Electronic device for providing notification of degenerative disease, operation method thereof, and storage medium

Abstract

According to one embodiment, when executed by at least one processor of an electronic device, instructions are configured to instruct, in a non-transitory storage medium for storing computer-readable instructions, the electronic device to perform at least one operation, wherein the at least one operation can include the operations of: connecting to a wearable electronic device; identifying first sensing data acquired from the wearable electronic device and accumulated during a first period from among sensing data measured by a plurality of sensors of the wearable electronic device; identifying that, from among a plurality of conditions related to a degenerative disease, a first condition in which a change amount of the first sensing data exceeds the threshold value during the first period is satisfied; identifying, on the basis of the identification that the first condition is satisfied, second sensing data measured by the plurality of sensors of the wearable electronic device during a second period and acquired from the wearable electronic device; identifying, on the basis of the second sensing data, that a second condition from among the plurality of conditions is satisfied; and displaying, on the basis of the identification that the second condition is satisfied, a notification of the degenerative disease corresponding to the first condition and the second condition.

Description

Electronic device for providing notification of degenerative disease, method of operation thereof, and storage medium

[0001] One embodiment disclosed in this document relates to an electronic device for providing notification of a degenerative disease, a method of operation thereof, and a storage medium.

[0002] Various services and additional functions provided through user terminals, such as electronic devices like smartphones, are gradually increasing. To enhance the utility value of these electronic devices and satisfy the needs of diverse users, telecommunications service providers and electronic device manufacturers are competitively developing electronic devices that offer a wide range of functions. Consequently, the various functions provided through these electronic devices are also becoming increasingly sophisticated.

[0003] Among the various functions provided by electronic devices, there are those that utilize sensors. These sensors can collect information related to the electronic device, the external environment, or the user. Electronic devices can provide various services by utilizing the information collected through these diverse sensors.

[0004] The information described above may be provided as related art for the purpose of aiding understanding of the present disclosure. No claim or determination is made as to whether any of the foregoing may be applied as prior art related to the present disclosure.

[0005] According to one embodiment, the electronic device may include a communication circuit, a display, at least one processor, and a memory for storing instructions. According to one embodiment, the instructions may be configured to cause the electronic device to connect with a wearable electronic device through the communication circuit when executed individually or collectively by the at least one processor.

[0006] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be configured to check the first sensing data acquired from the wearable electronic device and accumulated during a first period among the sensing data measured by a plurality of sensors of the wearable electronic device.

[0007] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be configured to confirm that a first condition is satisfied among a plurality of conditions related to a degenerative disease, wherein the amount of change in the first sensing data during the first period exceeds a threshold value.

[0008] According to one embodiment, the instructions may be configured such that, when executed individually or collectively by the at least one processor, the electronic device checks second sensing data obtained from the wearable electronic device by measuring a plurality of sensors of the wearable electronic device during a second period based on confirming that the first condition is satisfied.

[0009] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be configured to confirm that a second condition among the plurality of conditions is satisfied based on the second sensing data.

[0010] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be configured to display a notification regarding the degenerative disease corresponding to the first condition and the second condition through the display, based on confirming that the second condition is satisfied.

[0011] According to one embodiment, a method for providing a notification of a degenerative disease in an electronic device may include the operation of connecting with a wearable electronic device.

[0012] According to one embodiment, the method may include the operation of confirming first sensing data acquired from the wearable electronic device and accumulated during a first period among sensing data measured by a plurality of sensors of the wearable electronic device.

[0013] According to one embodiment, the method may include an operation of confirming that among a plurality of conditions related to a degenerative disease, a first condition is satisfied in which the amount of change of the first sensing data during the first period exceeds a threshold value.

[0014] According to one embodiment, the method may include an operation of confirming second sensing data obtained from the wearable electronic device by measuring a plurality of sensors of the wearable electronic device during a second period based on confirming that the first condition is satisfied.

[0015] According to one embodiment, the method may include an operation of confirming that a second condition among the plurality of conditions is satisfied based on the second sensing data.

[0016] According to one embodiment, the method may include an action of displaying a notification regarding the degenerative disease corresponding to the first condition and the second condition, based on confirming that the second condition is satisfied.

[0017] According to one embodiment, in a non-transient storage medium storing computer-readable instructions, the instructions are configured to cause the electronic device (101) to perform at least one operation when executed by at least one processor (120, 320) of the electronic device, wherein the at least one operation may include an operation of connecting to a wearable electronic device.

[0018] According to one embodiment, the at least one operation may include an operation of confirming first sensing data acquired from the wearable electronic device and accumulated during a first period among sensing data measured by a plurality of sensors of the wearable electronic device.

[0019] According to one embodiment, the at least one operation may include confirming that a first condition is satisfied among a plurality of conditions related to a degenerative disease, wherein the amount of change in the first sensing data during the first period exceeds a threshold value.

[0020] According to one embodiment, the at least one operation may include confirming second sensing data obtained from the wearable electronic device by measuring a plurality of sensors of the wearable electronic device during a second period based on confirming that the first condition is satisfied.

[0021] According to one embodiment, the at least one operation may include an operation of confirming that a second condition among the plurality of conditions is satisfied based on the second sensing data.

[0022] According to one embodiment, the at least one operation may include an operation of displaying a notification regarding the degenerative disease corresponding to the first condition and the second condition, based on confirming that the second condition is satisfied.

[0023] FIG. 1 is a block diagram of an electronic device in a network environment according to one embodiment.

[0024] FIG. 2 is a configuration diagram of a system for providing notification of degenerative diseases according to one embodiment.

[0025] FIG. 3 is an internal block diagram of an electronic device and a wearable electronic device, respectively, according to one embodiment.

[0026] FIG. 4 is a flowchart of the operation of an electronic device for providing notification of a degenerative disease according to one embodiment.

[0027] FIG. 5 is a detailed operation flowchart for providing a notification for a degenerative disease according to one embodiment.

[0028] FIG. 6 is a diagram illustrating the relationship between the measurement period and symptoms related to degenerative diseases according to one embodiment.

[0029] FIG. 7 is a table for explaining symptoms associated with each degenerative disease according to one embodiment.

[0030] FIG. 8 is a diagram illustrating a mode that is always measurable and a mode that is measurable after satisfying specific conditions related to degenerative diseases in a wearable electronic device according to one embodiment.

[0031] FIG. 9 is a drawing for illustrating a mode that can be measured continuously in a wearable electronic device according to one embodiment.

[0032] FIG. 10 is a diagram illustrating a mode measurable after satisfying specific conditions related to a degenerative disease in a wearable electronic device according to one embodiment.

[0033] FIG. 11 is a drawing for explaining a method for detecting gait abnormalities according to one embodiment.

[0034] FIG. 12 is a drawing for explaining a method of detecting a fall according to one embodiment.

[0035] FIG. 13 is a drawing for explaining a method of detecting hand slippage during rest according to one embodiment.

[0036] FIG. 14 is a drawing for explaining a method of detecting movement during sleep according to one embodiment.

[0037] FIG. 15 is an example diagram showing a medical questionnaire related to a degenerative disease according to one embodiment.

[0038] FIG. 16a is an illustrative diagram for providing a notification regarding a degenerative disease according to one embodiment.

[0039] FIG. 16b is an example diagram showing result reporting for each of a plurality of sensing items related to a degenerative disease according to one embodiment.

[0040] FIG. 16c is an example diagram showing a detailed report on a first sensing item among a plurality of sensing items related to a degenerative disease according to one embodiment.

[0041] In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0042] FIG. 1 is a block diagram of an electronic device (101) in a network environment (100) according to one embodiment. Referring to FIG. 1, in the network environment (100), the electronic device (101) may communicate with an electronic device (102) through a first network (198) (e.g., a short-range wireless communication network) or may communicate with at least one of an electronic device (104) or a server (108) through a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) through the server (108). According to one embodiment, the electronic device (101) may include a processor (120), memory (130), input module (150), sound output module (155), display module (160), audio module (170), sensor module (176), interface (177), connection terminal (178), haptic module (179), camera module (180), power management module (188), battery (189), communication module (190), subscriber identification module (196), or antenna module (197). In some embodiments, at least one of these components (e.g., connection terminal (178)) may be omitted from the electronic device (101), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (176), camera module (180), or antenna module (197)) may be integrated into a single component (e.g., display module (160)).

[0043] The processor (120) can control at least one other component (e.g., hardware or software component) of the electronic device (101) connected to the processor (120) by executing software (e.g., program (140)), for example, and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (120) can store commands or data received from other components (e.g., sensor module (176) or communication module (190)) in volatile memory (132), process the commands or data stored in volatile memory (132), and store the resulting data in non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., central processing unit or application processor) or an auxiliary processor (123) that can operate independently or together with it (e.g., graphics processing unit, neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor). For example, if the electronic device (101) includes a main processor (121) and an auxiliary processor (123), the auxiliary processor (123) may be configured to use lower power than the main processor (121) or to be specialized for a designated function. The auxiliary processor (123) may be implemented separately from the main processor (121) or as part thereof.

[0044] The auxiliary processor (123) may control at least some of the functions or states associated with at least one component of the electronic device (101) (e.g., display module (160), sensor module (176), or communication module (190)) on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (123) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (180) or communication module (190)). According to one embodiment, the auxiliary processor (123) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or through a separate server (e.g., server (108)). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers.An artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to the hardware structure, the artificial intelligence model may include a software structure, either additionally or substantially.

[0045] The memory (130) can store various data used by at least one component of the electronic device (101) (e.g., processor (120) or sensor module (176)). The data may include, for example, input data or output data for software (e.g., program (140)) and related commands. The memory (130) may include volatile memory (132) or non-volatile memory (134).

[0046] The program (140) may be stored as software in memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0047] The input module (150) can receive commands or data to be used for a component of the electronic device (101) (e.g., processor (120)) from outside the electronic device (101) (e.g., user). The input module (150) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0048] The sound output module (155) can output a sound signal to the outside of the electronic device (101). The sound output module (155) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0049] The display module (160) can visually provide information to an external (e.g., user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0050] The audio module (170) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150) or output sound through the sound output module (155) or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (101).

[0051] The sensor module (176) can detect the operating state of the electronic device (101) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (176) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0052] The interface (177) may support one or more specified protocols that can be used for the electronic device (101) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (102)). According to one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0053] The connection terminal (178) may include a connector through which the electronic device (101) can be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0054] The haptic module (179) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that the user can perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module (179) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0055] The camera module (180) can capture still images and video. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0056] The power management module (188) can manage the power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0057] The battery (189) can supply power to at least one component of the electronic device (101). According to one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0058] The communication module (190) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may include one or more communication processors that operate independently of the processor (120) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (194) (e.g., LAN (local area network) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device (104) through a first network (198) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (199) (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can identify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (196).

[0059] The wireless communication module (192) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. NR access technology can support high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and connection of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low-latency communications (URLLC)). The wireless communication module (192) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (192) can support various technologies for securing performance in the high-frequency band, such as beamforming, massive MIMO (multiple-input and multiple-output), full-dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large-scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), external electronic device (e.g., electronic device (104)), or network system (e.g., second network (199)). According to one embodiment, the wireless communication module (192) can support a Peak data rate (e.g., 20 Gbps or more) for realizing eMBB, loss coverage (e.g., 164 dB or less) for realizing mMTC, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) for realizing URLLC.

[0060] An antenna module (197) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (197) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as a first network (198) or a second network (199), may be selected from the plurality of antennas, for example, by a communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (197).

[0061] According to various embodiments, the antenna module (197) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0062] At least some of the above components can be connected to each other via a communication method between peripheral devices (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and exchange signals (e.g., commands or data) with each other.

[0063] According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) through a server (108) connected to a second network (199). Each of the external electronic devices (102, or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations performed on the electronic device (101) may be performed on one or more of the external electronic devices (102, 104, or 108). For example, if the electronic device (101) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (101) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (101) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device (104) or the server (108) may be included within a second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0064] In the following detailed description, reference numbers in the drawings may be assigned identically or omitted for configurations that can be easily understood through prior embodiments, and detailed descriptions thereof may also be omitted. An electronic device (101) according to one embodiment disclosed in this document may be implemented by selectively combining configurations of different embodiments, and a configuration of one embodiment may be replaced by a configuration of another embodiment. For example, it should be noted that the present invention is not limited to specific drawings or embodiments.

[0065] Degenerative diseases are characterized by a decline in cognitive, gait, and motor abilities. Currently, accurate diagnosis of these diseases requires trained professionals, specialized facilities and equipment, a clinical environment equipped with clinicians, and complex, time-consuming processes, which makes early diagnosis difficult. Since fundamental treatment is difficult even if an accurate diagnosis is made after symptoms appear, early diagnosis is crucial for degenerative diseases. A representative example is Parkinson's disease; if a user recognizes the symptoms associated with the disease and takes medication following an early diagnosis, the course of treatment can be different, such as by slowing the progression of the disease. However, early diagnosis can be challenging because users cannot recognize symptoms related to the degenerative disease until it has progressed significantly. For instance, in degenerative diseases like Parkinson's, gait abnormalities occur from the early stages, and these gait disorders worsen as the disease progresses, potentially becoming one of the symptoms that cause the most inconvenience in daily life.

[0066] Therefore, there is a need for a method for the early diagnosis of degenerative diseases that allows users to recognize symptoms related to the condition in advance, without requiring expensive equipment, skilled professionals (or specialists), or complex examination procedures. In particular, analyzing a user's gait can be effectively utilized for the early diagnosis of various degenerative diseases.

[0067] In one embodiment, an electronic device, a method of operation, and a storage medium may be provided for providing a notification regarding a degenerative disease related to a user's movement, such as walking, so that the user can recognize symptoms related to the degenerative disease in advance.

[0068] In one embodiment, using sensing data measured by a wearable electronic device that a user always wears, the electronic device analyzes the user's movement information (or activity information), such as walking, and provides information about a degenerative disease associated with at least one symptom based on the analysis results. For example, to diagnose a degenerative disease early, which the user may not know of until the disease has progressed significantly, the electronic device stores and manages the user's gradual behavioral changes (e.g., walking state) periodically measured by the wearable electronic device, and can induce the user to recognize their disease and receive effective treatment based on the user's behavioral changes accumulated over a certain period.

[0069] In one embodiment, a sensor with relatively low power consumption in a wearable electronic device operates in a mode that detects repetitive and regular user movements (e.g., walking, running), and can recognize symptoms related to a degenerative disease only when the amount of change in sensing data related to the user's movement over a certain period exceeds a threshold value (e.g., gait abnormality).

[0070] According to one embodiment, the electronic device can selectively activate additional sensors only when symptoms related to a degenerative disease are recognized, thereby confirming movements related to other symptoms as well as walking. Accordingly, the electronic device does not store and manage all sensor data (or sensing data) measured by the wearable electronic device, but selectively uses other sensor data when the amount of change in sensor data using a low-power sensor exceeds a threshold value, so it can be efficient not only in terms of data management but also in terms of battery consumption management.

[0071] According to one embodiment, a user can wear a wearable electronic device anytime and anywhere to objectively check changes in physical activity that gradually change over a certain period (e.g., several weeks or several months), making it possible for the user to self-diagnose their health and monitor the presence or absence of disease in real time.

[0072] According to one embodiment, changes in physical activity that take a long time to develop, such as gait disorders which are major symptoms of degenerative diseases, can be provided as objective indicators through periodic measurements, thereby providing the user with information for early diagnosis of degenerative diseases as well as opportunities for appropriate management and treatment.

[0073] FIG. 2 is a configuration diagram of a system for providing notification of degenerative diseases according to one embodiment.

[0074] Referring to FIG. 2, a system (200) for providing notification of a degenerative disease may include an electronic device (201) and at least one wearable electronic device (210) connected to the electronic device (201).

[0075] According to one embodiment, the electronic device (201) may be connected to at least one wearable electronic device (210) (e.g., a watch-type wearable electronic device that can be worn on a user's wrist (e.g., a smartwatch) (211), a ring-type wearable electronic device that can be worn on a user's finger (e.g., a smart ring) (212), or a wearable electronic device that can be worn on a user's ear (e.g., an earphone) (213)) based on a short-range wireless communication method (e.g., Bluetooth). The types of wearable electronic devices capable of providing information about the user's movements while worn on the user's body may not be limited to those shown in FIG. 2.

[0076] According to one embodiment, at least one wearable electronic device (210) may have a configuration similar or identical to at least a part of the electronic device (201).

[0077] According to one embodiment, the wearable electronic device (210) can be worn on the body of a user who is the subject of measurement and can transmit sensing data related to the user's movement, measured using a plurality of sensors, to an electronic device (201). According to one embodiment, the wearable electronic device (210) can periodically measure data related to the user's movement over a certain period and can transmit the measured sensing data to the electronic device (201) so that it can be stored and managed. According to one embodiment, the wearable electronic device (210) can transmit sensing data related to the user's movement to a separate server (e.g., server (108) of FIG. 1) for user-specific health management.

[0078] According to one embodiment, when a user wears two or more wearable electronic devices (210) (e.g., a smartwatch (211) and a smart ring (212)) simultaneously, the electronic device (201) can obtain information related to the movement of the wearable electronic device (210) (e.g., information related to the user's movement) from each of the two or more wearable electronic devices (210) (e.g., a smartwatch (211) and a smart ring (212)). Additionally, even when the user wears only one of a pair of earphones (213), the electronic device (201) can obtain information related to the movement of the one earphone worn (e.g., information related to the user's movement). Additionally, when the user wears a pair of earphones (213), information related to the movement of each earphone worn (e.g., information related to the user's movement) can be obtained, and information related to the imbalance of both movements in relation to the user can also be obtained using the information related to each movement.

[0079] According to one embodiment, the wearable electronic device (210) may be in a state of being connected to (or paired with) the electronic device (201) in communication while being worn on the user's body (e.g., wrist, finger, ear). The wearable electronic device (210) may check whether it is being worn before a health management application is executed on the electronic device (201), or check whether it is being worn in response to the execution of the health management application, and the timing of checking whether it is being worn is not limited thereto.

[0080] According to one embodiment, the wearable electronic device (210) may include at least one sensor for detecting the movement of the wearable electronic device (210). The at least one sensor may include at least one of a gyroscope sensor or an accelerometer sensor as an inertial sensor, for example, and may include a position sensor such as a GPS (global positioning system).

[0081] According to one embodiment, the wearable electronic device (210) can detect the movement of the wearable electronic device (210) (or the movement of a user wearing the wearable electronic device (211)) using at least one sensor (e.g., a gyroscope sensor, an accelerometer sensor) and transmit information related to the movement (or sensor information, sensor value) to the electronic device (201).

[0082] According to one embodiment, the wearable electronic device (210) can acquire sensing data corresponding to some of the multiple sensing items related to degenerative diseases. For example, the wearable electronic device (210) can operate in a mode that detects repetitive and regular user movements (e.g., walking, running) using a sensor with relatively low power consumption, and can transmit the results of sensing the user's walking data in walking mode or running mode to the electronic device (201). For example, the wearable electronic device (210) can periodically transmit the results of sensing the user's walking data to the electronic device (201). Additionally, for example, the wearable electronic device (210) can transmit the results of sensing the user's walking data accumulated during a first period to the electronic device (201). Additionally, for example, the wearable electronic device (210) can transmit the sensed result to the electronic device (201) when the amount of change in the walking data exceeds a threshold (e.g., walking abnormality) as a result of sensing the user's walking data accumulated during the first period.

[0083] According to one embodiment, the wearable electronic device (210) can acquire various types of sensing data necessary to determine whether there is a degenerative disease. For example, the wearable electronic device (210) can extract features from various types of signals, such as speed or reduced muscle coordination during exercise, hand tremors in specific situations, and movements during sleep, and transmit the extracted features (or sensed results) to the electronic device (201) or an external server (108). The electronic device (201) can store and manage the sensed results provided by the wearable electronic device (210) as learning data, so that gradual changes in the user's physical activity can be observed over a long period (e.g., 3 months or more).

[0084] According to one embodiment, the electronic device (201) can check the amount of change in sensing data (e.g., amount of change in physical activity) that gradually changes over a certain period (e.g., several weeks or several months) using sensing data obtained from the wearable electronic device (210). The electronic device (201) can check whether there is a response to symptoms related to a degenerative disease based on the amount of change in sensing data.

[0085] According to one embodiment, the electronic device (201) can confirm that it corresponds to symptoms related to a degenerative disease by using a learning model based on the amount of change in sensing data related to some of the multiple sensing items related to the degenerative disease, and in response to confirming that it corresponds to symptoms related to a degenerative disease, it can further drive other sensors in the wearable electronic device (210) to obtain data related to movement corresponding to the remaining items as well as walking corresponding to some of the items.

[0086] According to one embodiment, the electronic device (201) can generate information related to degenerative diseases based on the results of analyzing sensing data related to walking as well as user movement, and can provide (or output, display) the information related to degenerative diseases.

[0087] FIG. 3 is an internal block diagram of an electronic device and a wearable electronic device, respectively, according to one embodiment.

[0088] Referring to FIG. 3, the electronic device (201) may include at least one processor (320) including a processing circuit, memory (330), a display (360), and / or a communication circuit (390). Here, not all components shown in FIG. 3 are essential components of the electronic device (101), and the electronic device (201) may be implemented with more or fewer components than those shown in FIG. 3. In describing the electronic device (201) of FIG. 3, detailed descriptions of configurations similar to the embodiment of FIG. 1 or easily understood through the embodiment of FIG. 1 may be omitted.

[0089] According to one embodiment, the wearable electronic device (210) may include at least one processor (321), memory (331), sensor (377), and / or communication circuit (391).

[0090] According to one embodiment, the sensor (377) may include a plurality of sensors, and as an inertial sensor, it may include at least one of a gyroscope sensor or an accelerometer sensor. For example, at least one sensor may output sensor information (or sensor value, sensing information, sensing data) including movement, rotation, rotation angle, tilt, tilt direction, and / or posture of the wearable electronic device (210). Information indicating the movement of the wearable electronic device (210) may be information (or sensor data, sensing data) that is continuously or periodically sensed, which is measured or detected according to the movement of a user wearing the wearable electronic device (211).

[0091] According to one embodiment, the sensor (377) may further include a position sensor that operates together with a gyroscope sensor and an accelerometer sensor. For example, the position sensor may be a GPS that detects the position of the wearable electronic device (210).

[0092] According to one embodiment, the processor (321) can monitor the user's physical activity state (or user's movement) based on sensing data received from the sensor (377). For example, the processor (321) can always wake up and receive sensing data from the sensor (377) while power is supplied to the wearable electronic device (210).

[0093] The processor (321) can determine whether the user's movement is a repetitive, regular movement or exercise based on the sensing data. For example, if the difference between the sensing data is greater than or equal to a threshold value, it can determine whether the period of the sensing data is regular or repetitive. If the period of the sensing data is regular or repetitive, the user's movement, such as walking or running, can be identified. Accordingly, movements that occur during daily life (e.g., moving arms while sitting) that are not exercises such as walking or running can be excluded.

[0094] According to one embodiment, the processor (321) may not drive all sensors included in the sensor (377) simultaneously (or at once), but may drive only at least one sensor. For example, the processor (321) may operate in a continuous measurement mode to detect repetitive and regular user movements (e.g., walking, running) using a sensor with relatively low power consumption. The processor (321) may determine which sensor to drive among the multiple sensors included in the sensor (377) using sensing data measured (or accumulated) over a certain period (e.g., weeks or months). For example, if the amount of change in sensing data related to user movement over a certain period exceeds a threshold (or is above the threshold) (e.g., walking abnormality), the processor may drive a sensor different from the currently driven sensor or all sensors among the multiple sensors included in the sensor (377) to monitor an abnormal state different from the walking abnormality. For example, the amount of change and threshold of the sensing data over a certain period may be related to the user's movement intensity and may be preset by the processor (321), or the threshold may be adjusted to the user's activity intensity and may be set differently based on the user's age, gender, and / or weight.

[0095] According to one embodiment, sensing data over a certain period of time (or duration) (e.g., several weeks or several months) may be required to determine whether the user's gait is abnormal. For example, gait disorders commonly occur in patients with degenerative diseases and can worsen over time. Therefore, analyzing the user's movements, such as gait, can be effective for early diagnosis of the user's degenerative disease.

[0096] According to one embodiment, the subject of the operation to determine whether the amount of change in sensing data related to the user's movement over a certain period exceeds a threshold may be a wearable electronic device (210), but may also be an electronic device (201).

[0097] According to one embodiment, the processor (320) may receive (or acquire) first sensing data from the wearable electronic device (210), which is part of the sensing data periodically measured by sensors included in the sensor (377). For example, the processor (320) may receive first sensing data from the wearable electronic device (210) that has been measured (or accumulated) over a certain period in a constant measurement mode by some of the sensors of the sensor (377). The processor (320) may determine whether a first condition among a plurality of conditions related to a degenerative disease for early diagnosis of a degenerative disease is satisfied using the first sensing data accumulated over a first period acquired (or received) from the wearable electronic device (210). For example, the processor (320) may determine that the first condition is satisfied by determining whether the amount of change in the first sensing data accumulated over the first period exceeds a threshold value.

[0098] According to one embodiment, the processor (320) can identify, for example, the user's walking state (e.g., gait speed, walking posture), hand tremors, arm / leg movements, falls, or abnormal movements during sleep based on sensing data related to the user's movements measured by the sensor (377) of the wearable electronic device (210).

[0099] According to one embodiment, the processor (320) can identify a first condition corresponding to a first symptom among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced arm swing amplitude while walking, increased falls, or movement during sleep. For example, since analyzing the user's gait can be effective for early diagnosis of the user's degenerative disease, the processor (320) can primarily measure the user's walking condition (e.g., gait speed, walking posture) for early diagnosis of the user's degenerative disease.

[0100] According to one embodiment, the processor (320) can determine the walking speed of a user wearing a wearable electronic device (210) by using first sensing data accumulated during a first period by a position sensor included in the sensor (377). The processor (320) can determine whether a first condition is satisfied in which the amount of change in the sensing data representing the walking state during the first period exceeds a threshold value (e.g., a value serving as a criterion for determining an abnormal walking state corresponding to the user's age). For example, the processor (320) can determine that a first condition corresponding to a first symptom of slowing walking speed is satisfied based on confirming that the user's walking speed has decreased during the first period. Using the first sensing data, the user's step count, distance traveled, and travel time can be determined, and the processor (320) can determine whether the user's walking speed has decreased during the first period by measuring the user's step count, distance traveled, and travel time.

[0101] According to one embodiment, the processor (320) can determine which sensor to operate among a plurality of sensors included in the sensor (377) to obtain sensing data necessary to monitor another abnormal state (e.g., a state different from a gait abnormality) based on confirming that a first condition is satisfied, and can transmit a driving command for the determined sensor to the wearable electronic device (210). The processor (320) can receive (or obtain) second sensing data measured during a second time period by all other sensors included in the sensor (377), such as the sensor currently in operation, from the wearable electronic device (210). Based on the second sensing data measured during the second period, the processor (320) can determine whether a second condition different from the first condition among a plurality of conditions related to a degenerative disease is satisfied. According to one embodiment, the processor (320) can identify a second condition corresponding to a second symptom different from the first symptom, among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced arm swing amplitude during walking, increased falls, or movement symptoms during sleep. For example, the processor (320) can identify whether the second condition corresponds to a second symptom of reduced arm swing amplitude during walking, which is different from the first symptom of slowed walking speed, based on second sensing data indicating arm / leg movements during walking.

[0102] According to one embodiment, the processor (320) may further utilize sensors measured by other sensors, such as an accelerometer and a gyroscope, in addition to the position sensor, based on satisfying a first condition among a plurality of conditions related to a degenerative disease. For example, the processor (320) may identify the hand tremors of a user wearing the wearable electronic device (210) by using second sensing data measured by at least one of the position sensor, accelerometer, and gyroscope among the sensors included in the sensor (377) during a second period. The processor (320) may identify the second symptom as hand tremors during rest based on confirming that the user's hand tremors increase during the second period.

[0103] According to one embodiment, the processor (320) can determine the movement of the user’s arm / leg wearing the wearable electronic device (210) by using second sensing data measured by the accelerometer and gyroscope sensors among the sensors included in the sensor (377) during a second period, based on satisfying a first condition among a plurality of conditions related to a degenerative disease. The processor (320) can determine that the second symptom is a symptom of reduced arm swing amplitude during walking, based on confirming that the movement of the user’s arm / leg is reduced during the second period.

[0104] According to one embodiment, the processor (320) can confirm a fall of a user wearing a wearable electronic device (210) by using second sensing data measured by a fall detection sensor among the sensors included in the sensor (377) during a second period, based on satisfying a first condition among a plurality of conditions related to a degenerative disease. The processor (320) can confirm that the second symptom is the symptom of increased falls based on confirming that the number of falls of the user increases during the second period.

[0105] According to one embodiment, the processor (320) can identify abnormal movements during sleep of a user wearing the wearable electronic device by using the second sensing data measured by at least one of the accelerometer, gyroscope, or electrocardiogram sensor among the sensors included in the sensor (377) during the second period, based on satisfying a first condition among a plurality of conditions related to a degenerative disease. The processor (320) can identify that the second symptom is the sleep movement symptom based on confirming that the number of abnormal movements during sleep of the user increases during the second period.

[0106] According to one embodiment, if both the first condition and the second condition are satisfied, the processor (320) can confirm that the degenerative disease corresponding to the first condition and the second condition, such as symptoms of slowed walking speed and reduced arm swing amplitude during walking, is associated with Parkinson's disease. Accordingly, the processor (320) can display a notification regarding the degenerative disease through the display (360). For example, the processor (320) can display information regarding the degenerative disease through the display (360) so that the user can check information related to the degenerative disease regarding the user. For example, the notification regarding the degenerative disease may include at least one of the name of the degenerative disease, the user's current condition, or a result report for each of the plurality of symptoms related to the degenerative disease.

[0107] In the foregoing description, the subject of the operation determining whether the amount of change in sensing data related to the user's movement over a certain period exceeds a threshold was described as an example of an electronic device (201), but it may also be a wearable electronic device (210) or a server managing a health management application (e.g., the server (108) of FIG. 1).

[0108] According to one embodiment, the processor (321) of the wearable electronic device (210) may use sensing data measured (or accumulated) over a certain period by some of the sensors of the sensor (377) to recognize a gait abnormality when the amount of change in the sensing data exceeds a threshold (e.g., a threshold set in relation to the user's age) and transmit a signal to the electronic device (201) indicating the gait abnormality. Additionally, the processor (321) may transmit a signal to the electronic device (101) indicating that the amount of change in the sensing data accumulated over a certain period exceeds the threshold when the amount of change in the sensing data exceeds the threshold. The electronic device (201) may recognize a gait abnormality in response to receiving the signal indicating that the amount of change in the sensing data exceeds the threshold. In response to receiving a signal indicating an abnormal gait state or recognizing that there is an abnormal gait state, the electronic device (201) can determine which sensor to operate among the plurality of sensors included in the sensor (377) to obtain sensing data necessary to monitor an abnormal state different from the abnormal gait state, and transmit a driving command for the determined sensor to the wearable electronic device (210).

[0109] According to one embodiment, the processor (320) may generate a questionnaire for diagnosing a degenerative disease based on an abnormal condition related to the user's movement and display the generated questionnaire through the display (360). For example, a questionnaire may be displayed to the user to generate a questionnaire result in relation to the user's non-motor symptoms that cannot be measured by the sensor (377) of the wearable electronic device (210). The processor (320) may receive (or obtain) a response (or questionnaire result) to the questionnaire from the user and reflect the questionnaire result in generating information about the degenerative disease. Based on the information about the degenerative disease reflecting the questionnaire result, the processor (320) may display a notification about the degenerative disease through the display (360).

[0110] According to one embodiment, the memory (330) (e.g., the memory (130) of FIG. 1) may store a control program for controlling the electronic device (201), a UI (user interface) related to an application provided by the manufacturer or downloaded from an external source, images for providing the UI, user information, documents, databases, or related data.

[0111] According to one embodiment, the memory (330) can store instructions that control the processor (320) to perform various operations during execution.

[0112] According to one embodiment, the memory (330) may store a disease prediction model for early diagnosis of a degenerative disease. For example, the disease prediction model may be a stored deep learning model that determines the type of degenerative disease and may be a model that has undergone prior training on training data. For example, the disease prediction model may use the average value of sensing data corresponding to the user's age to detect an abnormal state of the user and predict a degenerative disease corresponding to the detected abnormal state. For example, based on sensing data that senses the user's gait and characteristic data representing the user's age group, the user's gait abnormality may be detected, and if a gait abnormality is detected, additional items to be sensed in relation to the degenerative disease may be determined, and the additionally sensed data and the response to the questionnaire corresponding to the gait abnormality may be input into the disease prediction model to predict a degenerative disease for the user.

[0113] According to one embodiment, the communication circuit (390) can communicate with the wearable electronic device (210) through the communication circuit (391) of at least one wearable electronic device (210) based on a short-range wireless communication method such as Bluetooth or NFC (near field communication) under the control of the processor (320).

[0114] According to one embodiment, when a health management application is executed under the control of the processor (320), the display (360) may display a user interface (UI) associated with the application. For example, the display (360) may communicate with the wearable electronic device (210) to display a user interface that provides data (e.g., sensing data or health data) related to the user's movement measured by the wearable electronic device (210) on a per-measure basis.

[0115] According to one embodiment, the communication circuit (390) can communicate with at least one wearable electronic device (210) under the control of the processor (320). According to one embodiment, the communication circuit (390) can communicate using at least one communication method among communication methods including Zigbee, Z-Wave, Wi-Fi, Bluetooth, Ultra-Wide Band (UWB), Wireless USB, and Near Field Communication (NFC). For example, the communication circuit (390) can perform low-power wireless communication using Zigbee or Z-Wave communication for communication with the wearable electronic device (210). According to one embodiment, the communication circuit (390) can support short-range communication such as Bluetooth and NFC (near field communication) in addition to Zigbee or Z-Wave communication.

[0116] According to one embodiment, the electronic device (101, 201) may include a communication circuit (390), a display (360), at least one processor (320), and a memory (330) for storing instructions. According to one embodiment, the instructions may be configured to cause the electronic device to connect with a wearable electronic device (210) through the communication circuit when executed individually or collectively by the at least one processor.

[0117] According to one embodiment, the instructions may be configured such that, when executed individually or collectively by the at least one processor, the electronic device checks the first sensing data acquired from the wearable electronic device and accumulated during a first period among the sensing data measured by the plurality of sensors (377) of the wearable electronic device.

[0118] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be configured to confirm that a first condition is satisfied among a plurality of conditions related to a degenerative disease, wherein the amount of change in the first sensing data during the first period exceeds a threshold value.

[0119] According to one embodiment, the instructions may be configured such that, when executed individually or collectively by the at least one processor, the electronic device checks second sensing data obtained from the wearable electronic device by measuring a plurality of sensors of the wearable electronic device during a second period based on confirming that the first condition is satisfied.

[0120] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be configured to confirm that a second condition among the plurality of conditions is satisfied based on the second sensing data.

[0121] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be configured to display a notification regarding the degenerative disease corresponding to the first condition and the second condition through the display, based on confirming that the second condition is satisfied.

[0122] According to one embodiment, the first condition corresponds to a first symptom among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced arm swing range while walking, increased falls, or movement during sleep, and the second condition may correspond to a second symptom different from the first symptom among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced arm swing range while walking, increased falls, or movement during sleep.

[0123] According to one embodiment, the instructions may be configured such that, when executed individually or collectively by the at least one processor, the electronic device checks the walking speed of a user wearing the wearable electronic device using the first sensing data accumulated during the first period by a position sensor among the plurality of sensors of the wearable electronic device, and checks that the first symptom is the walking speed slowing symptom based on the confirmation that the user's walking speed has decreased during the first period.

[0124] According to one embodiment, the instructions may be configured such that, when executed individually or collectively by the at least one processor, the electronic device determines whether the user's walking speed decreases during the first period by measuring the user's step count, distance traveled, and travel time using the first sensing data accumulated during the first period by the position sensor among the plurality of sensors of the wearable electronic device.

[0125] According to one embodiment, the instructions may be configured such that, when executed individually or collectively by the at least one processor, the electronic device checks for hand tremors of a user wearing the wearable electronic device using the second sensing data measured by at least one of a position sensor, an accelerometer, and a gyroscope sensor among a plurality of sensors of the wearable electronic device during the second period, based on confirming that the first condition is satisfied, and checks that the second symptom is a hand tremor symptom during rest, based on confirming that the hand tremors of the user increase during the second period.

[0126] According to one embodiment, the instructions may be configured such that, when executed individually or collectively by the at least one processor, the electronic device checks the movement of the user’s arm / leg using the second sensing data measured by the accelerometer and gyroscope sensors among the plurality of sensors of the wearable electronic device during the second period, based on confirming that the first condition is satisfied, and checks that the second symptom is a symptom of reduced arm swing amplitude during walking, based on confirming that the movement of the user’s arm / leg is reduced during the second period.

[0127] According to one embodiment, the instructions may be configured such that, when executed individually or collectively by the at least one processor, the electronic device detects a fall of a user wearing the wearable electronic device using the second sensing data measured by a fall detection sensor among a plurality of sensors of the wearable electronic device during the second period, based on confirming that the first condition is satisfied, and detects that the second symptom is the symptom of increased falls based on confirming that the number of falls of the user increases during the second period.

[0128] According to one embodiment, the instructions may be configured such that, when executed individually or collectively by the at least one processor, the electronic device identifies abnormal movement during sleep of a user wearing the wearable electronic device using the second sensing data measured by at least one of the accelerometer, gyroscope, or electrocardiogram sensor among the plurality of sensors of the wearable electronic device during the second period, based on confirming that the first condition is satisfied, and identifies that the second symptom is the sleep movement symptom based on confirming that the number of abnormal movements during sleep of the user increases during the second period.

[0129] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may be configured to display a questionnaire for diagnosing a degenerative disease through the display, obtain a questionnaire result regarding non-motor symptoms related to the degenerative disease through the questionnaire, generate an alert regarding the degenerative disease corresponding to the first condition and the second condition based on the questionnaire result, and display the generated alert regarding the degenerative disease through the display.

[0130] According to one embodiment, the notification regarding the degenerative disease may include at least one of the name of the degenerative disease, the user's current condition, or a result report for each of a plurality of symptoms related to the degenerative disease.

[0131] FIG. 4 is a flowchart of the operation of an electronic device for providing notification of a degenerative disease according to one embodiment.

[0132] Referring to FIG. 4, the operation method may include operations 405 through 430. Each operation of the operation method of FIG. 4 may be performed by at least one processor of an electronic device (e.g., the processor (120) of FIG. 1 and the processor (320) of FIG. 3). In one embodiment, at least one of operations 405 through 430 may be omitted, the order of some operations may be changed, or other operations may be added.

[0133] According to one embodiment, in operation 405, the electronic device (201) can be connected to a wearable electronic device (210). For example, the electronic device (201) can be paired with a wearable electronic device (210) worn on a user's body based on a short-range communication method.

[0134] According to one embodiment, in operation 410, the electronic device (201) can check the first sensing data acquired from the wearable electronic device (210) and accumulated during a first period among the sensing data measured by a plurality of sensors (377) of the wearable electronic device (210). For example, the wearable electronic device (210) can operate in a mode that detects repetitive and regular user movements (e.g., walking, running) using a sensor with relatively low power consumption, and can transmit the sensing results, which are sensed and accumulated during the first period, to the electronic device (201) in the walking mode or running mode.

[0135] According to one embodiment, the electronic device (201) can acquire sensing data and analysis information based on the sensing data (e.g., exercise time, exercise distance, etc.) from the wearable electronic device (210) whenever the user’s movement (e.g., exercise such as walking or running) ends. The electronic device (201) can accumulate and analyze the information acquired from the wearable electronic device (210). Thus, the electronic device (201) can use the first sensing data acquired from the wearable electronic device (210) and accumulated during the first period to confirm the correlation with a degenerative disease.

[0136] According to one embodiment, when the connection between the electronic device (201) and the wearable electronic device (210) is temporarily disconnected, information acquired from the wearable electronic device (210) during the temporary disconnection is accumulated and stored, and when a communication connection is re-established with the electronic device (201), the information acquired can be transmitted to the electronic device (201). Accordingly, the electronic device (201) can acquire the first sensing data accumulated during the first period from the wearable electronic device (210) during the communication connection and use it to confirm the relationship with the degenerative disease. According to one embodiment, in operation 415, the electronic device (201) can confirm that among a plurality of conditions related to the degenerative disease, the first condition in which the amount of change of the first sensing data during the first period exceeds a threshold value is satisfied. According to one embodiment, the first condition may correspond to the first symptom among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced arm swing amplitude during walking, increased falls, or movement during sleep. For example, in the case of degenerative diseases such as Parkinson's disease, gait abnormalities occur from the early stages, so analyzing whether there are gait abnormalities may be effective for early diagnosis of degenerative diseases.

[0137] According to one embodiment, the electronic device (201) can determine the walking speed of a user wearing the wearable electronic device (210) by using the first sensing data accumulated during the first period by a position sensor among the plurality of sensors (377) of the wearable electronic device (210). The electronic device (201) can determine that the first symptom is the symptom of slowing down the walking speed based on confirming that the user's walking speed has decreased during the first period.

[0138] According to one embodiment, the electronic device (201) can determine whether the user's walking speed decreases during the first period by measuring the user's step count, distance traveled, and travel time using the first sensing data accumulated during the first period by the position sensor among the plurality of sensors of the wearable electronic device.

[0139] According to one embodiment, in operation 420, the electronic device (201) can confirm second sensing data obtained from the wearable electronic device, which is measured by a plurality of sensors of the wearable electronic device during a second period, based on confirming that the first condition is satisfied.

[0140] According to one embodiment, in operation 425, the electronic device (201) can confirm that the second condition among the plurality of conditions is satisfied based on the second sensing data. According to one embodiment, the second condition may correspond to a second symptom different from the first symptom, among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced arm swing amplitude while walking, increased falls, or movement during sleep.

[0141] According to one embodiment, the electronic device (201) can detect the shaking of a user's hand wearing the wearable electronic device by using the second sensing data measured by at least one of a position sensor, an accelerometer, and a gyroscope sensor among a plurality of sensors of the wearable electronic device during the second period, based on confirming that the first condition is satisfied. The electronic device (201) can confirm that the second symptom is the shaking of the user's hand during rest, based on confirming that the shaking of the user's hand increases during the second period.

[0142] According to one embodiment, the electronic device (201) can confirm the movement of the user's arm / leg by using the second sensing data measured by the accelerometer and gyroscope sensors among the plurality of sensors of the wearable electronic device during the second period, based on confirming that the first condition is satisfied. The electronic device (201) can confirm that the second symptom is a symptom of reduced arm swing amplitude during walking, based on confirming that the movement of the user's arm / leg is reduced during the second period.

[0143] According to one embodiment, the electronic device (201) can confirm the movement of the user's arm / leg by using the second sensing data measured by the accelerometer and gyroscope sensors among the plurality of sensors of the wearable electronic device during the second period, based on confirming that the first condition is satisfied. The electronic device (201) can confirm that the second symptom is a symptom of reduced arm swing amplitude during walking, based on confirming that the movement of the user's arm / leg is reduced during the second period.

[0144] According to one embodiment, the electronic device (201) can confirm a fall of a user wearing the wearable electronic device by using the second sensing data measured by a fall detection sensor among a plurality of sensors of the wearable electronic device during the second period, based on confirming that the first condition is satisfied. The electronic device (201) can confirm that the second symptom is the symptom of increased falls based on confirming that the number of falls of the user increases during the second period.

[0145] According to one embodiment, the electronic device (201) can identify abnormal movement during sleep of a user wearing the wearable electronic device by using the second sensing data measured by at least one of the accelerometer, gyroscope, or electrocardiogram sensor among the plurality of sensors of the wearable electronic device during the second period, based on confirming that the first condition is satisfied. The electronic device (201) can identify that the second symptom is a symptom of reduced arm swing amplitude during walking, based on confirming that the movement of the user's arm / leg is reduced during the second period.

[0146] According to one embodiment, in operation 430, the electronic device (201) may display a notification regarding the degenerative disease corresponding to the first condition and the second condition based on confirming that the second condition is satisfied.

[0147] According to one embodiment, the electronic device (201) displays a questionnaire for diagnosing a degenerative disease and can obtain a questionnaire result regarding non-motor symptoms related to the degenerative disease through the questionnaire. Based on the questionnaire result, the electronic device (201) can generate an alert regarding the degenerative disease corresponding to the first condition and the second condition, and can display the generated alert regarding the degenerative disease.

[0148] FIG. 5 is a detailed flowchart of operations for providing a notification regarding a degenerative disease according to one embodiment. Referring to FIG. 5, the operation method may include operations 505 through 530. Each operation of the operation method of FIG. 5 may be performed by at least one processor (e.g., processor (120) of FIG. 1 and processor (320) of FIG. 3) of an electronic device (e.g., electronic device (201) of FIG. 1 through 3). In one embodiment, at least one of operations 505 through 530 may be omitted, the order of some operations may be changed, or other operations may be added. Refer to FIG. 6 and FIG. 7 to aid in understanding the description of FIG. 5.

[0149] Referring to FIG. 5, in operation 505, the electronic device (201) can identify early symptoms of a degenerative disease based on first sensing data corresponding to at least one first sensing item accumulated over a certain period by the wearable electronic device (210). The first sensing item may be an item related to the user's walking state, and the first sensing data may be data that senses walking data indicating the user's walking state (e.g., walking speed, walking posture) periodically over a certain period.

[0150] According to one embodiment, the electronic device (201) can extract various types of features based on sensing data accumulated over a certain period, classify according to the extracted features, and associate the classified data with symptoms related to degenerative diseases. For example, if the amount of change in the sensing data (e.g., walking data) accumulated over a certain period is greater than a threshold (e.g., walking speed gradually decreases over a certain period), the electronic device (201) can associate it with symptoms of slowing walking speed among symptoms related to degenerative diseases.

[0151] According to one embodiment, user movements such as walking and running, which can be measured regularly and repeatedly every day, can be measured in a continuous measurement mode; however, in relation to degenerative diseases, the number of measurements may be set to a fixed number of times at a designated interval (e.g., N times per week) rather than continuous measurement. Accordingly, the volume of data accumulated over a long period can be managed efficiently.

[0152] According to one embodiment, various data capacity management methods may be utilized, in addition to methods for limiting the specified period and the number of measurements. For example, data capacity may be managed by storing only a portion of the sensing data measured while a user is walking, or by storing only the average value of the sensing data measured while walking and deleting the remaining data. Furthermore, in the case of irregularly occurring behavior, instead of storing all the measured sensing data, the remaining data may be deleted after measuring for a specified period (e.g., one week) and then sampling to correspond to a predetermined number of measurements at a specified period (e.g., N measurements per week).

[0153] In operation 510, the electronic device (201) may add at least one second sensing item to monitor other symptoms of degenerative disease and generate and display a questionnaire for non-motor items that cannot be measured by the wearable electronic device (210).

[0154] According to one embodiment, a questionnaire may be generated to input various characteristic information related to the user in addition to sensing data measurable by a wearable electronic device (210) for the early diagnosis of degenerative diseases. For example, the characteristic information may include at least one of the user's age, disease history information, gender, or physical abnormality symptom information.

[0155] In operation 515, the electronic device (201) may activate a sensor corresponding to at least one second sensing item. For example, the electronic device (201) may not activate all sensors of the wearable electronic device (210) to measure all suspected symptoms, but may use sensing data from some sensors to identify initial symptoms, and then, in response to identifying initial symptoms of a degenerative disease, activate all related sensors to identify other overall symptoms related to the identified degenerative disease. For example, after identifying symptoms of slowed walking speed among symptoms related to the degenerative disease, the electronic device (201) may additionally drive (or activate) sensors necessary to identify other symptoms related to the degenerative disease.

[0156] According to one embodiment, the electronic device (201) may inform the user of additional items to be sensed. For example, in response to the user confirming that a symptom of slowed walking speed is an initial symptom, the device may output (or provide, display) information to the user indicating that additional sensing is needed for other items to confirm not only the symptom of slowed walking speed but also other suspected symptoms.

[0157] In operation 520, the electronic device (201) can analyze second sensing data and medical history results corresponding to at least one second sensing item. According to one embodiment, the electronic device (201) can generate and manage long-term data accumulated over a certain period without deleting data corresponding to initial symptoms. Additionally, the electronic device (201) can generate and manage long-term data to detect not only initial symptoms but also mid-to-long-term symptoms.

[0158] In operation 525, the electronic device (201) can identify other symptoms of a degenerative disease based on the analysis results. For example, the electronic device (201) can identify whether it corresponds to other suspected symptoms related to a degenerative disease based on second sensing data corresponding to at least one second sensing item. Additionally, for example, the electronic device (201) can analyze the results of the medical history to determine whether the results indicate suspected disease progression. According to one embodiment, the electronic device (201) can periodically obtain the results of the medical history through a medical history questionnaire from the user before or after the initial symptoms are identified.

[0159] In operation 530, the electronic device (201) can generate information about the degenerative disease associated with initial symptoms and other symptoms and then provide a notification.

[0160] According to one embodiment, FIG. 5 describes the case where the subject of the operation is an electronic device (201), but at least some of the operation may be performed by a wearable electronic device (210) or a server (108).

[0161] FIG. 6 is a diagram illustrating the relationship between the measurement period and symptoms related to degenerative diseases according to one embodiment.

[0162] Referring to FIG. 6, the electronic device (201) can detect (610) that some detection items indicate early symptoms (or significant symptoms) related to a degenerative disease based on the sensing data measured (or accumulated) over a certain period of time in the wearable electronic device (210), if the change in the accumulated sensing data exceeds a threshold. For example, energy scores and sleep scores may be used, and weights may be applied to detect early symptoms. If the electronic device (201) detects early symptoms related to a degenerative disease in some detection items, it may expand the sensor operation (625) to all detection items related to the suspected disease to monitor symptoms suspected related to the degenerative disease. To increase the accuracy of the prediction of the degenerative disease, the electronic device (210) may induce a survey (820) from the user regarding non-motor symptoms. The electronic device (210) can determine whether the change in sensing data over time reaches a threshold (630) suspected of a specific degenerative disease (e.g., Parkinson's disease). When the threshold suspected of a specific degenerative disease (e.g., Parkinson's disease) is reached, the electronic device (201) can provide a notification (635) about the specific degenerative disease to the user and those around them. For example, the electronic device (201) can provide a notification about the specific degenerative disease to the user or send the notification to a registered guardian and attending physician.

[0163] FIG. 7 is a table for explaining symptoms associated with each degenerative disease according to one embodiment.

[0164] FIG. 7 illustrates the relationship between suspected symptoms for each type of degenerative disease (e.g., Parkinson's disease, ALS, prion disease). For example, in the case of a specific degenerative disease (e.g., Parkinson's disease) (700), multiple symptoms (710) may appear over time, classified into early symptoms and mid-to-long-term symptoms. Representative examples of movement-related symptoms corresponding to multiple symptoms (710) detectable using a wearable electronic device (210) include hand tremors while at rest, slowed walking speed, staggering while walking, reduced arm swing amplitude while walking, increased falls, and movement during REM sleep. A sensor (377) of the wearable electronic device (210) may be used as a method (720) to detect whether each symptom corresponds to one of the symptoms.

[0165] For example, the wearable electronic device (210) can determine whether it corresponds to symptoms of hand tremors during rest based on sensing data measured using a position sensor (e.g., GPS), a gyroscope sensor, and an accelerometer sensor, when movement below a threshold is not changed for a certain period of time while the position and posture are not changed.

[0166] For example, the wearable electronic device (210) can measure the time taken relative to the distance traveled using a location sensor (e.g., GPS) while the walking exercise is detected, and can check whether it is responding to symptoms of slowing down the walking speed based on the measured sensing data.

[0167] For example, the wearable electronic device (210) can determine whether there is a symptom of staggering while walking or a symptom of reduced arm swing range while walking based on the sensing data measured using the gyroscope sensor and accelerometer sensor in the walking exercise detection state.

[0168] According to one embodiment, the electronic device (201) can predict that the user's abnormal symptoms are related to a specific degenerative disease (e.g., Parkinson's disease) if, after confirming symptoms of slowing walking speed based on sensing data measured by the wearable electronic device (210), it further confirms other symptoms related to a specific degenerative disease (e.g., Parkinson's disease), such as a decrease in the amplitude of arm swing while walking.

[0169] On the other hand, non-exercise-related symptoms that cannot be detected using the wearable electronic device (210) may be identified as characteristic information of the user, and the user may be required to input the relevant item through a survey.

[0170] FIG. 8 is a diagram illustrating a mode of continuous measurement and a mode of measurement after satisfying specific conditions related to degenerative diseases in a wearable electronic device according to one embodiment. Referring to FIG. 8, the operation method may include operations 805 through 815. Each operation of the operation method of FIG. 8 may be performed by at least one processor (e.g., processor (120) of FIG. 1 and processor (320) of FIG. 3) of an electronic device (e.g., electronic device (201) of FIG. 1 through 3). Additionally, each operation of the operation method of FIG. 8 may be performed by at least one processor (e.g., processor (321) of FIG. 3) of a wearable electronic device (e.g., wearable electronic device (210) of FIG. 2). To aid in understanding the description of FIG. 8, the description will be explained with reference to FIG. 9 through 14.

[0171] Referring to FIG. 8, in operation 805, the wearable electronic device (210) can confirm the association with the initial symptoms in a constant measurement mode (e.g., walking & running detection mode, fall detection mode) that detects repetitive and regular movements or falls of the wearable electronic device (210).

[0172] FIG. 9 is a drawing for illustrating a mode that can be measured continuously in a wearable electronic device according to one embodiment.

[0173] Referring to FIG. 9, the wearable electronic device (210) provides a walking mode and a running mode as examples of exercise functions of a smartwatch. As in 900a, the wearable electronic device (210) can detect movements such as walking and running in an always-on measurement mode that detects repetitive and regular user movements (e.g., walking, running) using a sensor with relatively low power consumption.

[0174] Additionally, the wearable electronic device (210) is provided with a fall detection mode, which is an example of a safety feature of the smartwatch, that can detect when a user falls or trips and provide a warning or request help. As in 900b, the wearable electronic device (210) can continuously monitor the user's movements and use a fall detection sensor to detect sudden changes in speed or rotation (e.g., falling) that exceed a specific reference value (or threshold). The wearable electronic device (210) determines whether a fall has occurred by detecting sudden movements or impacts, and can also consider cases where the user has not moved for a certain period of time. In this way, the wearable electronic device (210) can monitor the user's health status through fall data analysis.

[0175] For example, the wearable electronic device (210) can identify the association with suspected symptoms of degenerative disease among the data sensed in the continuous measurement mode, rather than operating all sensors or analyzing all sensing data to detect degenerative disease initially.

[0176] In operation 810, the wearable electronic device (210) can determine whether the amount of change in sensing data corresponds to an initial symptom. For example, based on the amount of change in sensing data measured in walking mode or running mode, the wearable electronic device (210) can determine whether the walking speed indicates a decrease over a certain period, and if the walking speed indicates a decrease over a certain period, it can be considered to correspond to an initial symptom of slowing down walking speed.

[0177] In response to checking whether the amount of change in sensing data corresponds to the initial symptom, in the 815 operation, the wearable electronic device (210) may additionally operate the sensor to detect not only the initial symptom but also other symptoms, or expand the detection range of the sensor to confirm the association with other symptoms.

[0178] FIG. 10 is a diagram illustrating a mode measurable after satisfying specific conditions related to a degenerative disease in a wearable electronic device according to one embodiment.

[0179] Referring to FIG. 10, as shown in 1000a, the wearable electronic device (210) may additionally operate a sensor to detect not only initial symptoms but also other symptoms, or increase the detection range (or sensitivity) of the sensor in operation to measure the degree of arm swinging back and forth, or as shown in 1000b, measure hand tremors during rest.

[0180] According to one embodiment, reference will be made to FIG. 11 and FIG. 12 to explain a method for confirming an association with initial symptoms in a continuous measurement mode (e.g., walking & running detection mode, fall detection mode) that detects repetitive and regular movements or falls.

[0181] FIG. 11 is a drawing for explaining a method for detecting gait abnormalities according to one embodiment.

[0182] Referring to FIG. 11, the wearable electronic device (210) can measure distance and time traveled using a location sensor (e.g., GPS) to measure walking speed (910). For example, the wearable electronic device (210) can measure walking speed during each exercise (e.g., up to 3 times per week), as in the 920 operation, and can use data measured (or accumulated) during a first period (e.g., 12 weeks). The wearable electronic device (210) can confirm that the initial symptoms correspond to symptoms of slowing walking speed based on confirming that walking speed decreased during the first period (e.g., 12 weeks). As an example of a mode measurable after satisfying specific conditions corresponding to initial symptoms associated with a degenerative disease, the wearable electronic device (210) can measure (905) the movement (or degree of swinging) of the arms back and forth using a gyroscope sensor and an accelerometer sensor. For example, the wearable electronic device (210) can measure the movement of swinging the arms back and forth during each exercise, such as in the 915 motion (e.g., up to 3 times per week), and can use the data measured during a second period (e.g., 12 weeks). The wearable electronic device (210) can confirm that it corresponds to a symptom of reduced arm swing amplitude during walking other than the initial symptom, based on confirming that the movement of swinging the arms back and forth (e.g., arm swing amplitude) is reduced during the second period (e.g., 12 weeks).

[0183] FIG. 12 is a diagram illustrating a method for detecting falls according to one embodiment. A wearable electronic device (210) can measure the frequency of fall detection (930) using a fall detection sensor. For example, the wearable electronic device (210) can record (or store) the number of falls per month as in operation 935 and can check whether falls occur per month. Based on confirming that falls occur per month, the wearable electronic device (210) can confirm that it responds to symptoms of an increase in falls other than initial symptoms. In addition, the wearable electronic device (210) can confirm that it responds to symptoms of an increase in falls other than initial symptoms based not only on the method of confirming that falls occur per month but also on confirming that the number of falls increases during a second period (e.g., 12 weeks).

[0184] FIG. 13 is a drawing for explaining a method of detecting hand slippage during rest according to one embodiment.

[0185] Referring to FIG. 13, as illustrated in 1300a, the position sensor, accelerometer, and gyroscope of the wearable electronic device (210) can recognize that the user wearing the wearable electronic device (210) is in a resting state when the user is not exercising (e.g., walking or running) and there is little movement and a low heart rate. As in operation 1310, the wearable electronic device (210) can detect hand tremors during rest using a motion sensor (e.g., a sensor capable of detecting finger movements). As in operation 1320, the wearable electronic device (210) can use data measured during a second period (e.g., 10 weeks) during each rest period. The wearable electronic device (210) can check whether the number of detections of symptoms considered to be hand tremors increases each week. For example, based on confirming that hand movements exhibiting hand tremor symptoms increased during the second period (e.g., 10 weeks), it can be confirmed that there is a response to hand tremor symptoms during rest other than the initial symptoms.

[0186] FIG. 14 is a drawing for explaining a method of detecting movement during sleep according to one embodiment.

[0187] Referring to FIG. 14, as illustrated in 1400a, the user can be recognized as being in a sleeping state by the accelerometer and gyroscope of the wearable electronic device (210). As in operation 1410, the wearable electronic device (210) can detect movement and heart rate during sleep using motion sensors (e.g., accelerometer, gyroscope) and an electrocardiogram sensor, and can detect abnormal sleep conditions because the heart rate increases rapidly when movements such as tossing and turning or flailing occur during sleep. The wearable electronic device (210) can measure data every time the user sleeps, as in operation 1420, and can use the data measured during a second period (e.g., 12 weeks). Here, the wearable electronic device (210) may delete the data after determining only whether there is a number of abnormal behaviors when measuring data every time the user sleeps. The wearable electronic device (210) can check whether the number of symptoms detected that are recognized as REM sleep disorder increases each month. For example, the wearable electronic device (210) can check for abnormal movements during sleep of a user wearing the wearable electronic device (210), and can check to respond to sleep movement symptoms other than initial symptoms based on confirming that the number of abnormal movements during sleep of the user increases during a second period (e.g., 12 weeks).

[0188] According to one embodiment, the electronic device (201) can predict a specific degenerative disease corresponding to additionally identified symptoms after confirming initial symptoms based on data sensed through the wearable electronic device (210), and can output (or display) a notification to provide information about the predicted specific degenerative disease.

[0189] FIG. 15 is an example diagram showing a medical questionnaire related to a degenerative disease according to one embodiment.

[0190] Referring to FIG. 15, the electronic device (201) may provide a questionnaire for the diagnosis of degenerative diseases. The electronic device (201) may generate a questionnaire to input various characteristic information related to the user in addition to sensing data measurable by the wearable electronic device (210) for the early diagnosis of degenerative diseases. For example, the characteristic information may include at least one of the user's age, disease history information, gender, or physical abnormality symptom information.

[0191] As illustrated in 1500a of FIG. 15, in response to detecting abnormal signs related to a user's physical activity based on sensing data accumulated over a period of time by a wearable electronic device (210), the electronic device (201) may notify the user of the abnormal signs and request the user to input a response related to the symptoms. In response to the user selecting an object (1510) indicating to go to the survey, the electronic device (201) may display a user interface showing a questionnaire as in 1500b. According to one embodiment, the response through the questionnaire may be transmitted to the electronic device (201) as well as to a server (108) managing a health management application. As illustrated in FIG. 15, the electronic device (201) may generate a questionnaire to input various characteristic information related to the user in addition to the sensing data measurable by the wearable electronic device (210) in order to increase the accuracy of early diagnosis of degenerative diseases. For example, characteristic information may include at least one of the user's age, disease history information, gender, or physical abnormality symptom information.

[0192] FIG. 16a is an exemplary diagram for providing a notification regarding a degenerative disease according to one embodiment, FIG. 16b is an exemplary diagram showing a result report for each of a plurality of sensing items related to a degenerative disease according to one embodiment, and FIG. 16c is an exemplary diagram showing a detailed report for a first sensing item among a plurality of sensing items related to a degenerative disease according to one embodiment.

[0193] Referring to FIG. 16a, when the prediction for a specific degenerative disease is completed, the electronic device (201) may output (or display) a notification for the specific degenerative disease as shown in FIG. 16a. In response to the user selecting an object (1610) representing a detailed view, the electronic device (201) may display a user interface including results (1620, 1630, 1640) for sensing items related to abnormal symptoms as in FIG. 16b. For example, the notification for the degenerative disease may include at least one of the diagnosis of the degenerative disease, the user's current condition, or result reports (1620, 1630, 1640) for each of a plurality of symptoms related to the degenerative disease. If the user selects one of the sensing items (e.g., walking speed) (1650), the electronic device (201) can provide detailed information about the sensing item (e.g., walking speed) as illustrated in FIG. 16c.

[0194] According to one embodiment, a user can wear a wearable electronic device anytime and anywhere to objectively check changes in physical activity that gradually change over a certain period (e.g., several weeks or several months), making it possible for the user to self-diagnose their health and monitor the presence or absence of disease in real time.

[0195] According to one embodiment, changes in physical activity that take a long time to develop, such as gait disorders which are major symptoms of degenerative diseases, can be provided as objective indicators through periodic measurements, thereby providing the user with information for early diagnosis of degenerative diseases as well as opportunities for appropriate management and treatment.

[0196] The electronic device according to the various embodiments disclosed in this document may be of various forms. The electronic device may include, for example, a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a consumer electronics device. The electronic device according to the embodiments of this document is not limited to the devices described above.

[0197] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, phrases such as "A or B," "at least one of A and B," "at least one of A or B," "A, B or C," "at least one of A, B and C," and "at least one of A, B, or C" may each include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used simply to distinguish said components from other said components and do not limit said components in any other aspect (e.g., importance or order). Where any (e.g., 1st) component is referred to as “coupled” or “connected” to another (e.g., 2nd) component, with or without the terms “functionally” or “communicationly,” it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0198] The term “module” as used in the various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0199] Various embodiments of the present document may be implemented as software (e.g., program (140)) comprising one or more instructions stored in a storage medium (e.g., internal memory (136) or external memory (138)) readable by a machine (e.g., electronic device (101)). For example, a processor (e.g., processor (120)) of the machine (e.g., electronic device (101)) may call at least one of the one or more instructions stored in the storage medium and execute it. This enables the machine to be operated to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily.

[0200] According to one embodiment, the method according to the various embodiments disclosed herein may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or an application store (e.g., Play Store). TM It can be distributed online (e.g., downloaded or uploaded) through ) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0201] According to various embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0202] According to one embodiment, in a non-transient storage medium storing computer-readable instructions, the instructions are configured to cause the electronic device (101) to perform at least one operation when executed by at least one processor (120, 320) of the electronic device, wherein the at least one operation may include an operation of connecting to a wearable electronic device.

[0203] According to one embodiment, the at least one operation may include an operation of confirming first sensing data acquired from the wearable electronic device and accumulated during a first period among sensing data measured by a plurality of sensors of the wearable electronic device.

[0204] According to one embodiment, the at least one operation may include confirming that a first condition is satisfied among a plurality of conditions related to a degenerative disease, wherein the amount of change in the first sensing data during the first period exceeds a threshold value.

[0205] According to one embodiment, the at least one operation may include confirming second sensing data obtained from the wearable electronic device by measuring a plurality of sensors of the wearable electronic device during a second period based on confirming that the first condition is satisfied.

[0206] According to one embodiment, the at least one operation may include an operation of confirming that a second condition among the plurality of conditions is satisfied based on the second sensing data.

[0207] According to one embodiment, the at least one operation may include an operation of displaying a notification regarding the degenerative disease corresponding to the first condition and the second condition, based on confirming that the second condition is satisfied.

Claims

1. In an electronic device (101, 201), Communication circuit (390); display; At least one processor; and It includes memory for storing instructions, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Connecting to a wearable electronic device through the above communication circuit, and Among the sensing data measured by a plurality of sensors of the wearable electronic device, the first sensing data acquired from the wearable electronic device and accumulated during a first period is identified, and Confirming that among a plurality of conditions related to degenerative diseases, a first condition is satisfied in which the amount of change in the first sensing data during the first period exceeds a threshold value, and Based on confirming that the above first condition is satisfied, second sensing data obtained from the wearable electronic device by being measured by a plurality of sensors of the wearable electronic device during a second period is confirmed, and Based on the second sensing data above, confirm that the second condition among the plurality of conditions is satisfied, and An electronic device configured to display a notification regarding the degenerative disease corresponding to the first condition and the second condition through the display, based on confirming that the second condition is satisfied.

2. In Paragraph 1, The above first condition corresponds to the first symptom among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced arm swing amplitude while walking, increased falls, or movement during sleep, and The above second condition is an electronic device that corresponds to a second symptom different from the above first symptom among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced range of arm swing during walking, increased falls, or movement during sleep.

3. In claim 1 or 2, when the instructions are executed individually or collectively by the at least one processor, the electronic device, Using the first sensing data accumulated during the first period by a position sensor among the plurality of sensors of the wearable electronic device, the walking speed of a user wearing the wearable electronic device is determined, and An electronic device configured to confirm that the first symptom is the symptom of slowed walking speed, based on confirming that the walking speed of the user is reduced during the first period.

4. In any one of claims 1 to 3, when the instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device configured to determine whether the user's walking speed decreases during the first period by measuring the user's step count, distance traveled, and travel time using the first sensing data accumulated during the first period by a position sensor among a plurality of sensors of the wearable electronic device.

5. In any one of claims 1 to 4, when the instructions are executed individually or collectively by the at least one processor, the electronic device, Based on confirming that the above first condition is satisfied, the shaking of the hand of a user wearing the wearable electronic device is confirmed using the second sensing data measured by at least one of a position sensor, an accelerometer, and a gyroscope among a plurality of sensors of the wearable electronic device during the above second period, and An electronic device configured to confirm that the second symptom is a hand tremor symptom during rest, based on confirming that the user's hand tremor increases during the second period.

6. In any one of claims 1 to 5, when the instructions are executed individually or collectively by the at least one processor, the electronic device, Based on confirming that the above first condition is satisfied, the movement of the arm / leg of a user wearing the wearable electronic device is confirmed using the second sensing data measured by the accelerometer and gyroscope among the plurality of sensors of the wearable electronic device during the above second period, and An electronic device configured to confirm that the second symptom is a symptom of reduced arm swing amplitude during walking, based on confirming that the movement of the user's arms / legs is reduced during the second period.

7. In any one of claims 1 to 6, when the instructions are executed individually or collectively by the at least one processor, the electronic device, Based on confirming that the above first condition is satisfied, a fall of a user wearing the wearable electronic device is confirmed using the second sensing data measured by the fall detection sensor among the plurality of sensors of the wearable electronic device during the above second period, and An electronic device configured to confirm that the second symptom is the symptom of increased falls, based on confirming that the number of falls of the user increases during the second period.

8. In any one of claims 1 to 7, when the instructions are executed individually or collectively by the at least one processor, the electronic device, Based on confirming that the above first condition is satisfied, abnormal movement during sleep of a user wearing the wearable electronic device is confirmed using the second sensing data measured by at least one of the accelerometer, gyroscope, or electrocardiogram sensor among the plurality of sensors of the wearable electronic device during the second period, and An electronic device configured to confirm that the second symptom is the sleep movement symptom based on confirming that the number of abnormal movements of the user during sleep increases during the second period.

9. In any one of claims 1 through 8, the instructions, when executed individually or collectively by the at least one processor, cause the electronic device, Display a medical questionnaire for the diagnosis of degenerative diseases through the above display, and Through the above questionnaire, the results of the medical history regarding non-motor symptoms related to the above degenerative disease are obtained, and Based on the results of the above medical history questionnaire, a notification regarding the degenerative disease corresponding to the first condition and the second condition is generated, and An electronic device configured to display a notification regarding the generated degenerative disease through the display.

10. In any one of paragraphs 1 to 9, the notification regarding the degenerative disease is, An electronic device comprising at least one of a diagnosis of the degenerative disease, the current condition of the user, or a result report for each of a plurality of symptoms associated with the degenerative disease.

11. A method for providing a notification of a degenerative disease in an electronic device, The act of connecting with a wearable electronic device; An operation of confirming first sensing data acquired from the wearable electronic device and accumulated during a first period among sensing data measured by a plurality of sensors of the wearable electronic device; An operation to confirm that among a plurality of conditions related to a degenerative disease, a first condition is satisfied in which the amount of change in the first sensing data during the first period exceeds a threshold value; Based on confirming that the above first condition is satisfied, an operation of confirming second sensing data obtained from the wearable electronic device, which is measured by a plurality of sensors of the wearable electronic device during a second period; An operation to confirm that the second condition among the plurality of conditions is satisfied based on the second sensing data; and A method for providing a notification of a degenerative disease, comprising the action of displaying a notification of the degenerative disease corresponding to the first condition and the second condition based on confirming that the second condition is satisfied.

12. In Paragraph 11, The above first condition corresponds to the first symptom among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced arm swing amplitude while walking, increased falls, or movement during sleep, and A method for providing notification of a degenerative disease, wherein the above-mentioned second condition corresponds to a second symptom different from the above-mentioned first symptom among symptoms of slowed walking speed, hand tremors during rest, staggering while walking, reduced range of arm swing during walking, increased falls, or movement symptoms during sleep.

13. In Paragraph 11 or 12, Using the first sensing data accumulated during the first period by a position sensor among the plurality of sensors of the wearable electronic device, the walking speed of a user wearing the wearable electronic device is determined, and A method for providing a notification of a degenerative disease, further comprising an action of confirming that the first symptom is the symptom of slowing down walking speed based on confirming that the walking speed of the user has decreased during the first period.

14. In any one of paragraphs 11 to 13, the operation of verifying the walking speed of a user wearing the wearable electronic device is, A method for providing a notification of a degenerative disease, comprising the operation of determining whether the user's walking speed decreases during the first period by measuring the user's step count, distance traveled, and travel time using the first sensing data accumulated during the first period by a position sensor among a plurality of sensors of the wearable electronic device.

15. In a non-transient storage medium storing computer-readable instructions, said instructions are configured to cause said electronic device (101) to perform at least one operation when executed by at least one processor (120, 320) of said electronic device, said at least one operation being, said at least one operation The act of connecting with a wearable electronic device; An operation of confirming first sensing data acquired from the wearable electronic device and accumulated during a first period among sensing data measured by a plurality of sensors of the wearable electronic device; An operation to confirm that among a plurality of conditions related to a degenerative disease, a first condition is satisfied in which the amount of change in the first sensing data during the first period exceeds a threshold value; Based on confirming that the above first condition is satisfied, an operation of confirming second sensing data obtained from the wearable electronic device, which is measured by a plurality of sensors of the wearable electronic device during a second period; An operation to confirm that the second condition among the plurality of conditions is satisfied based on the second sensing data; and A storage medium comprising an operation of displaying a notification regarding the degenerative disease corresponding to the first condition and the second condition based on confirming that the second condition is satisfied.

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