, the biometric sensor may include a photoplethysmography (PPG) sensor or a biomarker sensor.

[0064] According to an embodiment, a biosensor may include an emitter and a receiver (or detector). The biosensor may output light to the outside through the emitter under the control of a processor (110). The output of light (or light) may be replaced with expressions such as emission, divergence, or irradiation of light, for example. The emitter may include a plurality of light-emitting elements. For example, the light-emitting elements may be implemented as a light emitting diode (LED), a laser diode, or a vertical cavity surface emitting laser (VCSEL). The light output by the emitter may include at least one of infrared (IR) ray, visible light, or ultraviolet (UV) ray. The emitter may include a light-emitting element for outputting light corresponding to each of infrared, visible, and ultraviolet ray.

[0065] The light emitted from the light-emitting unit can be irradiated onto the user's skin. The user's skin may include various body parts that come into contact with the biosensor. For example, the body parts may include the palm or sole of the foot, which have a thick epidermal layer, areas where venous or capillary blood is located, or other areas with a high blood vessel density, such as the fingers, toes, or earlobes. Additionally, the body parts may include the wrist, fingers, or inside the ear, which may come into contact with the biosensor when the electronic device (100) is worn.

[0066] At least a portion of the light emitted from the light emitting unit may be scattered or reflected by the user's body (e.g., skin, skin tissue, fat layer, veins, arteries, or capillaries). The light receiving unit may receive at least a portion of the scattered or reflected light and convert the received light into an electrical signal. For example, the light receiving unit may be composed of at least one photodiode (PD) and a phototransistor. However, the present invention is not limited thereto, and may be implemented as a complementary metal-oxide semiconductor (CMOS) image sensor or a charge-coupled device (CCD) image sensor. As a non-limiting example, the biosensor may include an amplifier for amplifying an electrical signal and an analog-to-digital converter (ADC) for converting the electrical signal into a digital signal.

[0067] According to one embodiment, the biometric sensor can measure the user's biometric information based on the received light under the control of the processor (110).

[0068] For example, the processor (110) outputs visible light (e.g., green light, red light, or blue light) or infrared light to the user's skin, and when the output light is reflected by blood vessels and received, the amount of light reflected or absorbed based on the received light is measured to obtain a PPG signal, and the PPG signal can be used to obtain heart rate (HR), oxygen saturation (SpO2), blood pressure, blood volume, and stress index.

[0069] For example, the processor (110) outputs light of a specific wavelength to the user's skin, and when the output light is reflected by the user's skin or blood vessels and received, the received light can be analyzed to obtain information about a specific substance (or specific component) in the skin or blood vessels of the body. For example, the processor (110) can estimate the concentration of a specific substance using data acquired by a biosensor. The substance can include, for example, an antioxidant including a carotenoid, glucose, urea, lactate, triglyceride, total protein, cholesterol, or ethanol.

[0070] For example, the processor (110) outputs light of a specific wavelength to the user's skin, and when the output light is reflected by the user's skin or blood vessels and at least partly received, the received light is analyzed to measure pulse waves, and the heart rate can be identified based on the amount of blood flow that changes according to the pulse waves.

[0071] According to an embodiment, the second sensor (172) includes an electrode sensor, and the electrode sensor may be configured to detect biometric information through contact with the user's body. For example, the electrode sensor may include at least one electrode. The electrode sensor may detect an electrical signal from the body through an electrode in contact with the body under the control of the processor (110), thereby measuring an electrocardiogram (ECG), an electromyogram (EMG), and an electroencephalogram (EEG).

[0072] According to one embodiment, the sensor (170) may include a light sensor, an acceleration sensor, a gyro sensor, a geomagnetic sensor, a barometer, or a temperature sensor.

[0073] The light sensor can detect the brightness of external light. For example, the processor (110) can control the brightness of the display (140) using sensor data detected by the light sensor. The acceleration sensor can detect acceleration or impact caused by the movement of the electronic device (100) or the movement of a user carrying the electronic device (100). The gyro sensor can detect the rotational direction or rotational angle of the electronic device (100) caused by the movement of the electronic device (100) or the movement of a user carrying the electronic device (100). The geomagnetic sensor can detect the direction of geomagnetism. For example, the processor (110) can identify the user's motion (or movement) using sensor data detected by the acceleration sensor, gyro sensor, or geomagnetic sensor. The barometric pressure sensor can detect barometric pressure. For example, the processor (110) can obtain altitude information of the electronic device (100) using sensor data detected by the barometric pressure sensor. A temperature sensor can measure a body's temperature using either a contact or non-contact method. For example, the processor (110) can obtain the user's body temperature information using sensor data detected by the temperature sensor.

[0074]

[0075] FIG. 3 is a perspective view of the front side of an electronic device according to an embodiment of the present disclosure, and FIG. 4 is a perspective view of the rear side of an electronic device according to an embodiment of the present disclosure.

[0076] Referring to FIGS. 3 and 4 , an electronic device (200) according to an embodiment (e.g., the electronic device (100) of FIG. 1 ) may include a housing (210) including a first side (or front side) (210A), a second side (or back side) (210B), and a side surface (210C) surrounding a space between the first side (210A) and the second side (210B), and a fastening member (250, 260) connected to at least a portion of the housing (210) and configured to detachably fasten the electronic device (200) to a body part (e.g., a wrist or an ankle) of a user. In another embodiment, the housing may also refer to a structure forming a portion of the first side (210A), the second side (210B), and the side surface (210C) of FIGS. 3 and 4 . In an embodiment, the first side (210A) may be formed by a front plate (201) that is at least partially substantially transparent (e.g., a glass plate or a polymer plate comprising various coating layers). The second side (210B) may be formed by a substantially opaque back plate (207). The back plate (207) may be formed by, for example, coated or colored glass, ceramic, polymer, metal (e.g., aluminum, stainless steel (STS), or magnesium), or a combination of at least two of the foregoing materials. The side surface (210C) may be formed by a side bezel structure (or “side member”) (206) that is joined to the front plate (201) and the back plate (207) and comprises a metal and / or a polymer. In some embodiments, the back plate (207) and the side bezel structure (206) may be formed integrally and comprise the same material (e.g., a metal material such as aluminum). The above-mentioned fastening member (250, 260) may be formed of various materials and shapes. The integral and multiple unit links may be formed to be mutually movable by a combination of at least two of the above-mentioned materials, such as woven fabric, leather, rubber, urethane, metal, ceramic, or a combination of the above-mentioned materials.

[0077] According to an embodiment, the electronic device (200) may include at least one of a display (220, see FIG. 3), an audio module (205, 208), a sensor module (211), a key input device (202, 203, 204), and a connector hole (209). In some embodiments, the electronic device (200) may omit at least one of the components (e.g., the key input device (202, 203, 204), the connector hole (209), or the sensor module (211)) or may additionally include other components.

[0078] The display (220) may be visually exposed, for example, through a significant portion of the front plate (201). The shape of the display (220) may correspond to the shape of the front plate (201), and may have various shapes such as a circle, an oval, or a polygon. The display (220) may be combined with or disposed adjacent to a touch detection circuit, a pressure sensor capable of measuring the intensity (pressure) of a touch, and / or a fingerprint sensor.

[0079] The audio module (205, 208) may include a microphone hole (205) and a speaker hole (208). The microphone hole (205) may have a microphone (e.g., a microphone (130) of FIG. 2) disposed therein for acquiring external sounds, and in some embodiments, multiple microphones may be disposed therein to detect the direction of sounds. The speaker hole (208) may be used as an external speaker and a receiver for calls. In some embodiments, the speaker hole (208) and the microphone hole (205) may be implemented as a single hole, or a speaker (e.g., a speaker (180) of FIG. 2) may be included without the speaker hole (208) (e.g., a piezo speaker).

[0080] A sensor (211) (e.g., sensor (170) of FIG. 2) can generate an electrical signal or data value corresponding to an internal operating state of the electronic device (200) or an external environmental state. The sensor (211) may include, for example, a biometric sensor (211) (e.g., an HRM sensor) disposed on the second surface (210B) of the housing (210). The electronic device (200) may further include at least one of a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor, which are not illustrated.

[0081] The sensor (211) may include an electrode region (213, 214) forming a portion of a surface of the electronic device (200) and a biosignal detection circuit electrically connected to the electrode region (213, 214). For example, the electrode region (213, 214) may include a first electrode region (213) and a second electrode region (214) disposed on a second surface (210B) of the housing (210). The sensor (211) may be configured such that the electrode region (213, 214) obtains an electrical signal from a portion of the user's body, and the biosignal detection circuit detects bioinformation of the user based on the electrical signal.

[0082] The key input devices (202, 203, 204) may include a wheel key (202) disposed on a first side (210A) of the housing (210) and rotatable in at least one direction, and / or a side key button (203, 204) disposed on a side surface (210C) of the housing (210). The wheel key may have a shape corresponding to the shape of the front plate (201). In other embodiments, the electronic device (200) may not include some or all of the above-mentioned key input devices (202, 203, 204), and the key input devices (202, 203, 204) that are not included may be implemented in another form, such as a soft key, on the display (220). The connector hole (209) may include another connector hole (not shown) that may accommodate a connector (e.g., a USB connector) for transmitting and receiving power and / or data with an external electronic device, and may accommodate a connector for transmitting and receiving audio signals with the external electronic device. The electronic device (200) may further include, for example, a connector cover (not shown) that covers at least a portion of the connector hole (209) and blocks the inflow of external foreign substances into the connector hole.

[0083] The fastening member (250, 260) can be detachably fastened to at least a portion of the housing (210) using a locking member (251, 261). The fastening member (250, 260) can include one or more of a fixing member (252), a fixing member fastening hole (253), a band guide member (254), and a band fastening ring (255).

[0084] The fixing member (252) may be configured to fix the housing (210) and the fastening members (250, 260) to a part of the user's body (e.g., a wrist or an ankle). The fastening member fastening hole (253) may correspond to the fastening member (252) to fasten the housing (210) and the fastening members (250, 260) to a part of the user's body. The band guide member (254) may be configured to limit the range of movement of the fastening member (252) when the fastening member (252) is fastened to the fastening member fastening hole (253), thereby allowing the fastening members (250, 260) to be fastened in close contact with a part of the user's body. The band fixing ring (255) may limit the range of movement of the fastening members (250, 260) when the fastening member (252) and the fastening member fastening hole (253) are fastened.

[0085]

[0086] FIG. 5 is an exploded perspective view of an electronic device according to an embodiment of the present disclosure.

[0087] Referring to FIG. 5, an electronic device (300) (e.g., the electronic device (100) of FIG. 1, or the electronic device (200) of FIGS. 3 to 4) may include a side bezel structure (310), a wheel key (320) (e.g., the wheel key (202) of FIGS. 3 and 4), a front plate (201), a display (220), a first antenna (350), a second antenna (355), a support member (360) (e.g., a bracket), a battery (370), a printed circuit board (380), a sealing member (390), a rear plate (393) (e.g., the rear plate (207) of FIGS. 3 and 4), and fastening members (395, 397) (e.g., the fastening members (250, 260) of FIGS. 3 and 4). At least one of the components of the electronic device (300) may be identical or similar to at least one of the components of the electronic device (100) of FIG. 1 or the electronic device (200) of FIGS. 3 to 4, and any overlapping descriptions will be omitted below. The support member (360) may be disposed inside the electronic device (300) and connected to the side bezel structure (310), or may be formed integrally with the side bezel structure (310). The support member (360) may be formed of, for example, a metal material and / or a non-metallic (e.g., a polymer) material. The support member (360) may have a display (220) coupled to one surface and a printed circuit board (380) coupled to the other surface. The printed circuit board (380) may be equipped with a processor (e.g., the processor (110) of FIG. 2), a memory (e.g., the memory (120) of FIG. 2), and / or an interface. The processor may include, for example, one or more of a central processing unit, a graphics processing unit (GPU), an application processor, a sensor processor, or a communication processor.

[0088] The memory may include, for example, volatile memory (e.g., volatile memory (121) of FIG. 2) or non-volatile memory (e.g., non-volatile memory (122) of FIG. 2). The interface may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, and / or an audio interface. The interface may electrically or physically connect the electronic device (300) to an external electronic device, for example, and may include a USB connector, an SD card / MMC (multimedia card) connector, or an audio connector.

[0089] The battery (370) is a device for supplying power to at least one component of the electronic device (300), and may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell. At least a portion of the battery (370) may be disposed substantially on the same plane as, for example, the printed circuit board (380). The battery (370) may be disposed integrally within the electronic device (300), or may be disposed detachably from the electronic device (300).

[0090] The first antenna (350) may be positioned between the display (220) and the support member (360). The first antenna (350) may include, for example, a near field communication (NFC) antenna, a wireless charging antenna, and / or a magnetic secure transmission (MST) antenna. The first antenna (350) may, for example, perform short-range communication with an external device, wirelessly transmit and receive power required for charging, and transmit a magnetic-based signal including a short-range communication signal or payment data. In another embodiment, the antenna structure may be formed by a portion or a combination of the side bezel structure (310) and / or the support member (360).

[0091] The second antenna (355) may be positioned between the printed circuit board (380) and the back plate (393). The second antenna (355) may include, for example, a near field communication (NFC) antenna, a wireless charging antenna, and / or a magnetic secure transmission (MST) antenna. The second antenna (355) may, for example, perform short-range communication with an external device, wirelessly transmit and receive power required for charging, and transmit a magnetic-based signal including a short-range communication signal or payment data. In another embodiment, the antenna structure may be formed by a portion or a combination of the side bezel structure (310) and / or the back plate (393).

[0092] A sealing member (390) may be positioned between the side bezel structure (310) and the rear plate (393). The sealing member (390) may be configured to block moisture and foreign substances from entering the space surrounded by the side bezel structure (310) and the rear plate (393) from the outside.

[0093]

[0094] FIG. 6 is a diagram illustrating an electronic device for analyzing heart rate at preset time intervals according to an embodiment of the present disclosure.

[0095] An electronic device (100) according to an embodiment of the present disclosure can identify a heart rate at a preset time interval (e.g., P min).

[0096] For example, the electronic device (100) (or the electronic device (200) of FIGS. 3 to 4, the electronic device (300) of FIG. 5) can control the first sensor (171) to obtain first sensing data.

[0097] According to an embodiment, the electronic device (100) may apply first sensing data received from a first sensor (171) (e.g., a PPG sensor) to an analysis algorithm for heart rate to obtain a first analysis result (1).

[0098] For example, the electronic device (100) can control the first sensor (171) to obtain first sensing data including pulse rate variability (PRV).

[0099] According to an embodiment, the first sensing data includes a pulse signal detected by the first sensor (171), and the pulse signal may include noise due to signal distortion (motion artifact) caused by the minute degree of blood vessels of the electronic device (100), ambient light, or movement of a user wearing the electronic device (100).

[0100] According to an embodiment, the electronic device (100) applies the first sensing data to an analysis algorithm, and the analysis algorithm can identify points in time such as systolic peak, starting point, and diastole based on the pulse wave signal from which noise has been removed (or preprocessed) based on a group of parameters constituting the analysis algorithm. Here, the starting point is the point in time when blood flows out of the heart into the aorta, and the diastole is the point in time when the aortic valve closes after the blood flows out.

[0101] For example, an analysis algorithm can interpolate a denoised pulse signal based on a set of parameters that constitute the analysis algorithm, and identify points such as systolic peaks, onsets, and double pulses based on the shape and period information of the pulse signal. For example, the analysis algorithm can perform interpolation to increase the resolution of the pulse signal to more accurately locate peaks.

[0102] According to an embodiment, the analysis algorithm may identify a heart rate based on the reciprocal of the interval between peaks (or peaks) of a pulse signal, and output a first analysis result (1) including whether the heart rate is irregular based on the first sensing data.

[0103] For example, when first sensing data is input, the analysis algorithm outputs a first analysis result (1) corresponding to the first sensing data, and the first analysis result (1) may include an irregular heart rate or a regular heart rate.

[0104] For example, the analysis algorithm may analyze the first sensing data to identify a heart rate, and if the identified heart rate is excessively fast (e.g., 100 bpm or more), excessively slow (e.g., 60 bpm or less), or falls within an abnormally wide range inconsistently, the analysis algorithm may output a first analysis result (1) identifying an irregular heart rate.

[0105] Depending on the group of parameters that constitute the analysis algorithm according to the embodiment, the degree to which the analysis algorithm removes noise from the pulse signal, the degree to which the pulse signal from which the noise has been removed is interpolated, and when the pulse signal is divided into a plurality of intervals and a peak point within the plurality of intervals is identified, the size of each of the plurality of intervals may vary.

[0106] If a group of parameters constituting an analysis algorithm is changed according to an embodiment, the first analysis result (1) output by the analysis algorithm may change.

[0107] For example, the accuracy of the first analysis result (1) output by the analysis algorithm can be evaluated based on i) true positives (TP) in which the first analysis result (1) includes an irregular heart rate when the user's heart rate is actually irregular, ii) false negatives (FN) in which the first analysis result (1) includes a regular heart rate when the user's heart rate is actually irregular, iii) false positives (FP) in which the first analysis result (1) includes an irregular heart rate when the user's heart rate is actually regular, and iv) true negatives (TN) in which the first analysis result (1) includes a regular heart rate when the user's heart rate is actually regular.

[0108] According to an embodiment, the sensitivity of the analysis algorithm may include true positives (TP) (or true positives rate (TPR)) that outputs a first analysis result (1) that includes an irregular heart rate when the user's heart rate is irregular.

[0109] According to an embodiment, the specificity of the analysis algorithm may include true negatives (TN) (or true negatives rate (TNR)) that outputs a first analysis result (1) containing a regular heart rate when the user's heart rate is regular.

[0110] Depending on the embodiment, sensitivity and specificity may be inversely proportional, for example, as the sensitivity of an analysis algorithm increases, specificity may decrease, and as sensitivity decreases, specificity may increase.

[0111] According to an embodiment, the electronic device (100) may set an analysis algorithm by selecting an optimal parameter group among a plurality of parameter groups so that the analysis results include fewer errors (e.g., false negatives (FN), false positives (FP)) while maintaining sensitivity and specificity above a threshold. A detailed description thereof will be provided below with reference to FIG. 9.

[0112]

[0113] According to an embodiment, the electronic device (100) may receive first sensing data from the first sensor (171) and, after a preset time (e.g., P min) has elapsed, receive second sensing data from the first sensor (171).

[0114] According to an embodiment, the second sensing data can be applied to an analysis algorithm to obtain a second analysis result (2).

[0115] According to an embodiment, the electronic device (100) can identify whether the heart rate corresponding to the second sensing data is irregular based on the second analysis result (2), and when an irregular heart rate is identified from each of the first analysis result (1) corresponding to the first sensing data and the second analysis result (2) corresponding to the second sensing data, the electronic device (100) can display a notification through the display.

[0116] For example, when an irregular heartbeat is identified in a first analysis result (1) corresponding to the first sensing data, and an irregular heartbeat is identified in a second analysis result (2) corresponding to the second sensing data received after a preset time has elapsed, i.e., when an irregular heartbeat is continuously identified, the electronic device (100) may display a notification warning of an arrhythmia such as atrial fibrillation or ventricular fibrillation.

[0117] For example, the electronic device (100) may compare the heart rate included in the first analysis result (1) corresponding to the first sensing data with the heart rate included in the second analysis result (2) corresponding to the second sensing data, and if the variability of the heart rate is large (e.g., if the heart rate changes rapidly), a notification warning of an arrhythmia may be displayed.

[0118]

[0119] FIG. 7 is a flowchart illustrating a control method of an electronic device for obtaining a parameter group corresponding to biometric information according to an embodiment of the present disclosure.

[0120] In the following examples, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel.

[0121] According to one embodiment, operations S701 to S709 may be understood to be performed in a processor (e.g., processor (110) of FIG. 2) of an electronic device (e.g., electronic device (100) of FIGS. 1 to 2, electronic device (200) of FIGS. 3 to 4, or electronic device (300) of FIG. 5).

[0122] Referring to FIG. 7, according to an embodiment, the electronic device (100) can obtain the user's biometric information using at least one of the first sensor (171) or the second sensor (172) (S701).

[0123] For example, the biometric information may include at least one of the user's sleep information (e.g., sleep patterns such as deep sleep, light sleep, and REM (rapid eye movement) sleep), activity information (e.g., number of steps, calories burned, distance traveled), stress information (e.g., stress index), blood sugar information, body temperature information, or body composition information (e.g., bioimpedance).

[0124] According to an embodiment, the electronic device (100) can obtain a first parameter group corresponding to biometric information among a plurality of parameter groups (S702).

[0125] For example, the electronic device (100) can assign a score to each of sleep information, activity information, stress information, blood sugar information, body temperature information, or body composition information included in the biometric information, and add up the assigned scores to identify a first parameter group corresponding to the added score among a plurality of parameter groups.

[0126] For example, the electronic device (100) may assign a low score to deep sleep and a high score to light sleep in sleep information, assign a low score to low stress information, and assign a high score to high stress information.

[0127] For example, the electronic device (100) may assign a lower score to a user as the number of steps increases, a higher score to a user as the number of steps decreases, and a lower score to a user as the body fat mass decreases based on body composition information, and a higher score to a user as the body fat mass increases. The above-described examples are merely examples for convenience of explanation, and the present invention is not limited thereto.

[0128] For example, the higher the score (e.g., the more light sleep and stress information), the more likely the user's heart rate is to be irregular, and the lower the score (e.g., the less deep sleep and stress information), the more likely the user's heart rate is to be regular. Additionally, the higher the score (e.g., the fewer steps and the higher the body fat content), the more likely the user's heart rate is to be irregular, and the lower the score (e.g., the more steps and the lower the body fat content), the more likely the user's heart rate is to be regular.

[0129] According to an embodiment, in operation S702, the electronic device (100) may obtain a parameter group (hereinafter, a first parameter group) that increases the sensitivity of the analysis algorithm among a plurality of parameter groups, such that the probability that the analysis algorithm identifies an irregular heartbeat increases as the probability that the user's heartbeat is actually irregular (or: the higher the score) based on the user's biometric information increases.

[0130] In an embodiment, in operation S702, the electronic device (100) may obtain a parameter group (hereinafter, a second parameter group) that reduces the sensitivity of the analysis algorithm (or increases the specificity of the analysis algorithm) from among a plurality of parameter groups, such that the probability that the analysis algorithm identifies an irregular heartbeat decreases as the probability that the user's heartbeat is actually irregular based on the user's biometric information decreases (or, as the score decreases) (or, as the probability that the analysis algorithm identifies a regular heartbeat increases as the probability that the user's heartbeat is actually regular based on the user's biometric information increases).

[0131] According to an embodiment, the electronic device (100) may obtain a parameter group corresponding to the biometric information based on information about the parameter group corresponding to the biometric information stored in a memory (e.g., memory (120) of FIG. 2).

[0132] For example, the electronic device (100) may acquire biometric information such as sleep information, stress information, and body composition, and may acquire a parameter group mapped to the acquired biometric information (e.g., shallow sleep, high stress index, high body fat mass) among a plurality of parameter groups.

[0133] For example, the electronic device (100) may acquire biometric information, such as sleep information, stress information, and body composition, and input the acquired biometric information into a neural network model to acquire a parameter group. A detailed description thereof will be provided below with reference to FIG. 15.

[0134] According to an embodiment, in operation S702, when a first parameter group is obtained based on biometric information, the electronic device (100) can set an analysis algorithm based on the first parameter group (S703).

[0135] In FIG. 7, for convenience of explanation, it is assumed that a first parameter group among a plurality of parameter groups is acquired based on biometric information in operation S702, but the present invention is not limited thereto, and it is of course possible for the electronic device (100) to acquire a second parameter group based on biometric information.

[0136] According to an embodiment, the electronic device (100) may obtain first sensing data from the first sensor (171) when a preset time arrives (S704-Y) (S705). For example, the electronic device (100) may receive sensing data including a pulse signal from the first sensor (171) to measure a heart rate at a preset time (e.g., P min) cycle.

[0137] According to an embodiment, the electronic device (100) can obtain a first analysis result (1) by applying the first sensing data to an analysis algorithm set according to the first parameter group (S706).

[0138] According to an embodiment, the first analysis result (1) may include an analysis result on whether the user's heart rate is irregular based on the first sensing data. According to an embodiment, the electronic device (100) may identify whether the heart rate is irregular based on the first analysis result (S707).

[0139] According to an embodiment, if an irregular heartbeat is identified from the first analysis result (1) (S708-Y), the electronic device (100) may display a notification (S709). For example, in operation S709, the electronic device (100) may display a notification to warn of an irregular heartbeat.

[0140] According to an embodiment, if the preset time does not arrive (S704-N), the electronic device (100) may not acquire the first sensing data until the preset time arrives.

[0141] According to an embodiment, the electronic device (100) may not provide a notification if an irregular heartbeat is not identified from the first analysis result (1) (S708-N). For example, the electronic device (100) may not provide a notification if an irregular heartbeat is not identified from the first analysis result (1) (S708-N), since the user's heartbeat is normal and no warning is necessary.

[0142]

[0143] FIG. 8 is a flowchart illustrating a control method of an electronic device that provides a notification when an irregular heart rate is identified based on a plurality of analysis results according to an embodiment of the present disclosure.

[0144] In the following examples, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel.

[0145] According to one embodiment, operations S801 to S820 may be understood to be performed in a processor (e.g., processor (110) of FIG. 2) of an electronic device (e.g., electronic device (100) of FIGS. 1 to 2, electronic device (200) of FIGS. 3 to 4, or electronic device (300) of FIG. 5).

[0146] Since each of operations S801 to S807 illustrated in FIG. 8 is identical to operations S701 to S707 illustrated in FIG. 7, duplicate descriptions will be omitted.

[0147] Referring to FIG. 8, the electronic device (100) can maintain the first parameter group when an irregular heart rate is identified from the first analysis result (1) (S808-Y).

[0148] For example, after setting an analysis algorithm by acquiring a first parameter group that increases the sensitivity of the analysis algorithm based on the user's biometric information in operations S801 to S802, if the first analysis result (1) output by the analysis algorithm based on the first sensing data includes an irregular heartbeat, the electronic device (100) may not reset (or may maintain) the analysis algorithm set according to the first parameter group.

[0149] The electronic device (100) can identify an irregular heartbeat from the first analysis result (1) (S808-Y), acquire first sensing data, and when a preset time elapses (S809-Y), acquire second sensing data from the first sensor (171) (S810).

[0150] According to an embodiment, the electronic device (100) can obtain a second analysis result (2) by applying the second sensing data to an analysis algorithm set based on the first parameter group (S811).

[0151] According to an embodiment, the electronic device (100) can identify whether the heart rate is irregular based on the second analysis result (2) (S812).

[0152] According to an embodiment, the electronic device (100) identifies an irregular heartbeat from the first analysis result (1) and the second analysis result (2) (S813), and when an irregular heartbeat is identified from the first analysis result (1) and the second analysis result (2), a notification can be displayed (S814).

[0153] For example, in operation S814, the electronic device (100) may compare the heart rate according to the first analysis result (1) with the heart rate according to the second analysis result (2), and if the variability of the heart rate is large (e.g., if the heart rate changes rapidly), a notification warning of an arrhythmia may be displayed.

[0154] For example, if an irregular heart rate is identified based on the first analysis result (1) in operation S807 and an irregular heart rate is identified based on the second analysis result (2) in operation S812, the electronic device (100) may display a notification in operation S814.

[0155] The electronic device (100) according to the embodiment can obtain a second parameter group from among a plurality of parameter groups (S815) if an irregular heartbeat is not identified from the first analysis result (1) (S808-N).

[0156] For example, after setting the analysis algorithm by obtaining a first parameter group that increases the sensitivity of the analysis algorithm based on the user's biometric information in operations S801 to S802, if the first analysis result (1) output by the analysis algorithm based on the first sensing data does not include an irregular heartbeat, the electronic device (100) can reset the analysis algorithm set according to the first parameter group. For example, the electronic device (100) can obtain a second parameter group that decreases the sensitivity of the algorithm, and reset the analysis algorithm based on the second parameter group (S816).

[0157] According to an embodiment, the electronic device (100) may acquire first sensing data and, when a preset time elapses (S817-Y), acquire second sensing data from the first sensor (171) (S818).

[0158] According to an embodiment, the electronic device (100) can obtain a second analysis result (2) by applying the second sensing data to an analysis algorithm that is reset according to a second parameter group (S819).

[0159] According to an embodiment, the electronic device (100) can identify whether the heart rate is irregular based on the second analysis result (2) (S820). According to an embodiment, if an irregular heart rate is identified from each of the first analysis result (1) and the second analysis result (2), the electronic device (100) can display a notification (S814).

[0160] For example, if an irregular heart rate is identified based on the second analysis result in operation S820, the electronic device (100) may display a notification in operation S814.

[0161] For example, the electronic device (100) may identify a heart rate according to the first analysis result (1) in operation S807, identify a heart rate according to the second analysis result (2) in operation S820, and compare the heart rate according to the first analysis result (1) with the heart rate according to the second analysis result (2) in operation S814. If the variability of the heart rate is large (e.g., if the heart rate changes rapidly), the electronic device (100) may display a notification warning of an arrhythmia. According to an embodiment, if the preset time does not arrive in operation S804 (S804-N), the electronic device (100) may not acquire the first sensing data until the preset time arrives.

[0162] According to an embodiment, the electronic device (100) may not acquire the second sensing data until the preset time arrives (S809-N) in operation S809, if the preset time does not arrive. For example, the electronic device (100) may not acquire the second sensing data until the preset time (e.g., P min) elapses (S809-N) after the preset time arrives (S804-Y) in operation S804.

[0163] According to an embodiment, the electronic device (100) may not acquire the second sensing data until the preset time arrives (S817-N) in operation S817, if the preset time does not arrive. For example, the electronic device (100) may not acquire the second sensing data until the preset time (e.g., P min) elapses (S817-N) after the preset time arrives (S804-Y) in operation S804.

[0164]

[0165] FIG. 9 is a diagram illustrating an ROC curve according to an embodiment of the present disclosure.

[0166] Referring to Figure 9, if the parameter group constituting the analysis algorithm changes, the analysis results output by the analysis algorithm may vary. For example, depending on the parameter group constituting the analysis algorithm, the analysis algorithm may output analysis results that include an irregular heartbeat or analysis results that include a regular heartbeat for the same sensing data.

[0167] As described above, the analysis results output by the analysis algorithm can be divided into: i) true positives (TP), which include an irregular heart rate when the user's heart rate is actually irregular; ii) false negatives (FN), which include a regular heart rate when the user's heart rate is actually irregular; iii) false positives (FP), which include an irregular heart rate when the user's heart rate is actually regular; and iv) true negatives (TN), which include a regular heart rate when the user's heart rate is actually regular.

[0168] For example, the accuracy of an analysis algorithm may include i) TP and iv) TN, sensitivity may include i) TP (or true positives rate (TPR), and specificity may include iv) TN (or true negatives rate (TNR).

[0169] According to the ROC curve illustrated in Figure 9, the area formed by the ROC curve and the x-axis is called the area under curve (AUC), and can have a value between 0 and 1. The closer the AUC is to 1, the more consistent the analysis results output by the analysis algorithm are with the irregularity of the user's actual heart rate.

[0170] In some embodiments, the x-axis of the ROC curve may represent the false positive rate (fpr), which may represent the proportion of cases that are actually negative or incorrectly classified as positive. In some embodiments, the y-axis of the ROC curve may represent the true positive rate (tpr), which may represent the proportion of cases that are actually positive or correctly classified as positive.

[0171] Referring to FIG. 9, for example, the plurality of parameter groups may include parameter group A, parameter group B, parameter group C, and parameter group D.

[0172] According to an embodiment, for each of the plurality of parameter groups, as sensitivity increases, specificity may decrease.

[0173] For example, the electronic device (100) can set an analysis algorithm by selecting parameter group B as a basic parameter group among a plurality of parameter groups so that the analysis results include fewer errors (e.g., false negatives (FN), false positives (FP)) while maintaining sensitivity and specificity above a threshold (e.g., 80%), respectively.

[0174] According to an embodiment, the electronic device (100) may reset the analysis algorithm based on parameter group A that increases sensitivity (or decreases specificity) so that the probability of the analysis algorithm identifying an irregular heart rate increases (or the probability of the predicted heart rate increasing) as the probability of the user's actual heart rate being irregular based on biometric information increases.

[0175] According to an embodiment, the electronic device (100) may reset the analysis algorithm based on parameter group C (or parameter group D) to decrease sensitivity (or increase specificity) so that the probability of the analysis algorithm identifying an irregular heart rate (or the probability of the predicted heart rate being irregular) decreases as the probability of the user's actual heart rate being irregular based on biometric information decreases.

[0176]

[0177] FIG. 10 is a diagram illustrating an electronic device that identifies whether a heartbeat is irregular using an electronic device and an external electronic device, respectively, according to an embodiment of the present disclosure.

[0178] In the above example, it is assumed that a user's heart rate is measured using one electronic device (e.g., the electronic device (100) of FIG. 1), but of course, it is not limited thereto.

[0179] According to various embodiments of the present disclosure, a user's heart rate may be measured using each of an electronic device (100) and an external electronic device (e.g., an external electronic device (400) of FIG. 10).

[0180] In the past, when an irregular heartbeat was identified by an electronic device (100), the first sensor (171) (e.g., a PPG sensor) was controlled to measure the heartbeat at a shorter cycle than a preset time (e.g., P min). However, as the cycle for measuring the heartbeat using the first sensor (171) became shorter, the power consumption of the electronic device (100) increased, and there was a problem in that the electronic device (100) was discharged or required to be charged before identifying an irregular heartbeat more than a preset number of times to determine whether or not there was an arrhythmia.

[0181] According to an embodiment, the electronic device (100) may set a schedule for receiving sensing data from the electronic device (100) and receiving additional sensing data from an external electronic device (400).

[0182] For example, at a first point in time, the electronic device (100) can obtain first sensing data and apply the first sensing data to an analysis algorithm to obtain a first analysis result (1).

[0183] According to an embodiment, the electronic device (100) may obtain first additional sensing data from an external electronic device (400) at a time point 1-1 between a first time point and a second time point after a preset time (e.g., P min) has elapsed from the first time point based on a schedule, and may apply the first additional sensing data to an analysis algorithm to obtain a first additional analysis result (A).

[0184] According to an embodiment, the electronic device (100) may obtain second sensing data at a second time point and apply the second sensing data to an analysis algorithm to obtain a second analysis result (2).

[0185] According to an embodiment, the electronic device (100) may obtain second additional sensing data from an external electronic device (400) at a time point 2-1 after a preset time has elapsed from the time point 1-1, and apply the second additional sensing data to an analysis algorithm to obtain a second additional analysis result (B).

[0186] As described above, the electronic device (100) communicates with an external electronic device (400), and if the external electronic device (400) can obtain sensing data including a pulse signal using a PPG sensor, a schedule can be set for when each of the electronic device (100) and the external electronic device (400) obtains the sensing data.

[0187] According to an embodiment, the electronic device (100) can determine whether or not an arrhythmia is present by identifying an irregular heartbeat that is greater than a preset number of times based on sensing data acquired through each of the electronic device (100) and the external electronic device (400) without changing the cycle for measuring the heart rate to a shorter period (or without increasing the power consumption of the electronic device (100).

[0188] For example, comparing FIG. 6 and FIG. 10, as shown in FIG. 6, before a preset time elapses from the second point in time, the electronic device (100) can acquire first sensing data and second sensing data, and as shown in FIG. 10, the electronic device (100) can acquire first sensing data, first additional sensing data, second sensing data, and second additional sensing data.

[0189] According to an embodiment, the electronic device (100) may compare a first analysis result (1) based on first sensing data acquired at a first time point, a first additional analysis result (A) based on first additional sensing data acquired through an external electronic device (400) at a time point 1-1, a second analysis result (2) based on second sensing data acquired at a second time point, and a second additional analysis result (B) based on second additional sensing data acquired through an external electronic device (400) at a time point 2-1, and display a notification warning of an arrhythmia when the variability of the heart rate is large (e.g., when the heart rate changes rapidly).

[0190] For example, if an irregular heart rate is identified from each of the first analysis result (1), the first additional analysis result (A), the second analysis result (2), and the second additional analysis result (B), the electronic device (100) may display a notification warning of an arrhythmia.

[0191] In the above-described example, it is assumed and described that the electronic device (100) receives sensing data (e.g., first additional sensing data, second additional sensing data) from an external electronic device (400), but it is of course not limited thereto.

[0192] An external electronic device (400) may acquire sensing data via a PPG sensor, similar to the electronic device (100) according to various embodiments of the present disclosure, and may apply the sensing data to an analysis algorithm to obtain analysis results on heart rate and whether the heart rate is irregular. Depending on the embodiment, the external electronic device (400) may also transmit the analysis results to the electronic device (100).

[0193] In the above-described example, it is assumed that the electronic device (100) and the external electronic device (400) each set a schedule for when they acquire sensing data, but it is of course not limited thereto.

[0194] According to an embodiment, an electronic device (100) includes a user terminal device, and the electronic device (100) can set a schedule for when each of a plurality of external electronic devices (e.g., wearable devices) acquires sensing data, and control each of the plurality of external electronic devices to acquire sensing data according to the schedule.

[0195] According to an embodiment, when sensing data is received from each of a plurality of external electronic devices, the electronic device (100) may apply each of the plurality of sensing data to an analysis algorithm to obtain a plurality of analysis results. According to an embodiment, the electronic device (100) may identify an irregular heartbeat based on the plurality of analysis results and display a notification warning of an arrhythmia.

[0196]

[0197] FIG. 11 is a diagram illustrating the configuration of an external electronic device according to an embodiment of the present disclosure. FIG. 12 is a front view of an external electronic device according to an embodiment of the present disclosure. FIG. 13 is an exploded perspective view of an external electronic device according to an embodiment of the present disclosure. For example, FIG. 13 is an exploded perspective view of the external electronic device of FIG. 11.

[0198] According to an embodiment, the electronic device (100) or the external electronic device (400) according to an embodiment of the present disclosure may include a ring-shaped wearable device worn on a user's finger as illustrated in FIGS. 11 to 13. However, the present invention is not limited thereto, and may include a bracelet-type wearable device, an open-type ring-shaped electronic device with a portion open, or a curved or non-curved electronic device.

[0199] Referring to FIGS. 11 and 12 , the external electronic device (400) may be formed in an annular shape including an opening (4001) therein. In an embodiment, the external electronic device (400) may include an annular first housing (410) (e.g., an outer ring housing, a first ring housing, or a first housing portion) and an annular second housing (420) (e.g., an inner ring housing, a second ring housing, or a second housing portion) coupled to the first housing (410) and including an opening (4001). The opening (4001) may be formed to be sized such that a user's finger can be inserted therein.

[0200] For example, the first housing (410) may be formed of a material that is resistant to external impact or scratches, such as metal, ceramic, or stainless steel. The first housing (410) may also undergo a separate fixing or coating process for color implementation. The second housing (420) may be formed of the same material as the first housing (410), or may be formed of a material such as a molding material, plastic, or glass for sensing. The second housing (420) may also be formed so that at least a portion thereof is comprised of a metal material for biometric measurement.

[0201] In an embodiment, the external electronic device (400) may include at least one protrusion (4201) protruding from the second housing (420) toward the opening (4001). In an embodiment, the at least one protrusion (4201) may be arranged in an internal space of the external electronic device (400) and may have a shape that is advantageous for detecting an external environment or contacting a user's skin. In some embodiments, the at least one protrusion (4201) may be used as a means for preventing the external electronic device (400) from being arbitrarily rotated on a finger.

[0202] According to an embodiment, the external electronic device (400) may include at least one electrical element disposed in a space between the first housing (410) and the second housing (420). In an embodiment, the at least one electrical element may include at least one biometric sensor, a substrate, a display (401), or an output module disposed to detect biometric information of a user through at least a portion of the second housing (420). In an embodiment, the substrate (e.g., the substrate (440) of FIG. 13) may include a flexible printed circuit board (FPCB) having a bendability to correspond to the curvature of the external electronic device (400). In an embodiment, the display (401) may be disposed to be visible from the outside through a portion (e.g., an outer circumferential surface) of the first housing (410). In an embodiment, the external electronic device (400) may further include an indicator, such as an LED, that may provide visual output information to the user. In some embodiments, the indicator may replace the display (401). In an embodiment, the area of ​​the display (401) may be formed across the entire front of the first housing (410). In an embodiment, the output module may include at least one speaker (not shown) for providing auditory output information to the user. In an embodiment, the output module may include a haptic module for providing tactile output information to the user.

[0203] Referring to FIG. 13, the external electronic device (400) may include a first housing (410), a second housing (420) coupled with the first housing (410), and a battery (430) disposed between the first housing (410) and the second housing (420).

[0204] In an embodiment, the external electronic device (400) may be disposed between a first housing (410) and a second housing (420) and may include a substrate (440) including a plurality of electrical elements. In an embodiment, the substrate (440) may include a flexible printed circuit board (FPCB) having a bendability to correspond to the curvature of the external electronic device (400). In some embodiments, the substrate (440) may include a substrate or a plurality of hard type printed circuit boards (PCBs) including a hard type area having a width and length that are not interfered with by the curvature of the first housing (410) and / or the second housing (420). In an embodiment, the battery (430) may be disposed between the first housing (410) and the second housing (420) in a manner of being spaced apart from the substrate (440) by a predetermined distance, and may be electrically connected to the substrate (440) via a cable. In an embodiment, the battery (430) may be formed in a curved shape to have a curvature substantially the same as the curvature of the first housing (410). In some embodiments, the battery (430) may be positioned between the first housing (410) and the second housing (420) in a shape having a curvature different from the curvature of the first housing (410) and / or the curvature of the second housing (420).

[0205] According to an embodiment, the first housing (410) may be formed of a metal material, ceramic, or PC (polycarbonate) material. In an embodiment, the second housing (420) may be formed of a molding material and may be combined with the first housing (410) through a molding process. In an embodiment, the second housing (420) may include a first molding layer (421) arranged to cover at least a portion of the battery (430) and a second molding layer (422) that covers the first molding layer (421) and is combined with the first housing (410). In an embodiment, the first molding layer (421) may be arranged to cover the entirety of the battery (430) and at least partially contact the inner surface of the first housing (410).

[0206]

[0207] FIG. 14 is a drawing illustrating the configuration of an external electronic device according to an embodiment of the present disclosure.

[0208] An external electronic device (400) according to an embodiment may include a processor (441), a memory (442), a communication module (443), an antenna (444), a battery (430), a charging interface (445), at least one first sensor (450), a second sensor (446), a third sensor (447), a temperature sensor (448), and a power management integrated circuit (PMIC) (449). Some of the components may be arranged on a substrate (440) (e.g., FPCB, flexible printed circuit board) having flexibility to correspond to the curvature of the external electronic device (400).

[0209] According to some embodiments, the external electronic device (400) may further include other components (e.g., a display, an ultrasonic sensor, an audio output device) in addition to the components illustrated.

[0210] The communication module (443) according to an embodiment may include various hardware and / or software configurations to support wireless communication with the electronic device (100). The external electronic device (400) may transmit and receive various data or control commands with the electronic device (100) via the communication module (443) via wired / wireless communication. In an embodiment, the communication module may support short-range wireless communication. Short-range wireless communication includes at least one of Bluetooth, BLE (Bluetooth Low Energy), ZigBee, ANT+, Wi-Fi, Cellular (LTE, 5G, 6G, NB-IoT), NFC (near field communication), RFID (radio frequency identification), UWB (ultra wide band), GNSS (global navigation satellite system) and / or MST (magnetic secure transmission), but is not limited thereto. According to some embodiments, the communication module (443) may be implemented in an integrated form with the processor (441).

[0211] An antenna (444) according to an embodiment may be connected to a communication module (443) via a substrate (440). An external electronic device (400) may transmit or receive communication signals / data to the outside via the antenna (444). The antenna (444) may include a single or multiple antennas. In some embodiments, a part of the first housing (410) (e.g., a metal member) may be designed to be used as an antenna (444).

[0212] The battery (430) according to the embodiment may be formed in a curved shape so as to have a curvature corresponding to the curvature of the space between the first housing (410) and the second housing (420). The battery (430) may be configured such that multiple battery packs are separately arranged. The battery (430) may be connected to a charging interface (445).

[0213] A charging interface (445) according to an embodiment may be electrically connected to a PMIC (449) mounted on a substrate (440) via the substrate (440). The charging interface (445) may support wired charging (terminal) or wireless charging (WPC, NFC) for charging.

[0214] At least one first sensor (450) according to an embodiment can obtain various bio-information of the user using an optical signal. For example, the first sensor (450) may be a photoplethysmogram (PPG) sensor or an optical sensor that can obtain various bio-information such as heart rate and blood circulation by measuring a plethysmogram according to an optical signal, but is not limited thereto. The first sensor (450) can obtain bio-information such as heart rate (HR), blood pressure, saturation of percutaneous oxygen (SpO2), galvanic skin response (GSR), electrocardiography (ECG), blood flow velocity, and bioelectrical impedance, but is not limited thereto.

[0215] According to some embodiments, the first sensor (450) may include a fingerprint sensor.

[0216] A first sensor (450) according to an embodiment may include a sensor controller (450a), a plurality of emitters (450b) for outputting optical signals, and a plurality of light receivers (450c) for receiving optical signals. The plurality of emitters (450b) may include light emitting elements that emit light of various wavelengths or colors (e.g., green, red) to measure a biosignal. The plurality of emitters (450b) may be formed of at least one of a light emitting diode (LED), a semiconductor laser diode (LD), an infrared (IR) diode, and a vertical cavity surface emitting laser (VCSEL). The plurality of light receivers (450c) may be formed of a photodiode (PD) or a complementary metal-oxide-semiconductor (CMOS) camera. A plurality of light receiving units (450c) can convert the received light signal through an analog to digital converter (ADC) and store it in a processor (441) or memory (442). A sensor controller (450a) can control a plurality of light emitting units (450b) and a plurality of light receiving units (450c).

[0217] According to an embodiment, the first sensor (450) may be called a biometric sensor, and for convenience of explanation, it will be collectively referred to as the first sensor (450) hereinafter.

[0218] The second sensor (446) according to an embodiment can detect a touch signal of a user touching an external electronic device (400). The second sensor (446) can be formed in at least one of a pressure type, an electrostatic type, an optical type, or an ultrasonic type, for example. The second sensor (446) according to an embodiment may include a fingerprint sensor. According to some embodiments, the second sensor (446) may be omitted. According to an embodiment, the second sensor (446) may be called a touch sensor, and for the convenience of explanation, it will be collectively referred to as the second sensor (446) hereinafter.

[0219] The third sensor (447) according to an embodiment can obtain movement information of an external electronic device (400). For example, the third sensor (447) can detect motion, gesture, impact, posture, and / or activity (e.g., sedentary, moving, sports). The third sensor (447) may be formed as a three-axis accelerometer, but is not limited thereto, and may be formed as a six-axis sensor including an accelerometer and a gyroscope. Depending on the embodiment, the third sensor (447) may be called an inertial sensor or an acceleration sensor, but for the convenience of explanation, it will be collectively referred to as the third sensor (447) hereinafter.

[0220] A temperature sensor (448) according to an embodiment can measure the body temperature of a user or the temperature of a component (e.g., an electronic component) included in an external electronic device (400). The temperature sensor (448) can be formed in a contact or non-contact manner and may vary depending on the design. The external electronic device (400) can record the temperature information recorded through the temperature sensor (448) in a memory (442), or measure the body temperature of the user under the control of the processor (441), and utilize it to estimate skin temperature or estimate situational awareness.

[0221] A PMIC (449) according to an embodiment can manage power delivered from a battery (430) to each component of an external electronic device (400).

[0222] The memory (442) according to the embodiment may store various instructions that may be performed by the processor (441). Such instructions may include arithmetic and logical operations, data movement, or control commands such as input / output that may be recognized by the processor (441).

[0223] The processor (441) according to the embodiment is a configuration capable of performing calculations or data processing related to control and / or communication of each component of the external electronic device (400), and may be composed of one or more processors. The calculation and data processing functions that the processor (441) may implement on the external electronic device (400) are not limited, but may process various operations according to the present disclosure in conjunction with the electronic device (100).

[0224]

[0225] FIG. 15 is a diagram illustrating an electronic device for obtaining a parameter group using a neural network model according to an embodiment of the present disclosure.

[0226] Referring to FIG. 15, the electronic device (100) can obtain context information based on user input in addition to biometric information.

[0227] For example, context information may include at least one of age information, gender information, disease information, medication information, or information about whether or not the individual is drinking alcohol.

[0228] For example, the electronic device (100) may obtain age information and gender information based on the user's profile information, and may obtain information on the user's specific disease, information on the user's medication, and information on the user's recent number of drinks or amount of drinks from the user's input or the user's health-related application. However, the present invention is not limited thereto, and the electronic device (100) may obtain at least one of age information, gender information, disease information (or surgery history information), or medication information by receiving the user's health checkup results from the server.

[0229] According to an embodiment, the electronic device (100) may assign a score to each of age information, gender information, disease information, medication information, or information on whether or not one is drinking included in the context information, and may identify a first parameter group corresponding to the summed score among a plurality of parameter groups by adding up the assigned scores.

[0230] For example, the electronic device (100) may give a high score based on age information if the person is older or taking heart-related medication, and a low score if the person has not recently consumed alcohol or has no history of heart-related surgery.

[0231] For example, the higher the score (e.g., the more recent alcohol consumption and the more history of heart surgery), the more likely the user is to have an irregular heart rate, and the lower the score (e.g., the less recent alcohol consumption and the less history of heart surgery), the more likely the user is to have a regular heart rate.

[0232] According to an embodiment, the electronic device (100) may obtain a first parameter group that increases the sensitivity of the analysis algorithm among a plurality of parameter groups, such that the probability that the user's heart rate is actually irregular (or: the higher the score) increases based on the user's context information, and the probability that the analysis algorithm identifies an irregular heart rate increases.

[0233] According to an embodiment, the electronic device (100) may obtain a second parameter group that reduces the sensitivity of the analysis algorithm among a plurality of parameter groups, such that the probability that the user's heart rate is actually irregular (or, the lower the score) decreases based on the user's context information, thereby reducing the probability that the analysis algorithm identifies an irregular heart rate.

[0234] For example, as shown in Table 1 below, one parameter group among multiple parameter groups can be mapped based on the user's biometric information and context information.

[0235] Classification: Cardiac disease / surgical history, drinking the previous day, sleep apnea, irregular heartbeat, number of consecutive detections, parameter group 10, irrelevant, irrelevant, group 1, group 2, X0, irrelevant, group 1, group 3, XX0, irrelevant, group 2, group 4, XXX, more than once, group 3, group 5, XXX, group 4

[0236] According to an embodiment, when a first parameter group is acquired from among a plurality of parameter groups based on biometric information and context information, the electronic device (100) can set an analysis algorithm based on the first parameter group. In the above-described example, a case in which one parameter group from among a plurality of parameter groups is acquired based on a rule has been described, but it is of course not limited thereto.

[0237] For example, as illustrated in FIG. 15, the electronic device (100) can obtain a first parameter group that increases sensitivity (or a second parameter group that decreases sensitivity) by inputting at least one of biometric information and contextual information into a neural network model.

[0238] According to an embodiment, the neural network model may be a model trained to output a group of parameters for setting an analysis algorithm when at least one of biometric information or contextual information is input.

[0239] For example, a neural network model can be trained to generate a group of parameters that increase the probability that the analysis algorithm outputs an irregular heart rate as an analysis result, as the user's actual heart rate is more likely to be irregular based on the user's state (e.g., the user's biometric information, context information).

[0240] Additionally, the neural network model can be trained to generate a group of parameters that lower the probability that the analysis algorithm outputs an irregular heart rate as an analysis result, as the probability that the user's actual heart rate is irregular based on the user's condition is lower.

[0241]

[0242] FIG. 16 is a drawing illustrating an electronic device displaying a notification according to an embodiment of the present disclosure.

[0243] Referring to FIG. 16, the electronic device (100) may provide a notification (1000A, 1000B) warning of an irregular heart rate (or warning of an arrhythmia) when an irregular heart rate is continuously identified.

[0244] For example, the electronic device (100) may display a notification (1000A, 1000B) when an irregular heartbeat is identified based on a first analysis result (1) identified from the first sensing data and an irregular heartbeat is identified based on a second analysis result (2) identified from the second sensing data.

[0245] According to an embodiment, the electronic device (100) may display a notification (1000B) or control the user terminal device to display a notification (1000A).

[0246] According to an embodiment, the notification (1000A, 1000B) may include a UI that guides the user to measure a heart rate through the second sensor (172). For example, the second sensor (172) includes an electrocardiogram (ECG) measurement sensor, and when a user input for the UI included in the notification (1000A, 1000B) is received, the electronic device (100) may control the second sensor (172) to detect the user's ECG.

[0247] According to an embodiment, the second sensor (172) detects irregular heartbeats based on heart rate variability (HRV), unlike a PPG sensor based on pulse rate variability (PRV), and can detect arrhythmias such as atrial fibrillation and ventricular fibrillation.

[0248] According to an embodiment, the electronic device (100) can detect an arrhythmia by activating the second sensor (172) only when an irregular heartbeat is continuously detected through the first sensor (171), rather than activating the second sensor (172) at a preset time cycle.

[0249]

[0250] According to an embodiment, an electronic device (e.g., an electronic device (100) of FIG. 2) includes a first sensor (e.g., a first sensor (171) of FIG. 2), a second sensor (e.g., a second sensor (172) of FIG. 2), a display (e.g., a display (140) of FIG. 2), at least one processor (e.g., a processor (110) of FIG. 2) including a processing circuit), and a memory (e.g., a memory (120) of FIG. 2) storing instructions and including one or more storage media, wherein the instructions, when individually or collectively executed by the at least one processor, cause the electronic device to obtain biometric information of a user using at least one of the first sensor or the second sensor, obtain a first parameter group from among a plurality of parameter groups based on the biometric information, set an analysis algorithm for a heart rate based on the first parameter group, control the first sensor to obtain first sensing data, and analyze the first sensing data with the analysis algorithm. It is configured to obtain a first analysis result by applying the first analysis result and to identify whether the heart rate corresponding to the first sensing data is irregular based on the first analysis result.

[0251] For example, the instructions may be configured to cause the electronic device to receive the first sensing data, receive second sensing data from the first sensor after a preset period of time has elapsed, apply the second sensing data to the analysis algorithm to obtain a second analysis result, identify whether a heart rate corresponding to the second sensing data is irregular based on the second analysis result, and display a notification through the display when an irregular heart rate is identified from each of the first analysis result and the second analysis result.

[0252] For example, the instructions may be configured to cause the electronic device to, if the irregular heartbeat is identified based on the first analysis result, apply the second sensing data to the analysis algorithm to obtain the second analysis result, and if the irregular heartbeat is not identified based on the first analysis result, obtain a second parameter group from among the plurality of parameter groups, reset the analysis algorithm based on the second parameter group, and apply the second sensing data to the reset analysis algorithm to obtain the second analysis result.

[0253] For example, the instructions may be configured to cause the electronic device to receive the second sensing data, receive third sensing data from the first sensor after the preset time has elapsed, apply the third sensing data to the analysis algorithm to obtain a third analysis result, identify whether a heart rate corresponding to the third sensing data is irregular based on the third analysis result, and if an irregular heart rate is not identified from the third analysis result, obtain a second parameter group from among the plurality of parameter groups, and reset the analysis algorithm based on the second parameter group.

[0254] For example, the first parameter group may be a parameter group that increases the sensitivity of the analysis algorithm by increasing the probability that the analysis algorithm identifies the irregular heartbeat when sensing data is applied to the analysis algorithm, and the second parameter group may be a parameter group that decreases the probability that the analysis algorithm identifies the irregular heartbeat when sensing data is applied to the analysis algorithm, thereby decreasing the sensitivity of the analysis algorithm.

[0255] For example, the electronic device may further include a communication interface, and the instructions may be configured to cause the electronic device to schedule, when the irregular heartbeat is identified based on the first analysis result, to receive additional sensing data acquired by the external electronic device from the external electronic device between the preset time periods, when the additional sensing data is received from the external electronic device according to the schedule, to apply the additional sensing data to the analysis algorithm to obtain an additional analysis result, and to identify whether a heartbeat corresponding to the additional sensing data is irregular based on the additional analysis result, and to display the notification when an irregular heartbeat is identified from each of the first analysis result, the additional analysis result, and the second analysis result.

[0256] For example, the external electronic device may be a wearable device worn by the user.

[0257] For example, the biometric information may include at least one of sleep information, activity information, stress information, blood sugar information, or body composition information.

[0258] For example, the instructions may be configured to cause the electronic device to obtain context information based on a user input, and obtain the first parameter group from among the plurality of parameter groups based on the biometric information and the context information.

[0259] For example, the context information may include at least one of age information, gender information, disease information, or medication information.

[0260] For example, the instructions may be configured to cause the electronic device to input the biometric information and the context information into a neural network model to obtain the first parameter group.

[0261] For example, the neural network model can be trained to output a group of parameters for setting the analysis algorithm according to the biometric information and the context information when the biometric information and the context information are input.

[0262] For example, the instructions may be configured to cause the electronic device to display the notification including a UI that guides the electronic device to detect whether the user's heart rate is irregular through the second sensor when an irregular heart rate is identified from each of the first analysis result and the second analysis result.

[0263]

[0264] In a method for controlling an electronic device (e.g., an electronic device (100) of FIG. 2) according to an embodiment, the electronic device may include a first sensor (e.g., a first sensor (171) of FIG. 2) and a second sensor (e.g., a second sensor (172) of FIG. 2).

[0265] The method may include an operation of obtaining biometric information of a user using at least one of the first sensor or the second sensor, an operation of obtaining a first parameter group from among a plurality of parameter groups based on the biometric information, an operation of setting an analysis algorithm for a heart rate based on the first parameter group, an operation of controlling the first sensor to obtain first sensing data, an operation of applying the first sensing data to the analysis algorithm to obtain a first analysis result, and an operation of identifying whether a heart rate corresponding to the first sensing data is irregular based on the first analysis result.

[0266] For example, the method may include an operation of receiving the first sensing data and, after a preset time has elapsed, receiving second sensing data from the first sensor, an operation of applying the second sensing data to the analysis algorithm to obtain a second analysis result, an operation of identifying whether a heart rate corresponding to the second sensing data is irregular based on the second analysis result, and an operation of displaying a notification through the display when an irregular heart rate is identified from each of the first analysis result and the second analysis result.

[0267] For example, the operation of obtaining the second analysis result may include an operation of applying the second sensing data to the analysis algorithm to obtain the second analysis result if the irregular heart rate is identified based on the first analysis result, and an operation of obtaining a second parameter group from among the plurality of parameter groups, resetting the analysis algorithm based on the second parameter group, and applying the second sensing data to the re-set analysis algorithm to obtain the second analysis result if the irregular heart rate is not identified based on the first analysis result.

[0268] For example, the method may include an operation of receiving the second sensing data and receiving third sensing data from the first sensor after the preset time has elapsed, an operation of applying the third sensing data to the analysis algorithm to obtain a third analysis result, an operation of identifying whether a heart rate corresponding to the third sensing data is irregular based on the third analysis result, and an operation of acquiring a second parameter group from among the plurality of parameter groups and resetting the analysis algorithm based on the second parameter group if an irregular heart rate is not identified from the third analysis result.

[0269] For example, the first parameter group may be a parameter group that increases the sensitivity of the analysis algorithm by increasing the probability that the analysis algorithm identifies the irregular heartbeat when sensing data is applied to the analysis algorithm, and the second parameter group may be a parameter group that decreases the probability that the analysis algorithm identifies the irregular heartbeat when sensing data is applied to the analysis algorithm, thereby decreasing the sensitivity of the analysis algorithm.

[0270] For example, the method may further include, when the irregular heart rate is identified based on the first analysis result, setting a schedule to receive additional sensing data acquired by the external electronic device between the preset times from the external electronic device; when the additional sensing data is received from the external electronic device according to the schedule, applying the additional sensing data to the analysis algorithm to obtain an additional analysis result; when the irregular heart rate is identified from each of the first analysis result, the additional analysis result, and the second analysis result, displaying the notification.

[0271] For example, the external electronic device may be a wearable device worn by the user.

[0272] For example, the biometric information may include at least one of sleep information, activity information, stress information, blood sugar information, or body composition information.

[0273] For example, the method may further include an operation of obtaining context information based on user input.

[0274] For example, the operation of obtaining the first parameter group may include an operation of obtaining the first parameter group from among the plurality of parameter groups based on the biometric information and the context information.

[0275] For example, the context information may include at least one of age information, gender information, disease information, or medication information.

[0276] For example, the method may further include an operation of inputting the biometric information and the context information into a neural network model to obtain the first parameter group.

[0277] For example, the neural network model can be trained to output a group of parameters for setting the analysis algorithm according to the biometric information and the context information when the biometric information and the context information are input.

[0278] For example, the action of displaying the notification may include an action of displaying the notification including a UI that guides the user to detect whether the user's heart rate is irregular through the second sensor when an irregular heart rate is identified from each of the first analysis result and the second analysis result.

[0279]

[0280] Meanwhile, the various embodiments described above may be implemented in a storage medium readable by a computer or similar device using software, hardware, or a combination thereof. In some cases, the embodiments described herein may be implemented by the processor itself. In a software implementation, embodiments, such as the procedures and functions described herein, may be implemented as separate software modules. Each of the software modules may perform one or more functions and operations described herein.

[0281] Meanwhile, computer instructions for performing processing operations of an electronic device according to various embodiments of the present disclosure described above may be stored in a non-transitory computer-readable medium. When executed by a processor of a specific device, the computer instructions stored in the non-transitory computer-readable medium cause the specific device to perform processing operations in the electronic device according to various embodiments described above.

[0282] A non-transitory computer-readable medium refers to a medium that permanently stores data and can be read by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specific examples of non-transitory computer-readable media include CDs, DVDs, hard disks, Blu-ray discs, USBs, memory cards, and ROMs.

[0283] Although the preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above, and various modifications may be made by a person having ordinary skill in the art to which the present disclosure pertains without departing from the gist of the present disclosure as claimed in the claims, and such modifications should not be understood individually from the technical idea or prospect of the present disclosure.

Claims

1. In electronic devices, First sensor (171); Second sensor (172); display (140); At least one processor (110) comprising a processing circuit; and A memory (120) storing instructions and including one or more storage media; The above instructions, when individually or collectively executed by the at least one processor (110), cause the electronic device to: Obtaining the user's biometric information using at least one of the first sensor (171) or the second sensor (172), Based on the above biometric information, a first parameter group is obtained from among a plurality of parameter groups, Based on the first parameter group above, an analysis algorithm for heart rate is set, Control the first sensor (171) to obtain first sensing data, Applying the above first sensing data to the above analysis algorithm to obtain the first analysis result (1), An electronic device configured to identify whether a heart rate corresponding to the first sensing data is irregular based on the first analysis result (1).

2. In paragraph 1, The above instructions cause the electronic device to: After receiving the first sensing data and a preset time has elapsed, the second sensing data is received from the first sensor (171), Applying the above second sensing data to the above analysis algorithm to obtain the second analysis result (2), Based on the second analysis result (2), identify whether the heart rate corresponding to the second sensing data is irregular, An electronic device configured to display a notification (1000B) through the display when an irregular heart rate is identified from each of the first analysis result (1) and the second analysis result (2).

3. In paragraph 2, The above instructions cause the electronic device to: When the irregular heartbeat is identified based on the first analysis result (1), the second sensing data is applied to the analysis algorithm to obtain the second analysis result (2). An electronic device configured to, if the irregular heartbeat is not identified based on the first analysis result (1), acquire a second parameter group among the plurality of parameter groups, reset the analysis algorithm based on the second parameter group, and apply the second sensing data to the reset analysis algorithm to acquire the second analysis result (2).

4. In either of paragraphs 2 and 3, The above instructions cause the electronic device to: After receiving the second sensing data and the preset time has elapsed, receiving the third sensing data from the first sensor (171), Applying the above third sensing data to the above analysis algorithm to obtain a third analysis result, Based on the third analysis result, identify whether the heart rate corresponding to the third sensing data is irregular, An electronic device configured to, if an irregular heartbeat is not identified from the third analysis result, acquire a second parameter group from among the plurality of parameter groups and reset the analysis algorithm based on the second parameter group.

5. In paragraph 4, The first parameter group above is: When sensing data is applied to the above analysis algorithm, it is a group of parameters that increases the sensitivity of the analysis algorithm by increasing the probability that the analysis algorithm identifies the irregular heartbeat. The second parameter group is: An electronic device, wherein when sensing data is applied to the above analysis algorithm, a group of parameters that reduce the sensitivity of the analysis algorithm by reducing the probability that the analysis algorithm identifies the irregular heartbeat.

6. In any one of paragraphs 2 to 5, further comprising a communication interface; The above instructions cause the electronic device to: If the irregular heartbeat is identified based on the first analysis result (1), a schedule is set to receive additional sensing data acquired by the external electronic device (400) from the external electronic device during the preset time. When the additional sensing data is received from the external electronic device (400) according to the above schedule, the additional sensing data is applied to the analysis algorithm to obtain an additional analysis result (A), Based on the above additional analysis result (A), identify whether the heart rate corresponding to the above additional sensing data is irregular, When an irregular heart rate is identified from each of the first analysis result (1), the additional analysis result, and the second analysis result (2), the notification (1000B) is configured to be displayed. The above external electronic device (400) is, An electronic device, which is a wearable device worn by the user.

7. In any one of paragraphs 1 to 6, The above biometric information is, An electronic device comprising at least one of sleep information, activity information, stress information, blood sugar information, or body composition information.

8. In any one of paragraphs 1 to 7, The above instructions cause the electronic device to: Obtain context information based on user input, It is configured to obtain the first parameter group from among the plurality of parameter groups based on the biometric information and the context information, The above context information is, An electronic device comprising at least one of age information, gender information, disease information, or medication information.

9. In paragraph 8, The above instructions cause the electronic device to: It is configured to input the above biometric information and the above context information into a neural network model to obtain the first parameter group, The above neural network model is, An electronic device that is trained to output a group of parameters for setting the analysis algorithm according to the biometric information and the context information when the biometric information and the context information are input.

10. In any one of paragraphs 2 to 9, The above instructions cause the electronic device to: An electronic device configured to display the notification (1000B) including a UI that guides the user to detect whether the user's heart rate is irregular through the second sensor (172) when an irregular heart rate is identified from each of the first analysis result (1) and the second analysis result (2).

11. In a method for controlling an electronic device, The above electronic device, first sensor; and a second sensor; The above method, An operation of obtaining a user's biometric information using at least one of the first sensor or the second sensor; An operation of obtaining a first parameter group from among a plurality of parameter groups based on the above biometric information; An operation of setting an analysis algorithm for heart rate based on the first parameter group; An operation of controlling the first sensor to obtain first sensing data; An operation of applying the first sensing data to the analysis algorithm to obtain a first analysis result; and A control method, comprising: an operation of identifying whether a heart rate corresponding to the first sensing data is irregular based on the first analysis result; 12. In paragraph 11, An operation of receiving the first sensing data and receiving second sensing data from the first sensor after a preset time has elapsed; An operation of applying the second sensing data to the analysis algorithm to obtain a second analysis result; An operation of identifying whether the heart rate corresponding to the second sensing data is irregular based on the second analysis result; and A control method, comprising: an operation of displaying a notification through the display when an irregular heart rate is identified from each of the first analysis result and the second analysis result; 13. In paragraph 12, The operation of obtaining the above second analysis result is as follows: When the irregular heartbeat is identified based on the first analysis result, an operation of applying the second sensing data to the analysis algorithm to obtain the second analysis result; and A control method comprising: an operation of acquiring a second parameter group from among the plurality of parameter groups, resetting the analysis algorithm based on the second parameter group, and applying the second sensing data to the re-set analysis algorithm to acquire the second analysis result if the irregular heartbeat is not identified based on the first analysis result.

14. In any one of paragraphs 12 and 13, An operation of receiving the second sensing data and receiving third sensing data from the first sensor after the preset time has elapsed; An operation of applying the third sensing data to the analysis algorithm to obtain a third analysis result; An operation of identifying whether the heart rate corresponding to the third sensing data is irregular based on the third analysis result; and A control method, comprising: an operation of acquiring a second parameter group among the plurality of parameter groups and resetting the analysis algorithm based on the second parameter group, if an irregular heart rate is not identified from the third analysis result; 15. In a storage medium storing computer-readable instructions, the instructions, when executed by at least one processor of an electronic device including a first sensor and a second sensor, cause the electronic device to: Obtaining the user's biometric information using at least one of the first sensor or the second sensor, Based on the above biometric information, a first parameter group is obtained from among a plurality of parameter groups, Based on the first parameter group above, an analysis algorithm for heart rate is set, Controlling the first sensor to obtain first sensing data, Applying the above first sensing data to the above analysis algorithm to obtain a first analysis result, A storage medium that causes identification of whether the heart rate corresponding to the first sensing data is irregular based on the first analysis result.

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