Electronic device for measuring sleep apnea

Abstract

This wearable electronic device can: convert, into a respiration signal indicating respiration power, an acceleration signal indicating acceleration received from an acceleration sensor; classify a signal component with a power value lower than a first threshold power value in the respiration signal into a first section (for example: an apnea section); classify a signal component with a power value higher than the first threshold power value and lower than a second threshold power value in the respiration signal into a second section (for example: a respiration section); classify a signal component with a power value higher than the second threshold power value in the respiration signal into a third section (for example: a tossing and turning section); identify peaks among signal components classified into the second section; select an effective peak from among the identified peaks on the basis of a criterion of one peak per section; determine, on the basis of the number of peaks selected as the effective peak, an apnea index indicating an irregular degree of respiration; and provide sleep information including the apnea index through a display.

Description

Electronic device for measuring sleep apnea

[0001] Embodiments of the present disclosure relate to an electronic device for measuring sleep apnea.

[0002] Wearable electronic devices (e.g., smart watches, smart rings) can be equipped with various sensors (e.g., accelerometers, biometric sensors). The information collected using these sensors can be used as raw data to provide information related to the health or fitness of the user wearing the wearable electronic device.

[0003] The above information is provided as background information to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above is applicable as prior art related to the present disclosure.

[0004] When a user stops breathing during sleep, their blood oxygen saturation (SpO2) may become relatively low. This may be referred to as oxygen desaturation.

[0005] A wearable electronic device may include a photoplethysmography (PPG) sensor as a type of biosensor. The wearable electronic device may calculate oxygen saturation using data collected from the PPG sensor while the user sleeps. Alternatively, another electronic device (e.g., a smartphone or a cloud server) may periodically receive biometric data from the wearable electronic device while the user sleeps and calculate oxygen saturation using the received biometric data. The measured oxygen saturation may be used to measure sleep apnea. For example, the electronic device may count the number of times the oxygen saturation falls below a threshold saturation value and provide an apnea-hypopnea index (AHI) as an index indicating the degree of apnea during sleep using the counted number of times.

[0006] Embodiments of the present disclosure may provide an electronic device configured to measure sleep apnea using a motion sensor (e.g., an acceleration sensor) that consumes relatively less power than a PPS sensor during operation.

[0007] Embodiments of the present disclosure may provide an electronic device configured to provide a result value that combines a result value obtained using a PPG sensor and a result value obtained using a motion sensor. Accordingly, even if the period of time required to collect raw data (PPG data, motion data) to obtain the result value is short, a relatively accurate result value (e.g., AHI) can be provided to the user.

[0008] The technical problems to be achieved in the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by a person having ordinary skill in the technical field to which the present invention belongs from the description below.

[0009] According to one embodiment, a wearable electronic device may include a motion sensor configured to generate a motion signal representing a motion of the wearable electronic device; a biosensor configured to generate a biosignal representing biological information of a user; a display; a processor; and a memory storing instructions. The instructions, when executed by the processor, may cause the wearable electronic device to determine, based on at least one of a motion signal received from the motion sensor and a biosignal received from the biosensor, whether the wearable electronic device is in a wearing state on the user's body and whether the user is in a sleeping state. The instructions may cause the wearable electronic device to periodically perform a first operation of collecting a motion signal from the motion sensor during a first time interval while the wearable electronic device is in the wearing state and the user is in the sleeping state, and determining a power value representing a power of respiration during the first time interval using the collected motion signal, whenever the first time interval elapses. The instructions may cause the wearable electronic device to periodically perform a second operation of determining a power value representing the power of respiration in the second time interval using power values ​​obtained as a result of performing the first operation whenever a second time interval longer than the first time interval has elapsed. The instructions may cause the wearable electronic device to periodically perform a third operation of selecting a peak value from among the power values ​​obtained as a result of performing the second operation whenever the second time interval has elapsed. The instructions may cause the wearable electronic device to perform a fourth operation of selecting a valid peak value in a respiration interval immediately following an apnea interval from among the peak values ​​obtained as a result of performing the third operation.The instructions may cause the wearable electronic device to determine an apnea index indicating the degree of breathing irregularity based on the number of peak values ​​selected as the valid peak values. The instructions may cause the wearable electronic device to provide sleep information including the apnea index through the display.

[0010] According to one embodiment, an electronic device may include a communication circuit for wirelessly communicating with a wearable electronic device; a display; a processor; and a memory storing instructions. The instructions, when executed by the processor, may cause the electronic device to receive a motion signal representing a motion of the wearable electronic device from the wearable electronic device through the communication circuit. The instructions may cause the wearable electronic device to periodically perform a first operation for determining a power value representing a power of respiration in a first time interval using the motion signal received from the wearable electronic device during the first time interval, whenever the first time interval elapses. The instructions may cause the wearable electronic device to periodically perform a second operation for determining a power value representing a power of respiration in the second time interval using power values ​​obtained as a result of performing the first operation, whenever a second time interval designated to be longer than the first time interval elapses. The instructions may cause the wearable electronic device to periodically perform a third operation of selecting a peak value from among power values ​​obtained as a result of performing the second operation, whenever the second time interval elapses. The instructions may cause the wearable electronic device to perform a fourth operation of selecting a valid peak value in a breathing period immediately following an apnea period from among peak values ​​obtained as a result of performing the third operation. The instructions may cause the wearable electronic device to determine an apnea index indicating a degree of irregularity of breathing based on the number of peak values ​​selected as the valid peak values. The instructions may cause the wearable electronic device to provide sleep information including the apnea index through the display.

[0011] According to one embodiment, a wearable electronic device may include an acceleration sensor configured to generate an acceleration signal representing acceleration of the wearable electronic device; a display; a processor; and a memory storing instructions. The instructions, when executed by the processor, may cause the wearable electronic device to convert an acceleration signal representing acceleration received from the acceleration sensor into a respiration signal representing power of respiration. The instructions may cause the wearable electronic device to classify a signal component having a power value lower than a first threshold power value in the respiration signal as a first interval (e.g., an apnea interval). The instructions may cause the wearable electronic device to classify a signal component having a power value higher than the first threshold power value and lower than a second threshold power value in the respiration signal as a second interval (e.g., a respiration interval). The instructions may cause the wearable electronic device to classify a signal component having a power value higher than the second threshold power value in the respiration signal as a third section (e.g., a tossing and turning section). The instructions may cause the wearable electronic device to identify peaks among the signal components classified as the second section. The instructions may cause the wearable electronic device to select a valid peak among the identified peaks based on a criterion of one peak per section. The instructions may cause the wearable electronic device to determine an apnea index indicating a degree of irregularity of breathing based on the number of peaks selected as the valid peaks. The instructions may cause the wearable electronic device to provide sleep information including the apnea index through the display.

[0012] According to one embodiment, a method of operating a wearable electronic device may include an operation of determining whether the wearable electronic device is in a wearing state on a user's body and whether the user is in a sleeping state based on at least one of a motion signal received from a motion sensor of the wearable electronic device and a biosignal received from a biosensor of the wearable electronic device. The method may include an operation of periodically performing a first function of collecting a motion signal from the motion sensor during a first time interval while the wearable electronic device is in the wearing state and the user is in the sleeping state and determining a power value representing a respiration power in the first time interval using the collected motion signal, whenever the first time interval elapses. The method may include an operation of periodically performing a second function of determining a power value representing a respiration power in the second time interval using power values ​​obtained as a result of performing the first function, whenever a second time interval designated to be longer than the first time interval elapses. The method may include an operation of periodically performing a third function of selecting a peak value from among power values ​​obtained as a result of performing the second function whenever the second time interval elapses. The method may include an operation of performing a fourth function of selecting a valid peak value in a breathing period immediately following an apnea period from among peak values ​​obtained as a result of performing the third function. The method may include an operation of determining an apnea index indicating a degree of irregularity of breathing based on the number of peak values ​​selected as the valid peak values. The method may include an operation of providing sleep information including the apnea index through a display of the wearable electronic device.

[0013] According to embodiments of the present disclosure, an electronic device can reduce battery power consumption by being configured to measure sleep apnea using a motion sensor (e.g., an acceleration sensor). Furthermore, the electronic device can provide a result value that combines a result value obtained using a PPG sensor and a result value obtained using a motion sensor. Accordingly, even if the period of time required to collect raw data (PPG data, motion data) to obtain the result value is short, a relatively accurate result value (e.g., AHI) can be provided to the user. In addition, various benefits, directly or indirectly identified through this document, can be provided.

[0014] FIG. 1 is a block diagram of an electronic device within a network environment according to various embodiments.

[0015] FIGS. 2A and 2B are front and rear perspective views of a wearable electronic device having a wrist-worn structure, according to one embodiment.

[0016] FIG. 3 illustrates a wearable electronic device configured to measure sleep apnea, according to one embodiment.

[0017] Figures 4a, 4b, and 4c are graphs showing patterns of motion signals (e.g., acceleration signals) collected using a motion sensor in a wearable electronic device when a user is sleeping.

[0018] Figure 5a is a graph showing the pattern of an acceleration signal indicating acceleration in the z-axis direction when a user exhibits symptoms of apnea during sleep.

[0019] Figure 5b is a graph showing the pattern of a first breathing signal indicating breathing power in the x-axis direction, a second breathing signal indicating breathing power in the y-axis direction, and a third breathing signal indicating breathing power in the z-axis direction when a user shows symptoms of apnea during sleep.

[0020] Figure 5c is a graph showing the result obtained by integrating the respiratory signals of Figure 5b and normalizing them between 0 and 1.

[0021] Figure 6a is a graph showing the pattern of an acceleration signal indicating acceleration in the z-axis direction when a user without apnea symptoms is sleeping.

[0022] Figure 6b is a graph showing the pattern of a first breathing signal indicating breathing power in the x-axis direction, a second breathing signal indicating breathing power in the y-axis direction, and a third breathing signal indicating breathing power in the z-axis direction when a user without apnea symptoms is sleeping.

[0023] Figure 6c is a graph showing the result obtained by integrating the respiratory signals of Figure 6b and normalizing them between 0 and 1.

[0024] FIG. 7 illustrates a configuration of a system for measuring sleep apnea according to one embodiment.

[0025] FIG. 8 is a flowchart illustrating operations for selecting a valid peak value from among peak values ​​in an electronic device according to one embodiment.

[0026] FIG. 9 is a flowchart illustrating operations for selecting a valid peak value from among peak values ​​in an electronic device according to one embodiment.

[0027] FIG. 10 is a flowchart illustrating operations for providing sleep information in an electronic device according to one embodiment.

[0028] FIG. 11 is a flowchart illustrating operations for providing sleep information in an electronic device according to one embodiment.

[0029] FIGS. 12a, 12b, 12c, 12d, 12e, and 12f are diagrams illustrating examples of sleep information provided to a user in an electronic device according to various embodiments.

[0030] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings so that those skilled in the art can easily implement the present disclosure. However, the present disclosure may be implemented in various different forms and is not limited to the embodiments described herein. In connection with the description of the drawings, the same or similar reference numerals may be used for identical or similar components. Furthermore, in the drawings and related descriptions, descriptions of well-known functions and configurations may be omitted for clarity and conciseness.

[0031] FIG. 1 is a block diagram of an electronic device (101) within a network environment (100) according to various embodiments. Referring to FIG. 1, in the network environment (100), the electronic device (101) may communicate with an electronic device (102) via 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) via 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) via the server (108). According to one embodiment, the electronic device (101) may include a processor (120), a memory (130), an input module (150), an audio output module (155), a display module (160), an audio module (170), a sensor module (176), an interface (177), a connection terminal (178), a haptic module (179), a camera module (180), a power management module (188), a battery (189), a communication module (190), a subscriber identification module (196), or an antenna module (197). In some embodiments, the electronic device (101) may omit at least one of these components (e.g., the connection terminal (178)), or may have one or more other components added. In some embodiments, some of these components (e.g., the sensor module (176), the camera module (180), or the antenna module (197)) may be integrated into one component (e.g., the display module (160)).

[0032] The processor (120) may, for example, execute software (e.g., a program (140)) to control at least one other component (e.g., a hardware or software component) of the electronic device (101) connected to the processor (120) and perform various data processing or calculations. According to one embodiment, as at least a part of the data processing or calculations, the processor (120) may store commands or data received from other components (e.g., a sensor module (176) or a communication module (190)) in a volatile memory (132), process the commands or data stored in the volatile memory (132), and store result data in a non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., a central processing unit or an application processor) or a secondary processor (123) (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor)) that can operate independently or together therewith. For example, if the electronic device (101) includes a main processor (121) and a secondary processor (123), the secondary processor (123) may be configured to use less power than the main processor (121) or to be specialized for a specified function. The secondary processor (123) may be implemented separately from the main processor (121) or as a part thereof.

[0033] The auxiliary processor (123) may control at least a portion of functions or states associated with at least one component (e.g., a display module (160), a sensor module (176), or a communication module (190)) of the electronic device (101), for example, 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. In one embodiment, the auxiliary processor (123) (e.g., an image signal processor or a communication processor) may be implemented as a part of another functionally related component (e.g., a camera module (180) or a communication module (190)). In one embodiment, the auxiliary processor (123) (e.g., a neural network processing unit) may include a hardware structure specialized for processing artificial intelligence models. The artificial intelligence models may be generated through machine learning. This learning can be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or can be performed through a separate server (e.g., server (108)). The learning algorithm can 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 can include multiple artificial neural network layers.The artificial neural network may be one of 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, or alternatively to, a hardware structure, an artificial intelligence model may include a software structure.

[0034] The memory (130) can store various data used by at least one component (e.g., processor (120) or sensor module (176)) of the electronic device (101). The data can include, for example, software (e.g., program (140)) and input data or output data for commands related thereto. The memory (130) can include volatile memory (132) or non-volatile memory (134).

[0035] The program (140) may be stored as software in the memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0036] The input module (150) can receive commands or data to be used in a component of the electronic device (101) (e.g., a processor (120)) from an external source (e.g., a user) of the electronic device (101). The input module (150) can include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0037] The audio output module (155) can output audio signals to the outside of the electronic device (101). The audio output module (155) can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. In one embodiment, the receiver can be implemented separately from the speaker or as part of the speaker.

[0038] The display module (160) can visually provide information to an external party (e.g., a 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 the device. In 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 a force generated by the touch.

[0039] The audio module (170) can convert sound into an electrical signal, or vice versa, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150), output sound through the sound output module (155), or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphone) directly or wirelessly connected to the electronic device (101).

[0040] The sensor module (176) can detect the operating status (e.g., power or temperature) of the electronic device (101) or the external environmental status (e.g., user status) and generate an electrical signal or data value corresponding to the detected status. According to one embodiment, the sensor module (176) can include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0041] The interface (177) may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device (101) with an external electronic device (e.g., the electronic device (102)). In 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.

[0042] The connection terminal (178) may include a connector through which the electronic device (101) may 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).

[0043] A haptic module (179) can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that a user can perceive through tactile or kinesthetic sensations. In one embodiment, the haptic module (179) can include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

[0044] The camera module (180) can capture still images and videos. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0045] The power management module (188) can manage power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least a part of a power management integrated circuit (PMIC).

[0046] A battery (189) may power at least one component of the electronic device (101). In one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0047] The communication module (190) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between the 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 operate independently from the processor (120) (e.g., application processor) and may include one or more communication processors that 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., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module (194) (e.g., a local area network (LAN) communication module, or a power line communication module). Among these communication modules, the corresponding communication module can communicate with an external electronic device (104) via a first network (198) (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network (199) (e.g., a long-range communication network such as 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 can 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 verify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) by using subscriber information (e.g., an international mobile subscriber identity (IMSI)) stored in the subscriber identification module (196).

[0048] The wireless communication module (192) can support 5G networks and next-generation communication technologies following the 4G network, such as NR access technology (new radio access technology). The NR access technology can support high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module (192) can support, for example, a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate. The wireless communication module (192) can support various technologies for securing performance in a high-frequency band, such as beamforming, massive multiple-input and multiple-output (MIMO), 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), an external electronic device (e.g., the electronic device (104)), or a network system (e.g., the 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 eMBB realization, a loss coverage (e.g., 164 dB or less) for mMTC realization, or a U-plane latency (e.g., 0.5 ms or less for downlink (DL) and uplink (UL), or 1 ms or less for round trip) for URLLC realization.

[0049] The antenna module (197) can transmit or receive signals or power to or from an external device (e.g., an external electronic device). In one embodiment, the antenna module (197) may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). In 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 the first network (198) or the second network (199), may be selected from the plurality of antennas by, for example, the 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. In some embodiments, in addition to the radiator, another component (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module (197).

[0050] 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 a first side (e.g., a bottom side) of the printed circuit board and capable of supporting a designated high-frequency band (e.g., a mmWave band), and a plurality of antennas (e.g., an array antenna) disposed on or adjacent a second side (e.g., a top side or a side side) of the printed circuit board and capable of transmitting or receiving signals in the designated high-frequency band.

[0051] At least some of the above components can be interconnected and exchange signals (e.g., commands or data) with each other via a communication method between peripheral devices (e.g., a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)).

[0052] According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) via 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 executed in the electronic device (101) may be executed in one or more of the external electronic devices (102, 104, or 108). For example, when the electronic device (101) is to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device (101) may, instead of or in addition to executing the function or service itself, request one or more external electronic devices to perform the function or at least a part of the service. One or more external electronic devices that receive the request may execute at least a portion of the requested function or service, or an 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 process the result as is or additionally and provide it as at least a portion of a response to the request. For this purpose, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used, for example. The electronic device (101) may provide an ultra-low latency service by using distributed computing or mobile edge computing, for example. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server utilizing machine learning and / or a neural network. According to one embodiment, the external electronic device (104) or the server (108) may be included in the second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0053] In various embodiments of the present disclosure, a wearable electronic device is defined as a device having a structure that can be worn on the human body. For example, a smart watch worn on the wrist or a smart ring worn on the finger may be classified as a wearable electronic device.

[0054] FIGS. 2A and 2B are front and rear perspective views of a wearable electronic device (200) having a structure wearable on a wrist, according to one embodiment.

[0055] Referring to FIGS. 2A and 2B, a wearable electronic device (200) (e.g., electronic device (101) or electronic device (102) in FIG. 1) may include a housing (210) including a first side (or front side, a side viewed from above in a downward direction (e.g., -z direction)) (210A), a second side (or back side, a side viewed from below in a upward direction (e.g., z direction)) (210B), and a side surface (210C) surrounding a space between the first side (210A) and the second side (210B), and a fastening member (250, 260) (e.g., a strap, a connecting member, and / or a joining member) connected to at least a portion of the housing (210) and configured to removably fasten the wearable electronic device (200) to a user's wrist. In another embodiment (not shown), the housing (210) may refer to a structure forming part of the first side (210A), the second side (210B), and the side surface (210C) of FIG. 2A.

[0056] The first side (210A) may be formed by a front plate (201) that is at least partially substantially transparent (e.g., a glass plate or a polymer plate including various coating layers). The second side (210B) may be formed by a substantially opaque back plate (207). The back plate (207) may be formed by, for example, coated or colored glass, ceramic, polymer, metal (e.g., aluminum, stainless steel (STS), or magnesium), and / or a combination of at least two of the foregoing materials. The side surface (210C) may be formed by a side bezel structure (or “side member”) (206) that is joined to the front plate (201) and the back plate (207) and includes a metal and / or a polymer.

[0057] The wearable electronic device (200) may include at least one of a display (220) (e.g., the display module (160) of FIG. 1), an audio module (205, 208) (e.g., the audio module (170) of FIG. 1), a biosensor (211) (e.g., the sensor module (176) of FIG. 1), a key input device (202, 203, 204) (e.g., the input module (150) of FIG. 1), and a connector hole (209) (e.g., the connection terminal (178) of FIG. 1). The electronic device (200) may omit at least one of the components (e.g., the key input device (202, 203, 204), the connector hole (209), and / or the sensor module (211)) or may additionally include other components.

[0058] The display (220) may be visually exposed through a significant portion of the front plate (201). The shape of the display (220) may correspond to the shape of the front plate (201), and may have various shapes such as a circle, an oval, and / or a polygon. The display (220) may be combined with or disposed adjacent to a touch detection circuit, a pressure sensor capable of measuring the intensity (pressure) of a touch, and / or a fingerprint sensor.

[0059] The audio module (205, 208) may include a microphone hole (205) and a speaker hole (208). The microphone hole (205) may have a microphone positioned therein for acquiring external sounds, and in some embodiments, multiple microphones may be positioned therein to detect the direction of sounds. The speaker hole (208) may be used as an external speaker and a receiver for calls. In some embodiments, the speaker hole (208) and the microphone hole (205) may be implemented as a single hole, or a speaker may be included without the speaker hole (208) (e.g., a piezo speaker).

[0060] The biometric sensor (211) may be placed on the second surface (210B) of the housing (210). The wearable electronic device (200) may further include various sensors in addition to the biometric sensor (211). For example, the wearable electronic device (200) may further include at least one of a Hall sensor (e.g., Hall IC), a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a color sensor, an IR (infrared) sensor, a temperature sensor, a humidity sensor, and an illuminance sensor.

[0061] The key input device (202, 203, 204) may include an annular member (202) (e.g., a bezel housing, a rotatable wheel, a wheel key) disposed on a first side (210A) of the housing (210) and rotatable in at least one direction, and / or a side key button (203, 204) (e.g., a physical button) disposed on a side surface (210C) of the housing (210). The annular member (202) may have a shape corresponding to the shape of the front plate (201). The annular member (202) may rotate clockwise or counterclockwise about the center of the display (220) as an axis. The wearable electronic device (200) may not include some or all of the above-described key input devices (202, 203, 204), and the key input devices (202, 203, 204) that are not included may be implemented in another form, such as a soft key, on the display (220). The connector hole (209) may accommodate a connector (e.g., a USB connector) for transmitting and receiving power and / or data with an external electronic device (e.g., a smart phone or a TA (travel adapter)) and may include another connector hole (not shown) for receiving a connector for transmitting and receiving audio signals with the external electronic device. The electronic device (200) may further include, for example, a connector cover (not shown) that covers at least a portion of the connector hole (209) and blocks the inflow of external foreign substances into the connector hole.

[0062] The fastening member (250, 260) can be detachably fastened to at least a portion of the housing (210) using the locking member (251, 261). The fastening member (250, 260) can include one or more of a fixing member (252), a fixing member fastening hole (253), a band guide member (254), and a band fastening ring (255). The fastening member (252) can be configured to fasten the housing (210) and the fastening member (250, 260) to a part of the user's body (e.g., a wrist and / or an ankle). The fastening member fastening hole (253) can fasten the housing (210) and the fastening member (250, 260) to a part of the user's body in response to the fastening member (252). The band guide member (254) is configured to limit the range of movement of the fixing member (252) when the fixing member (252) is fastened to the fixing member fastening hole (253), thereby allowing the fastening member (250, 260) to be fastened in close contact with a part of the user's body. The band fastening ring (255) can limit the range of movement of the fastening member (250, 260) when the fixing member (252) and the fixing member fastening hole (253) are fastened.

[0063] FIG. 3 illustrates a wearable electronic device (300) configured to measure sleep apnea, according to one embodiment. FIGS. 4A, 4B, and 4C are graphs showing patterns of motion signals (e.g., acceleration signals) collected using a motion sensor in the wearable electronic device (300) when a user is sleeping. FIG. 5A is a graph showing a pattern of an acceleration signal indicating acceleration in the z-axis direction when a user exhibits apnea symptoms during sleep. FIG. 5B is a graph showing a pattern of a first respiration signal indicating breathing power in the x-axis direction, a second respiration signal indicating breathing power in the y-axis direction, and a third respiration signal indicating breathing power in the z-axis direction when a user exhibits apnea symptoms during sleep. FIG. 5C is a graph showing a result obtained by integrating the respiration signals of FIG. 5B and normalizing them between 0 and 1. Fig. 6a is a graph showing a pattern of an acceleration signal indicating acceleration in the z-axis direction when a user without apnea symptoms is sleeping. Fig. 6b is a graph showing a pattern of a first respiration signal indicating breathing power in the x-axis direction, a second respiration signal indicating breathing power in the y-axis direction, and a third respiration signal indicating breathing power in the z-axis direction when a user without apnea symptoms is sleeping. Fig. 6c is a graph showing the result obtained by integrating the respiration signals of Fig. 6b and normalizing them between 0 and 1.

[0064] Referring to FIG. 3, a wearable electronic device (300) (e.g., the wearable electronic device (200) in FIGS. 2A and 2B) may include a first communication circuit (311), a first sensing circuit (312), a first display (313), a first input module (314), a first memory (318), and a first processor (319). The components of the wearable electronic device (300) may be operatively or electrically connected to each other. The first communication circuit (311), the first sensing circuit (312), the first display (313), the first input module (314), the first memory (318), and the first processor (319) may be implemented substantially identically to the wireless communication module (192), the sensor module (176), the display module (160), the input module (150), the memory (130), and the processor (120) of FIG. 1, respectively, and thus may perform the same functions.

[0065] The first communication circuit (311) may include a short-range wireless communication circuit configured to establish a wireless communication channel between the wearable electronic device (300) and an external electronic device (e.g., a smart phone or an access point) and to communicate data between the two devices through the established wireless communication channel. For example, the first communication circuit (311) may include a Bluetooth communication circuit. Additionally, the first communication circuit (311) may include a WiFi communication circuit. The first processor (319) may perform data communication with the external electronic device through the short-range wireless communication channel (e.g., a Bluetooth communication channel or a WiFi communication channel) established by the first communication circuit (211). The first communication circuit (311) may further include a cellular communication circuit for communicating with an external electronic device (e.g., a server (108) of FIG. 1) through a long-range wireless communication network (e.g., the second network (199) of FIG. 1).

[0066] The first sensing circuit (312) is configured to generate raw data used to provide information related to the user's health or exercise, and may provide the generated data to the first processor (319). The first sensing circuit (312) may include a biosensor (320) and a motion sensor (325). The biosensor (320) (e.g., the biosensor (211) of FIG. 2) may be configured to generate a biosignal (e.g., a signal indicating the intensity of blood flow, a signal indicating the speed of blood flow, a signal indicating the intensity of heartbeat, a signal indicating the cycle of heartbeat, a signal indicating a change in blood volume in a blood vessel) as raw data used to obtain the user's bioinformation (e.g., blood pressure, blood oxygen saturation, heart rate). For example, the biosensor (320) may include a heart rate monitoring (HRM) sensor, a photoplethysmogram (PPG) sensor, an optical blood flow measurement sensor, an optical volume pulse measurement sensor, or an optical volume measurement sensor. The motion sensor (325) may be configured to generate a motion signal (e.g., an acceleration signal, an angular velocity signal, a geomagnetic signal) as raw data used to obtain motion information of the wearable electronic device (300). For example, the motion sensor (325) may include an inertia measurement unit (IMU) configured to include an acceleration sensor, a gyroscope (in other words, an angular velocity sensor), and a magnetometer. In the motion sensor (325), the acceleration sensor can be configured to generate a first acceleration value corresponding to motion in the x-axis direction (see FIGS. 2a and 2b), a second acceleration value corresponding to motion in the y-axis direction, and a third acceleration value corresponding to motion in the z-axis direction.In the motion sensor (325), the gyroscope may be configured to generate a first angular velocity value corresponding to rotational motion about the x-axis, a second angular velocity value corresponding to rotational motion about the y-axis, and a third angular velocity value corresponding to rotational motion about the z-axis. The first processor (319) may calculate Euler angles (roll, pitch, yaw) using data received from the motion sensor (e.g., data representing acceleration values ​​of each axis and data representing a direction in which the Earth's magnetic force is directed).

[0067] The wearing confirmation module (330), the sleep confirmation module (335), the noise removal module (340), the respiratory power determination module (350), the peak selection module (360), and the apnea index determination module (370) are composed of instructions, which can be stored in the first memory (318) and executed by the first processor (319). The first processor (319) can store data generated by executing the above-described modules, for example, sleep information (380) including the apnea index indicating the degree of irregularity of breathing, in the first memory (318). The first processor (319) can also provide information (for example, the apnea index) generated by executing the above-described modules to an external electronic device through the first communication circuit (310).

[0068] The wearing confirmation module (330) can confirm whether the wearable electronic device (300) is worn on the user's body based on data acquired using the first sensing circuit (312). For example, the wearing confirmation module (330) can receive a motion signal from a motion sensor (325) and acquire motion data (in other words, a physical quantity) (e.g., acceleration, angular velocity, or magnetic field) from the received motion signal. When a change in the motion data is identified, the wearing confirmation module (330) can recognize the state of the wearable electronic device (300) as a wearing state. As another example, the wearing confirmation module (330) can receive a biosignal from a biosensor (320) and acquire biodata (e.g., oxygen saturation, HR (Heart Rate)) from the received biosignal. The wearing confirmation module (330) can recognize the state of the wearable electronic device (300) as a wearing state when the confirmed oxygen saturation falls within a preset range (e.g., when the confirmed oxygen saturation value is higher than a specified threshold value). As another example, the wearing confirmation module (330) can identify a heartbeat from biometric data acquired using a biometric sensor (320) and determine the state of the wearable electronic device (300) as a wearing state accordingly.

[0069] The sleep confirmation module (335) can determine whether the user is in a sleeping state based on data acquired using the first sensing circuit (312). For example, the sleep confirmation module (335) can monitor the degree of change in the user's movement from motion data acquired using the motion sensor (325), and if the amount of change confirmed through monitoring satisfies a preset sleep pattern, it can recognize that the user has started sleeping. As another example, the sleep confirmation module (335) can recognize that the user has started sleeping if a motion change that satisfies a sleep pattern is repeatedly confirmed for a specified period of time. As another example, the sleep confirmation module (335) may periodically check at least one of heart rate (or respiration rate) per unit time (e.g., BPM (beats per minute)), heartbeat cycle, and heartbeat size from the biometric data acquired using the biometric sensor (320), and if a value related to the confirmed heartbeat satisfies a designated sleep pattern (e.g., (e.g., if the confirmed heartbeat is below a designated threshold value), the sleep confirmation module (335) may recognize that the user has started sleeping. As another example, the sleep confirmation module (335) may recognize that the user has started sleeping if a value related to a heartbeat that satisfies a sleep pattern is repeatedly checked for a designated time period.

[0070] Based on the sleep confirmation module (335) determining that the user is sleeping, the remaining modules (340, 350, 360, 370) may be executed.

[0071] The noise removal module (340) can receive a motion signal from the motion sensor (325) and remove noise components from the received motion signal. According to one embodiment, the motion signal generated by the motion sensor (325) and output to the noise removal module (340) can include a signal indicating acceleration in the X-axis direction, a signal indicating acceleration in the Y-axis direction, and a signal indicating acceleration in the Z-axis direction, as shown in FIGS. 2A and 2B.

[0072] Referring to FIGS. 4A, 4B, and 4C, the noise removal module (340) can receive a first acceleration signal (410) indicating acceleration in the x-axis direction, a second acceleration signal (420) indicating acceleration in the y-axis direction, and a third acceleration signal (430) indicating acceleration in the z-axis direction from the motion sensor (325). The noise removal module (340) can remove components having a specified low frequency (e.g., about 0.5 Hz) or lower from the received acceleration signals (410, 420, 430) and output them to the respiratory power determination module (350).

[0073] The respiratory power determination module (350) can collect a motion signal through the noise removal module (340) at each designated first time interval. The respiratory power determination module (350) can periodically perform an operation (hereinafter, the first operation or the first function) of determining a power value representing the power (or intensity) of respiration in the first time interval using the collected motion signal, whenever the first time interval elapses. The above-described time interval can be expressed by other terms (e.g., window interval, window length). According to one embodiment, the respiratory power determination module (350) can generate a respiration signal representing the power of respiration (e.g., the difference between the power when inhaling and the power when exhaling) when the user breathes during sleep by converting the acceleration in the acceleration signal into a respiration power value. As an example of the conversion, the respiratory power determination module (350) can calculate a variance (first respiration power value) for x-axis acceleration values ​​collected during the first time interval from the acceleration signal. The respiratory power determination module (350) can calculate a variance (second respiratory power value) for the y-axis acceleration values ​​collected during the first time interval. The respiratory power determination module (350) can calculate a variance (third respiratory power value) for the z-axis acceleration values ​​collected during the first time interval. As another example of transformation, the respiratory power determination module (350) can calculate a first variance for the x-axis acceleration values ​​collected during the first time interval, a second variance for the y-axis acceleration values, and a third variance for the z-axis acceleration values ​​from the acceleration signal. The respiratory power determination module (350) can calculate a standard deviation of the first variance (first respiratory power value), a standard deviation of the second variance (second respiratory power value), and a standard deviation of the second variance (third respiratory power value). The breathing power determination module (350) can determine the maximum value among the first breathing power value, the second breathing power value, and the third breathing power value as a power value representing the power of breathing in the first time interval.Alternatively, the breathing power determination module (350) may determine the average (or sum) of the first breathing power value, the second breathing power value, and the third breathing power value as a power value representing the power of breathing in the first time interval.

[0074] The breathing power determination module (350) may determine the first time interval based on heart rate per unit time, for example, beats per minute (BPM). According to one embodiment, information indicating the lowest BPM during sleep may be stored in the first memory (318). The breathing power determination module (350) may use the BPM information stored in the first memory (318) when determining the first time interval. For example, if the BPM identified in the BPM information is '20', one cycle of the breathing signal is 3 seconds. For example, 2 seconds may be determined as the first time interval so that a breathing signal of half a cycle (1.5 seconds) is included.

[0075] The breathing power determination module (350) may periodically perform an operation (hereinafter, referred to as a second operation or a second function) of determining a power value representing the power of breathing in the second time interval using a plurality of power values ​​obtained as a result of performing the first operation whenever a second time interval designated as longer than the first time interval has elapsed. For example, the breathing power determination module (350) may determine the sum (or average, maximum value) of the plurality of power values ​​obtained as a result of performing the first operation as the power value representing the power of breathing in the second time interval. A state in which breathing is stopped for, for example, about 10 seconds or more during sleep may be defined as sleep apnea. Accordingly, 10 seconds may be designated as the second time interval.

[0076] In the present disclosure, a "peak" may be defined as a point in a time interval where the power value in a respiratory signal representing the power of respiration increases and then decreases. A "peak value" may be defined as the power value possessed by a peak in a respiratory signal. Based on these definitions, the peak detection module (360) may detect peaks and peak values ​​in a respiratory signal.

[0077] The peak selection module (360) can periodically perform an operation (hereinafter, the third operation or third function) of selecting a peak value from among the power values ​​obtained as a result of performing the second operation, whenever a second time interval elapses.

[0078] The peak selection module (360) can continuously perform an operation (hereinafter, the fourth operation or fourth function) of selecting a valid peak value in the breathing section immediately following the apnea section among the plurality of peak values ​​obtained as a result of performing the third operation while the user is confirmed to be sleeping through the sleep confirmation module (335).

[0079] Referring to FIG. 5A, while a user suffering from apnea is sleeping, the respiratory power determination module (350) can receive an acceleration signal (510) representing acceleration in the z-axis direction from the motion sensor (325) through the noise removal module (340). Although not shown, the respiratory power determination module (350) can also receive acceleration signals in the x-axis direction and the y-axis direction from the motion sensor (325) through the noise removal module (340).

[0080] Referring to FIG. 5B, the breathing power determination module (350) can generate a first breathing signal (520) representing the power of breathing in the x-axis direction by converting acceleration from a received x-axis acceleration signal into a breathing power value. The breathing power determination module (350) can generate a second breathing signal (530) representing the power of breathing in the y-axis direction by converting acceleration from a received y-axis acceleration signal into a breathing power value. The breathing power determination module (350) can generate a third breathing signal (540) representing the power of breathing in the z-axis direction by converting acceleration from a received z-axis acceleration signal (510) into a breathing power value.

[0081] Referring to FIG. 5C, the respiratory power determination module (350) can generate an integrated respiratory signal (550) by combining the first respiratory signal (510), the second respiratory signal (520), and the third respiratory signal (530) (e.g., selecting a maximum value or calculating an average or a sum from the x-axis respiratory power value, the y-axis respiratory power value, and the z-axis respiratory power value) and normalizing the respiratory power value to between 0 and 1. The peak selection module (360) can identify a peak in the respiratory signal (550) and identify a power value (peak value) at the peak. For example, the peak selection module (360) can classify a signal component (or time interval) having a power value lower than a first threshold power value in the respiratory signal (550) as an apnea interval (or first interval). The peak selection module (360) can classify a signal component having a power value higher than a first threshold power value but lower than a second threshold power value in a respiration signal (550) as a respiration section (or second section). The peak selection module (360) can classify a signal component having a power value higher than the second threshold power value in a respiration signal (550) as a tossing section (or third section). The peak selection module (360) can identify peaks (A, B, C, D) among the signal components (or time sections) classified as respiration sections. The peak selection module (360) can select a valid peak among the peaks (A, B, C, D). For example, when there are multiple peaks in one respiration section, the peak selection module (360) can arbitrarily select only one peak among the peaks as a valid peak. For example, one of A and B and one of C and D can be selected as a valid peak. The peak selection module (360) can select a peak as a valid peak if there is only one peak in a breathing interval. That is, one valid peak can be understood as an indicator that there was one apnea interval prior to the breathing interval.

[0082] Referring to FIG. 6A, while a user without apnea symptoms is sleeping, the respiratory power determination module (350) can receive an acceleration signal (610) representing acceleration in the z-axis direction from the motion sensor (325) through the noise removal module (340). Although not shown, the respiratory power determination module (350) can also receive acceleration signals in the x-axis direction and the y-axis direction from the motion sensor (325) through the noise removal module (340).

[0083] Referring to FIG. 6B, the breathing power determination module (350) can generate a first breathing signal (620) representing the power of breathing in the x-axis direction by converting acceleration from a received x-axis acceleration signal into a breathing power value. The breathing power determination module (350) can generate a second breathing signal (630) representing the power of breathing in the y-axis direction by converting acceleration from a received y-axis acceleration signal into a breathing power value. The breathing power determination module (350) can generate a third breathing signal (640) representing the power of breathing in the z-axis direction by converting acceleration from a received z-axis acceleration signal (610) into a breathing power value.

[0084] Referring to FIG. 6C, the respiratory power determination module (350) can generate an integrated respiratory signal (650) by combining the first respiratory signal (620), the second respiratory signal (630), and the third respiratory signal (640) (e.g., selecting a maximum value from the x-axis respiratory power value, the y-axis respiratory power value, and the z-axis respiratory power value, or calculating an average or a sum) and normalizing the respiratory power value to be between 0 and 1. The peak selection module (360) can check whether there is a peak value in the respiratory signal (650). For example, as illustrated in FIG. 6C, the peak selection module (360) can confirm that all respiratory power values ​​in the respiratory signal (650) are within a normal respiratory range (e.g., the first threshold power value < the power value of the respiratory signal (650)).

[0085] The apnea index determination module (370) can determine an apnea index indicating the degree of irregularity of breathing based on the number of peak values ​​selected as valid peak values. The apnea index determination module (370) can store the apnea index determined by the apnea index determination module (370) in the first memory (318) (e.g., update the sleep information (380)). The apnea index determination module (370) can provide the sleep information (380) to the user through the first display (313). The apnea index determination module (370) can also provide the sleep information (380) to an external electronic device through the first communication circuit (311).

[0086] FIG. 7 illustrates a configuration of a system for measuring sleep apnea, according to one embodiment. Referring to FIG. 7, the system may include a first electronic device (701) having a structure wearable on a human body (e.g., a wearable electronic device (300)) and a second electronic device (702). The first electronic device (701) may be connected to the second electronic device (702) via a first network (703) (e.g., the first network (198) of FIG. 1). Alternatively, the first electronic device (701) may be connected to the second electronic device (702) via the first network (703) and the second network (704) (e.g., the second network (199) of FIG. 1).

[0087] A first wearable electronic device (701) (e.g., electronic device (102) of FIG. 1) may have substantially the same configuration as the wearable electronic device (300) of FIG. 3. A second electronic device (702) (e.g., electronic device (101), electronic device (104), or server (108) of FIG. 1) may include a second communication circuit (711), a second display (713), a second input module (714), a second memory (718), and a second processor (719). The above components of the second electronic device (702) may be operatively or electrically connected to each other. The second communication circuit (711), the second display (713), the second input module (714), the second memory (718), and the second processor (719) are implemented substantially identically to the wireless communication module (192), the display module (160), the input module (150), the memory (130), and the processor (120) of FIG. 1, respectively, and thus can perform the same functions.

[0088] At least one module among the noise removal module (340), the respiratory power determination module (350), the peak selection module (360), and the apnea index determination module (370) described above may be configured with instructions and stored in the second memory (318) and executed by the second processor (319). The first processor (319) may store data generated by executing the above-described modules, for example, sleep information including the apnea index indicating the degree of irregularity of breathing, in the second memory (718). The second processor (719) may also provide information (for example, the apnea index) generated by executing the above-described modules to the first electronic device (701) through the second communication circuit (310).

[0089] FIG. 8 is a flowchart illustrating operations for selecting a valid peak value among peak values ​​in an electronic device according to one embodiment. When instructions (e.g., peak selection module (360)) stored in a first memory (318) in a wearable electronic device (300) are executed by a first processor (319), the wearable electronic device (300) may perform the operations of FIG. 8. Alternatively, when instructions stored in a second memory (718) in a second electronic device (702) are executed by a second processor (719), the second electronic device (702) may perform the operations of FIG. 8.

[0090] In operation 810, the electronic device may obtain acceleration values ​​from an acceleration signal component of a third time interval before a peak is detected, based on a peak being detected in a respiration signal (e.g., respiration signal (550) of FIG. 5c).

[0091] In operation 820, the electronic device can determine a maximum angle representing a maximum degree of inclination and a minimum angle representing a minimum degree of inclination in the third time interval using the acquired acceleration values. For example, the electronic device can calculate an Euler angle using a first acceleration value representing acceleration in the x-axis direction, a second acceleration value representing acceleration in the y-axis direction, and a third acceleration value representing acceleration in the z-axis direction. The electronic device can check the maximum angle value and the minimum angle value among the Euler angles calculated during the third time interval.

[0092] In operation 830, the electronic device can determine whether the difference between the maximum angle and the minimum angle is less than or equal to a specified threshold angle value. If the difference is greater than the threshold angle value, the electronic device can exclude the detected peak from the valid peaks in operation 840. The detected peak may be, for example, a peak generated when the user tosses and turns while sleeping.

[0093] If the difference is less than or equal to the threshold angle value, in operation 850, the electronic device can determine whether the power value of the peak (hereinafter, referred to as the peak value) is greater than or equal to the threshold power value (e.g., the first threshold power value in FIGS. 5C and 6C). If the peak value is less than the threshold power value, the electronic device can perform operation 840. The detected peak may be, for example, a peak that occurred when the user was not breathing.

[0094] If the peak value is greater than or equal to the threshold power value, in operation 860, the electronic device can determine the minimum power value in the respiratory signal component during the fourth time interval before the peak is detected.

[0095] In operation 870, the electronic device can compare a ratio of a peak value to a minimum power value to a threshold ratio value.

[0096] If the comparison result ratio is less than the threshold ratio value, the electronic device may perform operation 840. For example, the detected peak may be a peak that occurred when breathing was normal without apnea.

[0097] If the comparison result ratio is greater than or equal to the threshold ratio value, the electronic device can classify the detected peak as a valid peak in operation 880.

[0098] FIG. 9 is a flowchart illustrating operations for selecting a valid peak value among peak values ​​in an electronic device according to one embodiment. When instructions (e.g., a respiratory power determination module (350), a peak selection module (360)) stored in a first memory (318) in a wearable electronic device (300) are executed by a first processor (319), the wearable electronic device (300) may perform the operations of FIG. 9. Alternatively, when instructions stored in a second memory (718) in a second electronic device (702) are executed by a second processor (719), the second electronic device (702) may perform the operations of FIG. 9.

[0099] In operation 910, the electronic device can convert an acceleration signal generated by an acceleration sensor (e.g., a z-axis acceleration signal (510), an x-axis acceleration signal, a y-axis acceleration signal of FIG. 5a) into a respiration signal representing the power of respiration (e.g., a respiration signal (550) of FIG. 5c).

[0100] In operation 920, the electronic device can classify a signal component having a power value lower than a first threshold power value in the respiratory signal as an apnea period, classify a signal component having a power value higher than the first threshold power value and lower than a second threshold power value in the respiratory signal as a respiratory period, and classify a signal component having a power value higher than the second threshold power value in the respiratory signal as a tossing period.

[0101] At step 930, the electronic device can identify peaks (e.g., A, B, C, D in FIG. 5c) among signal components classified as breathing sections.

[0102] At operation 940, the electronic device can select a valid peak from among the peaks identified at operation 930 based on the criterion of one peak per breathing segment.

[0103] FIG. 10 is a flowchart illustrating operations for providing sleep information in an electronic device according to one embodiment. When instructions (e.g., apnea index determination module (370)) stored in a first memory (318) in a wearable electronic device (300) are executed by a first processor (319), the wearable electronic device (300) may perform the operations of FIG. 10. Alternatively, when instructions stored in a second memory (718) in a second electronic device (702) are executed by a second processor (719), the second electronic device (702) may perform the operations of FIG. 10.

[0104] In operation 1010, the electronic device can determine an apnea index based on the number of peaks selected as valid peaks. For example, the electronic device (e.g., a wearable electronic device (300)) can check the user's sleep time based on a signal (motion signal and / or bio-signal) received from a sensing circuit provided in the electronic device, and check the number of valid peaks acquired as a result of performing operation 880 or operation 940 during sleep. As another example, the electronic device (e.g., a second electronic device (702)) can receive information about a sleep start time (start of a sleep state) and a sleep end time (release from a sleep state) from a wearable electronic device (e.g., a first electronic device (701)), and, based on the received information, check the sleep time and check the number of valid peaks acquired as a result of performing operation 880 or operation 940 during sleep. The electronic device can determine the ratio of the sleep time to the number of valid peaks (the result obtained by dividing the number of valid peaks by the sleep time) as the apnea index. As another example, the electronic device can estimate the apnea-hypopnea index (AHI) based on the ratio. The ratio can have a positive correlation with the AHI provided as a result of a test (polysomnography) for diagnosing sleep disorders in a hospital. The correlation between the ratio and the AHI can be defined by a mathematical formula, for example, “y = 218687x ? 5.2089” (x = ratio, y = AHI). The electronic device can calculate the ratio of the sleep time to the number of valid peaks. The electronic device can convert the calculated ratio into the apnea-hypopnea index (AHI) using the mathematical formula.

[0105] In operation 1020, the electronic device may provide sleep information to the user based on the apnea index. For example, if the apnea index (e.g., ratio, AHI) determined in operation 1020 is greater than or equal to a specified threshold index value, the electronic device may include in the sleep information content indicating a sleep disorder and provide the information to the user. If the apnea index is less than the threshold index value, the electronic device may include in the sleep information content indicating normal sleep and provide the information to the user. As an example of the provision method, the electronic device may display the sleep information through a display provided in the electronic device. As another example, the electronic device may transmit the sleep information to an external electronic device through a communication circuit. The external electronic device may display the sleep information through a display provided in the external electronic device.

[0106] FIG. 11 is a flowchart illustrating operations for providing sleep information in an electronic device according to one embodiment. When instructions (e.g., apnea index determination module (370)) stored in a first memory (318) in a wearable electronic device (300) are executed by a first processor (319), the wearable electronic device (300) may perform the operations of FIG. 11. Alternatively, when instructions stored in a second memory (718) in a second electronic device (702) are executed by a second processor (719), the second electronic device (702) may perform the operations of FIG. 11.

[0107] In operation 1110, the electronic device may determine a first apnea index (e.g., a first ratio or a first AHI) based on the number of peaks selected as valid peaks. In addition, the electronic device may determine a second apnea index based on oxygen saturation measured using a biosensor. The operation of determining the first apnea index may be the same as operation 1010. The electronic device may measure oxygen saturation using a biosignal. The electronic device may classify the biosignal into a respiration period and an apnea period based on the measured oxygen saturation. For example, the electronic device may classify a biosignal component having an oxygen saturation greater than or equal to a threshold saturation value as a respiration period and a biosignal component having an oxygen saturation less than or equal to the threshold saturation value as an apnea period. As another example, the electronic device may measure a degree of change in oxygen saturation (amount of change) and classify the corresponding biosignal component as an apnea period when the amount of change is greater than or equal to a specified threshold change value. The electronic device may classify a biosignal component as a respiration interval when the amount of change is less than a threshold change value. The electronic device may count the number of biosignal components classified as apnea intervals. The electronic device may determine a second ratio of the sleep time to the counted number as a second apnea index. Alternatively, the electronic device may convert the second ratio into a second AHI, for example, using the mathematical formula described above, and determine the second AHI as the second apnea index.

[0108] In operation 1120, the electronic device may generate a third apnea index using the first apnea index and the second apnea index. For example, the electronic device may determine the average of the first apnea index and the second apnea index as the third apnea index.

[0109] In operation 1130, the electronic device may provide sleep information to the user based on the third apnea index. For example, the electronic device may provide the user with sleep information indicating a sleep disorder if the third apnea index (e.g., third ratio or third AHI) is greater than or equal to a specified threshold index value. The electronic device may provide the user with sleep information indicating normal sleep if the third apnea index is less than the threshold index value. As an example of a provision method, the electronic device may display the sleep information through a display provided in the electronic device. As another example, the electronic device may transmit the sleep information to an external electronic device through a communication circuit. The external electronic device may display the sleep information through a display provided in the external electronic device.

[0110] FIGS. 12a, 12b, 12c, 12d, 12e, and 12f are diagrams illustrating examples of sleep information provided to a user in an electronic device according to various embodiments.

[0111] Referring to FIG. 12A, an electronic device (e.g., the first electronic device (701) or the second electronic device (702) of FIG. 7) may display a graph representing changes in an apnea index by date on a display. For example, the electronic device may provide the apnea index in the form of dots. One dot may represent an apnea index measured for one day. Alternatively, one dot may represent an average of apnea indices measured for two or more days. In addition, the electronic device may include visual elements in the graph to allow an intuitive understanding of the apnea symptom and display them on the display. For example, the electronic device may include a critical index line (1210) corresponding to a critical index value (A) in the graph and display it on the display. The electronic device may display dots representing an apnea index exceeding the critical index value and dots representing an apnea index below the critical index value differently so as to be visually distinguishable. For example, the colors or shapes may be different as illustrated. The electronic device may display the phrase 'normal' below the critical index line (1210) and the phrase 'need caution' above it on the graph.

[0112] Referring to FIG. 12B, an electronic device (e.g., the first electronic device (701) or the second electronic device (702) of FIG. 7) may provide an apnea index in the form of points. The electronic device may display a graph including a line (1220) connecting each point along with a critical index line (1210). One point may represent the average of the apnea indices measured over two days or more. The electronic device may display a scatter plot (1230) including a graph indicating the distribution of the apnea index.

[0113] Referring to FIG. 12C, an electronic device (e.g., the first electronic device (701) or the second electronic device (702) of FIG. 7) may display a first graph (1201) representing an apnea index measured based on acceleration (ACC), a second graph (1202) representing an apnea index measured based on oxygen saturation (SpO2), and a third graph (1203) representing a merged apnea index (e.g., a third apnea index determined in operation 1120). The electronic device may display a legend (1204) along with the graphs (1201, 1202, 1203) indicating what each graph is based on.

[0114] Referring to FIG. 12d, an electronic device (e.g., a wearable electronic device (300) of FIG. 3) may display a request message (1240) on a display indicating that more sleep is needed when the sleep time is lower than a threshold sleep time value (e.g., when the user's sleep time satisfies only 30% of the recommended sleep time).

[0115] Referring to FIG. 12e, an electronic device (e.g., a wearable electronic device (300) of FIG. 3) may display on a display content (1250) indicating normal sleep based on the apnea index being lower than the threshold index value when the sleep time is equal to or greater than a threshold sleep time value (e.g., when the user's sleep time satisfies 90% or more of the recommended sleep time).

[0116] Referring to FIG. 12F, an electronic device (e.g., a wearable electronic device (300) of FIG. 3) may display on a display content (1260) indicating that sleep is disturbed based on an apnea index being greater than or equal to a threshold index value when a sleep time is greater than or equal to a threshold sleep time value (e.g., when a user's sleep time satisfies 90% or more of the recommended sleep time).

[0117] According to one embodiment, a wearable electronic device (e.g., 300) may include a motion sensor configured to generate a motion signal representing a motion of the wearable electronic device; a biosensor configured to generate a biosignal representing biological information of a user; a display; a processor (e.g., a first processor (319)); and a memory storing instructions. The instructions, when executed by the processor, may cause the wearable electronic device to determine whether the wearable electronic device is in a wearing state on the user's body and whether the user is in a sleeping state based on at least one of a motion signal received from the motion sensor and a biosignal received from the biosensor. The instructions may cause the wearable electronic device to periodically perform a first operation of collecting a motion signal from the motion sensor during a first time interval while the wearable electronic device is in the wearing state and the user is in the sleeping state, and determining a power value representing the power of respiration in the first time interval using the collected motion signal, whenever the first time interval elapses. The instructions may cause the wearable electronic device to periodically perform a second operation of determining a power value representing the power of respiration in the second time interval using power values ​​obtained as a result of performing the first operation, whenever a second time interval designated to be longer than the first time interval elapses. The instructions may cause the wearable electronic device to periodically perform a third operation of selecting a peak value from among the power values ​​obtained as a result of performing the second operation, whenever the second time interval elapses.The above instructions may cause the wearable electronic device to perform a fourth operation of selecting a valid peak value in a breathing period immediately following an apnea period from among peak values ​​obtained as a result of performing the third operation. The instructions may cause the wearable electronic device to determine an apnea index indicating a degree of irregularity of breathing based on the number of peak values ​​selected as the valid peak values. The instructions may cause the wearable electronic device to provide sleep information including the apnea index through the display.

[0118] The motion sensor may include an acceleration sensor configured to generate a signal representing acceleration in an x-axis direction, a signal representing acceleration in a y-axis direction, and a signal representing acceleration in a z-axis direction. The first operation may include an operation of generating, using the acceleration signal generated by the acceleration sensor, a first power value corresponding to the x-axis direction, a second power value corresponding to the y-axis direction, and a third power value corresponding to the z-axis direction in the first time section; and an operation of determining a maximum value or an average among the first power value, the second power value, and the third power value as a power value representing the power of breathing in the first time section.

[0119] The second operation may include an operation of determining a sum of a plurality of power values ​​obtained as a result of performing the first operation as a power value representing the power of breathing in the second time interval.

[0120] The motion sensor may include an acceleration sensor configured to generate a signal representing acceleration in the x-axis direction, a signal representing acceleration in the y-axis direction, and a signal representing acceleration in the z-axis direction. The fourth operation may include, when a first peak value is detected as a result of performing the third operation, an operation of determining a maximum angle representing a maximum degree of inclination of the wearable electronic device and a minimum angle representing a minimum degree of inclination in the third time period using signal components collected from the acceleration sensor during a third time period before the first peak value is detected; an operation of confirming a minimum power value among power values ​​obtained as a result of performing the second operation during the fourth time period before the first peak value is detected based on a difference between the maximum angle and the minimum angle being less than a specified threshold angle value and the detected peak value being greater than or equal to a threshold power value; an operation of comparing a ratio of the first peak value to the confirmed minimum power value with a threshold ratio value; And it may include an operation of selecting the first peak value as the valid peak value when the ratio is greater than or equal to the threshold ratio value, and excluding the first peak value from the valid peak value when the ratio is less than the threshold ratio value.

[0121] The operation of determining the maximum angle and the minimum angle may include an operation of calculating an Euler angle using a first acceleration value indicating acceleration in the x-axis direction, a second acceleration value indicating acceleration in the y-axis direction, and a third acceleration value indicating acceleration in the z-axis direction; and an operation of determining the maximum angle and the minimum angle among the Euler angles calculated during the third time interval.

[0122] The instructions may cause the wearable electronic device to determine a sleep time of the user based on a motion signal received from the motion sensor and / or a biosignal received from the biosensor, obtain a first apnea index by dividing the number of valid peak values ​​obtained during the sleep time by the sleep time, and generate the sleep information based on the first apnea index.

[0123] The above instructions may cause the wearable electronic device to display a request message on the display indicating that more sleep is needed when the sleep time is less than a threshold sleep time value.

[0124] The above instructions may cause the wearable electronic device to obtain a second apnea index during the sleep period based on a biosignal received from the biosensor, generate a third apnea index using the first apnea index and the second apnea index, and generate the sleep information based on the third apnea index.

[0125] According to one embodiment, an electronic device (e.g., a second electronic device (702)) may include a communication circuit for wirelessly communicating with a wearable electronic device; a display; a processor (e.g., a second processor (719)); and a memory storing instructions. The instructions, when executed by the processor, may cause the electronic device to receive, from the wearable electronic device through the communication circuit, a motion signal representing a motion of the wearable electronic device. The instructions may cause the wearable electronic device to periodically perform a first operation for a first time interval, the first operation comprising determining a power value representing a power of respiration during the first time interval using the motion signal received from the wearable electronic device, whenever the first time interval elapses. The instructions may cause the wearable electronic device to periodically perform a second operation of determining a power value representing the power of respiration in the second time interval using power values ​​obtained as a result of performing the first operation whenever a second time interval longer than the first time interval has elapsed. The instructions may cause the wearable electronic device to periodically perform a third operation of selecting a peak value from among the power values ​​obtained as a result of performing the second operation whenever the second time interval has elapsed. The instructions may cause the wearable electronic device to perform a fourth operation of selecting a valid peak value in a respiration interval immediately following an apnea interval from among the peak values ​​obtained as a result of performing the third operation. The instructions may cause the wearable electronic device to determine an apnea index representing the degree of irregularity of respiration based on the number of peak values ​​selected as the valid peak values. The above instructions may cause the wearable electronic device to provide sleep information including the apnea index through the display.

[0126] According to one embodiment, a wearable electronic device (e.g., 300) may include an acceleration sensor configured to generate an acceleration signal representing acceleration of the wearable electronic device; a display; a processor; and a memory storing instructions. The instructions, when executed by the processor, may cause the wearable electronic device to convert an acceleration signal representing acceleration received from the acceleration sensor into a respiration signal representing power of respiration. The instructions may cause the wearable electronic device to classify a signal component having a power value lower than a first threshold power value in the respiration signal as a first interval (e.g., an apnea interval). The instructions may cause the wearable electronic device to classify a signal component having a power value higher than the first threshold power value and lower than a second threshold power value in the respiration signal as a second interval (e.g., a respiration interval). The instructions may cause the wearable electronic device to classify a signal component having a power value higher than the second threshold power value in the respiration signal as a third section (e.g., a tossing and turning section). The instructions may cause the wearable electronic device to identify peaks among the signal components classified as the second section. The instructions may cause the wearable electronic device to select a valid peak among the identified peaks based on a criterion of one peak per section. The instructions may cause the wearable electronic device to determine an apnea index indicating a degree of irregularity of breathing based on the number of peaks selected as the valid peaks. The instructions may cause the wearable electronic device to provide sleep information including the apnea index through the display.

[0127] According to one embodiment, a method of operating a wearable electronic device (e.g., 300) may include an operation of determining whether the wearable electronic device is in a wearing state on a user's body and whether the user is in a sleeping state based on at least one of a motion signal received from a motion sensor of the wearable electronic device and a biosignal received from a biosensor of the wearable electronic device. The method may include an operation of periodically performing a first function of collecting a motion signal from the motion sensor during a first time interval while the wearable electronic device is in the wearing state and the user is in the sleeping state and determining a power value representing a respiration power in the first time interval using the collected motion signal, whenever the first time interval elapses. The method may include an operation of periodically performing a second function of determining a power value representing a respiration power in the second time interval using power values ​​obtained as a result of performing the first function, whenever a second time interval designated to be longer than the first time interval elapses. The method may include an operation of periodically performing a third function of selecting a peak value from among power values ​​obtained as a result of performing the second function whenever the second time interval elapses. The method may include an operation of performing a fourth function of selecting a valid peak value in a breathing period immediately following an apnea period from among peak values ​​obtained as a result of performing the third function. The method may include an operation of determining an apnea index indicating a degree of irregularity of breathing based on the number of peak values ​​selected as the valid peak values. The method may include an operation of providing sleep information including the apnea index through a display of the wearable electronic device.

[0128] The motion sensor may include an acceleration sensor configured to generate a signal representing acceleration in an x-axis direction, a signal representing acceleration in a y-axis direction, and a signal representing acceleration in a z-axis direction. The first function may include a function of generating, by using the acceleration signal generated by the acceleration sensor, a first power value corresponding to the x-axis direction, a second power value corresponding to the y-axis direction, and a third power value corresponding to the z-axis direction in the first time section; and a function of determining a maximum value or an average among the first power value, the second power value, and the third power value as a power value representing the power of breathing in the first time section.

[0129] The second function may include a function of determining a sum of a plurality of power values ​​obtained as a result of performing the first function as a power value representing the power of breathing in the second time interval.

[0130] The motion sensor may include an acceleration sensor configured to generate a signal representing acceleration in the x-axis direction, a signal representing acceleration in the y-axis direction, and a signal representing acceleration in the z-axis direction. The fourth function includes: a function of, when a first peak value is detected as a result of performing the third function, determining a maximum angle representing a maximum degree of inclination of the wearable electronic device and a minimum angle representing a minimum degree of inclination in the third time period using signal components collected from the acceleration sensor during a third time period before the first peak value is detected; a function of identifying a minimum power value among power values ​​obtained as a result of performing the second operation during the fourth time period before the first peak value is detected, based on a difference between the maximum angle and the minimum angle being less than a specified threshold angle value and the detected peak value being greater than or equal to a threshold power value; a function of comparing a ratio of the first peak value to the identified minimum power value with a threshold ratio value; And it may include a function of selecting the first peak value as the valid peak value when the ratio is greater than or equal to the critical ratio value, and excluding the first peak value from the valid peak value when the ratio is less than the critical ratio value.

[0131] The function of determining the maximum angle and the minimum angle may include a function of calculating an Euler angle using a first acceleration value indicating acceleration in the x-axis direction, a second acceleration value indicating acceleration in the y-axis direction, and a third acceleration value indicating acceleration in the z-axis direction; and a function of determining the maximum angle and the minimum angle among the Euler angles calculated during the third time interval.

[0132] In the above explanation, the prefixes “first,” “second,” and “third” are only used to distinguish between the same names and do not have any special meaning in themselves, such as importance or order.

[0133] Electronic devices according to the various embodiments disclosed in this document may take various forms. Electronic devices may include, for example, portable communication devices (e.g., smartphones), computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, or home appliances. Electronic devices according to the embodiments of this document are not limited to the aforementioned devices.

[0134] The various embodiments of this document and the terminology used therein are not intended to limit the technical features described in this document to specific embodiments, but should be understood to include various modifications, equivalents, or substitutes of the 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 the items, unless the context clearly indicates otherwise. In this document, each of the phrases "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" can include any one of the items listed together in the corresponding phrase among those phrases, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used merely to distinguish one component from another, and do not limit the components in any other respect (e.g., importance or order). When a component (e.g., a first component) is referred to as "coupled" or "connected" to another component (e.g., a second component), with or without the terms "functionally" or "communicatively," it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component.

[0135] The term "module" used in 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. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. In one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0136] Various embodiments of the present document may be implemented as software (e.g., a program (140)) including one or more instructions stored in a storage medium (e.g., an internal memory (136) or an external memory (138)) readable by a machine (e.g., an electronic device (101)). For example, a processor (e.g., a processor (120)) of the machine (e.g., an electronic device (101)) may call at least one instruction among the one or more instructions stored from the storage medium and execute it. This enables the machine to operate 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 executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently or temporarily on the storage medium.

[0137] According to one embodiment, the method according to various embodiments disclosed in this document may be provided as a computer program product. The computer program product may be traded between sellers and buyers 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 may be provided through an application store (e.g., Play Store). TM ) or directly between two user devices (e.g., smart phones), online distribution (e.g., downloading or uploading). In the case of online distribution, at least a portion of the computer program product may be at least temporarily stored or temporarily created in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0138] According to various embodiments, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and placed in other components. According to various embodiments, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In wearable electronic devices, A motion sensor configured to generate a motion signal indicative of motion of the wearable electronic device; A biosensor configured to generate a biosignal representing biological information of a user; display; processor; and Contains memory that stores instructions, The above instructions, when executed by the processor, cause the wearable electronic device to: Based on at least one of a motion signal received from the motion sensor and a biosignal received from the biosensor, it is determined whether the wearable electronic device is worn on the user's body and whether the user is sleeping. While the wearable electronic device is in the wearing state and the user is in the sleeping state, a first operation of collecting a motion signal from the motion sensor for a first time interval and determining a power value representing the power of breathing in the first time interval by using the collected motion signal is performed periodically every time the first time interval elapses. A second operation is performed periodically, each time a second time interval designated as longer than the first time interval has elapsed, to determine a power value representing the power of breathing in the second time interval using the power values ​​obtained as a result of performing the first operation, A third operation of selecting a peak value from among the power values ​​obtained as a result of performing the second operation is performed periodically every time the second time interval elapses. As a result of performing the above third operation, a fourth operation is performed to select a valid peak value in the breathing section immediately following the apnea section among the peak values ​​obtained. Based on the number of peak values ​​selected as the above valid peak values, an apnea index indicating the degree of irregularity of breathing is determined, A wearable electronic device that provides sleep information including the above apnea index through the display.

2. In the first paragraph, the motion sensor includes an acceleration sensor configured to generate a signal indicating acceleration in the x-axis direction, a signal indicating acceleration in the y-axis direction, and a signal indicating acceleration in the z-axis direction. The above first operation is, An operation of generating a first power value corresponding to the x-axis direction, a second power value corresponding to the y-axis direction, and a third power value corresponding to the z-axis direction in the first time section using an acceleration signal generated by the acceleration sensor; and A wearable electronic device including an operation of determining a maximum value or an average among the first power value, the second power value, and the third power value as a power value representing the power of breathing in the first time interval.

3. In the first paragraph, the second operation is, A wearable electronic device including an operation of determining a sum of a plurality of power values ​​obtained as a result of performing the first operation as a power value representing the power of breathing in the second time interval.

4. In paragraph 1, The above motion sensor includes an acceleration sensor configured to generate a signal representing acceleration in the x-axis direction, a signal representing acceleration in the y-axis direction, and a signal representing acceleration in the z-axis direction, The fourth operation above is, An operation of determining a maximum angle representing a maximum degree of inclination of the wearable electronic device and a minimum angle representing a minimum degree of inclination during the third time period by using signal components collected from the acceleration sensor during a third time period before the first peak value is detected as a result of performing the third operation; An operation of determining a minimum power value among power values ​​obtained as a result of performing the second operation during a fourth time interval before the first peak value is detected, based on a difference between the maximum angle and the minimum angle being less than a specified threshold angle value and the detected peak value being greater than or equal to a threshold power value; An operation of comparing a ratio of the first peak value to the confirmed minimum power value with a threshold ratio value; and A wearable electronic device including an operation of selecting the first peak value as the valid peak value if the ratio is greater than or equal to the threshold ratio value, and excluding the first peak value from the valid peak value if the ratio is less than the threshold ratio value.

5. In paragraph 4, The operation of determining the above maximum angle and the above minimum angle is, An operation of calculating an Euler angle using a first acceleration value representing acceleration in the x-axis direction, a second acceleration value representing acceleration in the y-axis direction, and a third acceleration value representing acceleration in the z-axis direction; and A wearable electronic device comprising an operation for determining the maximum angle and the minimum angle among the Euler angles calculated during the third time interval.

6. In any one of paragraphs 1 to 5, the instruction, when executed by the processor, causes the wearable electronic device to: Based on the motion signal received from the motion sensor and / or the biosignal received from the biosensor, the sleep time of the user is determined, The first apnea index is obtained by dividing the number of valid peak values ​​obtained during the above sleep time by the above sleep time, A wearable electronic device that generates sleep information based on the first apnea index.

7. In the 6th paragraph, the command, when executed by the processor, causes the wearable electronic device to: A wearable electronic device that displays a request message on the display indicating that more sleep is needed when the above sleep time is lower than a threshold sleep time value.

8. In the sixth paragraph, the command, when executed by the processor, causes the wearable electronic device to: Based on the biosignals received from the above biosensor, a second apnea index is obtained during the sleep period, Using the first apnea index and the second apnea index, a third apnea index is generated, A wearable electronic device that generates sleep information based on the third apnea index.

9. In electronic devices, Communication circuit for wireless communication with a wearable electronic device; display; processor; and Contains memory that stores instructions, The above instructions, when executed by the processor, cause the electronic device to: A motion signal representing the motion of the wearable electronic device is received from the wearable electronic device through the communication circuit, A first operation of determining a power value representing the power of breathing in a first time interval by using a motion signal received from the wearable electronic device during the first time interval is performed periodically whenever the first time interval elapses, A second operation is performed periodically, each time a second time interval designated as longer than the first time interval has elapsed, to determine a power value representing the power of breathing in the second time interval using the power values ​​obtained as a result of performing the first operation, A third operation of selecting a peak value from among the power values ​​obtained as a result of performing the second operation is performed periodically every time the second time interval elapses. As a result of performing the above third operation, a fourth operation is performed to select a valid peak value in the breathing section immediately following the apnea section among the peak values ​​obtained. Based on the number of peak values ​​selected as the above valid peak values, an apnea index indicating the degree of irregularity of breathing is determined, An electronic device providing sleep information including the above apnea index through the display.

10. In wearable electronic devices, An acceleration sensor configured to generate an acceleration signal representing acceleration of the wearable electronic device; display; processor; and Contains memory that stores instructions, The above instructions, when executed by the processor, cause the wearable electronic device to: Converting an acceleration signal representing acceleration received from the above acceleration sensor into a respiration signal representing the power of respiration, In the above respiratory signal, a signal component having a power value lower than the first threshold power value is classified as the first section, In the above respiratory signal, a signal component having a power value higher than the first threshold power value and lower than the second threshold power value is classified into a second section, In the above respiratory signal, a signal component having a power value higher than the second threshold power value is classified into a third section, Identify peaks among the signal components classified into the second section above, Based on the criterion of one peak per section, a valid peak is selected from the identified peaks, Based on the number of peaks selected as the above valid peaks, an apnea index indicating the degree of irregularity of breathing is determined, A wearable electronic device that provides sleep information including the above apnea index through the display.

11. A method for operating a wearable electronic device, An operation of determining whether the wearable electronic device is worn on a user's body and whether the user is sleeping, based on at least one of a motion signal received from a motion sensor of the wearable electronic device and a biosignal received from a biosensor of the wearable electronic device; An operation of periodically performing a first function of collecting a motion signal from the motion sensor during a first time interval while the wearable electronic device is in the wearing state and the user is in the sleeping state, and determining a power value representing the power of breathing during the first time interval by using the collected motion signal, whenever the first time interval elapses; An operation of performing a second function of determining a power value representing the power of breathing in the second time interval by using the power values ​​obtained as a result of performing the first function periodically whenever a second time interval designated as longer than the first time interval has elapsed; An operation of periodically performing a third function of selecting a peak value from among power values ​​obtained as a result of performing the second function as each second time interval elapses; An operation of performing a fourth function of selecting a valid peak value in the breathing section immediately following the apnea section among the peak values ​​obtained as a result of performing the third function; An operation of determining an apnea index indicating the degree of irregularity of breathing based on the number of peak values ​​selected as the above valid peak values; and A method comprising providing sleep information including the apnea index through a display of the wearable electronic device.

12. In the 11th paragraph, the motion sensor includes an acceleration sensor configured to generate a signal indicating acceleration in the x-axis direction, a signal indicating acceleration in the y-axis direction, and a signal indicating acceleration in the z-axis direction. The above first function is, A function of generating a first power value corresponding to the x-axis direction, a second power value corresponding to the y-axis direction, and a third power value corresponding to the z-axis direction in the first time section by using an acceleration signal generated by the acceleration sensor; and A method comprising a function of determining a maximum value or an average among the first power value, the second power value, and the third power value as a power value representing the power of breathing in the first time interval.

13. In the 11th paragraph, the second function is, A method including a function of determining a sum of a plurality of power values ​​obtained as a result of performing the first function as a power value representing the power of breathing in the second time interval.

14. In paragraph 11, The above motion sensor includes an acceleration sensor configured to generate a signal representing acceleration in the x-axis direction, a signal representing acceleration in the y-axis direction, and a signal representing acceleration in the z-axis direction, The fourth function above is, As a result of performing the third function, if a first peak value is detected, a function of determining a maximum angle representing a maximum degree of inclination of the wearable electronic device and a minimum angle representing a minimum degree of inclination during the third time period by using signal components collected from the acceleration sensor during a third time period before the first peak value is detected; A function of determining a minimum power value among power values ​​obtained as a result of performing the second operation during a fourth time interval before the first peak value is detected, based on a difference between the maximum angle and the minimum angle being less than a specified threshold angle value and the detected peak value being greater than or equal to a threshold power value; A function of comparing the ratio of the first peak value to the minimum power value confirmed above with a threshold ratio value; and A method comprising a function of selecting the first peak value as the valid peak value if the ratio is greater than or equal to the critical ratio value, and excluding the first peak value from the valid peak value if the ratio is less than the critical ratio value.

15. In paragraph 14, The function of determining the above maximum angle and the above minimum angle is, A function for calculating an Euler angle using a first acceleration value representing acceleration in the x-axis direction, a second acceleration value representing acceleration in the y-axis direction, and a third acceleration value representing acceleration in the z-axis direction; and A method comprising a function of determining the maximum angle and the minimum angle among the Euler angles calculated during the third time interval.?

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