KR20220158469A - Electronic device for processing a plurality of sensing data and method for thereof - Google Patents

Abstract

According to various embodiments, an electronic device comprises: a sensor; a communication circuit; a memory; and at least one processor. When executing instructions stored in the memory, the at least one processor obtains first sensing data and at least one sensing data by using the sensor and/or the communication circuit; identifies a first signal having a first pattern which is individually included in the first sensing data and the at least one sensing data; arranges the first sensing data and the at least one sensing data to correspond to a time point of the first signal included in the first sensing data and a time point of the first signal included in the at least one sensing data; identifies a second signal having a second pattern which is individually included in the arranged first sensing data and the at least one sensing data; and processes at least a part of the first sensing data and the at least one sensing data to correspond to a first time length between the first signal and the second signal included in the first sensing data and a second time length between the first signal and the second signal included in the at least one sensing data. Other embodiments are possible.

Description

Electronic device for processing a plurality of sensing data and its operating method

Various embodiments of the present disclosure relate to an electronic device for processing a plurality of sensed data and an operating method thereof.

In the past, personal health management services were mainly focused on healthcare, which was limited to disease treatment in hospitals or medical institutions. As a result, interest in preventive health care services for diseases through health status measurement for healthy people is increasing.

To this end, research on devices (eg, wearable devices) for measuring various types of bio-signals of the user regardless of location by being worn on the user's body is being actively conducted.

Sensing data representing various types of bio-signals (eg, electrocardiogram, pulse wave, brain wave, respiration) of a user may be acquired (or collected) by using a plurality of sensing devices including sensors for measuring bio-signals. By comparing and analyzing (or compositely analyzing) a plurality of sensing data, each of which represents a different type of bio-signal, the accuracy of analysis for user diagnosis, medical research, and technology development is improved and the possibility of making new discoveries is improved. can rise However, since a plurality of sensing data is acquired under an environment that causes a time error of the sensing data, such as a time delay when acquiring the sensing data from a plurality of sensing devices, the times of the plurality of sensing data are not synchronized with each other. A problem may occur in comparing a plurality of sensing data. In addition, even if the starting point of operation of the plurality of sensing devices is synchronized, a time error may accumulate when the plurality of sensing devices are operated for a long time, so that the time of the plurality of sensing data is not synchronized with each other, which makes it difficult to compare the plurality of sensing data. problems may arise.

According to various embodiments, an electronic device and an operating method thereof simultaneously apply a physical signal having a specific pattern to a plurality of sensing devices (or a plurality of sensors) and a plurality of sensing data obtained from the plurality of sensing devices. Comparison between a plurality of sensed data representing different bio-signals can be made possible by enabling time synchronization based on the applied physical signal.

According to various embodiments, an electronic device and its operating method arranges a plurality of sensing data based on signals having a specific pattern included in reference sensing data among a plurality of sensing data and sets a sampling frequency of the remaining sensing data. By adjusting, it is possible to compare a plurality of sensed data even in the case of long-term operation.

According to various embodiments, an electronic device may include a sensor; communication circuit; Memory; and at least one processor; wherein, when the instructions stored in the memory are executed, the at least one processor: obtains first sensing data and at least one sensing data using the sensor and/or the communication circuit; , Identifying a first signal having a first pattern included in each of the first sensing data and the at least one sensing data, and a time point of the first signal included in the first sensing data and the at least one sensing data Aligning the first sensing data and the at least one sensing data so that the viewpoints of the first signal included in correspond to each other, and a second pattern included in each of the aligned first sensing data and the at least one sensing data. Identifying a second signal having a first time length between the first signal and the second signal included in the first sensing data and the first signal and the second signal included in the at least one sensing data An electronic device may be provided that performs an operation of processing at least a portion of the first sensing data and the at least one piece of sensing data so that a second length of time between the first sensing data and the at least one sensing data corresponds to each other.

According to various embodiments, a method of operating an electronic device may include obtaining first sensing data and at least one sensing data using the sensor and/or the communication circuit; identifying a first signal having a first pattern included in each of the first sensing data and the at least one sensing data; arranging the first sensing data and the at least one sensing data so that a time point of the first signal included in the first sensing data corresponds to a time point of the first signal included in the at least one sensing data; identifying a second signal having a second pattern included in each of the aligned first sensing data and the at least one sensing data; and a first time length between the first signal and the second signal included in the first sensing data and a second time length between the first signal and the second signal included in the at least one sensing data. Correspondingly, an operation of performing an operation of processing at least a portion of the first sensing data and the at least one sensing data; including, an operation method may be provided.

According to various embodiments, an electronic device may include: a first signal output device; a second signal output device; Memory; and at least one processor; wherein, when the instructions stored in the memory are executed, the at least one processor: identifies occurrence of an event for generating a signal, and based on the occurrence of the event, the at least one processor determines the occurrence of the event at a first point in time. A first signal output device is used to output a first type of first signal having a first pattern, and the second signal output device is configured to output a second type of second signal having the first pattern; The first pattern is the magnitude of the values of the first signal and the second signal, a first period in which the values of the first signal and the second signal are repeated, or the values of the first signal and the second signal. An electronic device indicating at least one of changes in may be provided.

According to various embodiments, the solution to the problem is not limited to the above-described solution, and solutions not mentioned can be provided to those skilled in the art from this specification and the accompanying drawings. will be clearly understood.

According to various embodiments, a physical signal having a specific pattern is simultaneously applied to a plurality of sensing devices (or a plurality of sensors), and a plurality of sensing data obtained from the plurality of sensing devices is based on the applied physical signal. An electronic device and an operating method thereof enabling comparison between a plurality of sensed data indicating different biosignals by enabling time synchronization by performing a time synchronization may be provided.

In addition, according to various embodiments, by aligning a plurality of sensing data based on signals having a specific pattern included in the reference sensing data among a plurality of sensing data and adjusting the sampling frequency of the remaining sensing data, long-term operation Even in this case, an electronic device and its operating method enabling comparison between a plurality of sensed data may be provided.

1 is a block diagram of an electronic device in a network environment, according to various embodiments.
2A is a diagram for explaining an example of a system (or environment) according to various embodiments.
2B is a diagram for explaining another example of a system according to various embodiments.
Figure 2c is a diagram for explaining another example of a system according to various embodiments.
3 is a diagram for explaining an example of configurations of a sensing device, a signal applying device, and an analysis device according to various embodiments.
4A is a diagram for explaining an example of a signal applying device according to various embodiments.
4B is a diagram for explaining an example of a signal generated by a signal applying device according to various embodiments.
5 is a diagram for explaining another example of a configuration of a sensing device, a signal applying device, and an analysis device according to various embodiments.
6 is a flowchart illustrating an example of an operation of electronic devices (eg, a signal application device, a sensing device, and an analysis device) according to various embodiments.
7 is a diagram for explaining an example of an operation of obtaining sensing data using sensing devices after a signal having a specific pattern is applied by a signal applying device according to various embodiments.
8A is a diagram for explaining an example of an operation of acquiring sensing data of sensing devices according to various embodiments.
8B is a diagram for explaining an example of an operation of synchronizing the times of sensing data of an analysis device according to various embodiments.
9 is a flowchart illustrating an example of an operation of an electronic device (eg, an analysis device) according to various embodiments.
10A is a diagram for explaining an example of an operation of arranging a plurality of sensing data of an analysis device according to various embodiments.
10B is a diagram for explaining an example of an operation of adjusting a sampling frequency of at least some of a plurality of sensed data of an analysis device according to various embodiments.
11 is a diagram for explaining an example of optical vein wave data and electrocardiogram data synchronized with time according to various embodiments.
12 is a flowchart illustrating an example of an operation of an electronic device (eg, an analysis device) according to various embodiments.
13 is a diagram for explaining an example of an operation of filtering a plurality of sensed data of an electronic device according to various embodiments.
14 is a flowchart illustrating an example of an operation of electronic devices (eg, a signal application device, a sensing device, and an analysis device) according to various embodiments.
15 is a diagram for explaining an example of an operation of a signal generating device included in each of sensing devices according to various embodiments.

1 is a block diagram of an electronic device 101 within a network environment 100, according to various embodiments. Referring to FIG. 1 , in a network environment 100, an electronic device 101 communicates with an electronic device 102 through a first network 198 (eg, a short-range wireless communication network) or through a second network 199. It may communicate with at least one of the electronic device 104 or the server 108 through (eg, a long-distance wireless communication network). According to one embodiment, the electronic device 101 may communicate with the electronic device 104 through the server 108 . According to an embodiment, the electronic device 101 includes 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), interface 177, connection terminal 178, haptic module 179, camera module 180, power management module 188, battery 189, communication module 190, subscriber identification module 196 , or the antenna module 197 may be included. In some embodiments, in the electronic device 101, at least one of these components (eg, the connection terminal 178) may be omitted or one or more other components may be added. In some embodiments, some of these components (eg, sensor module 176, camera module 180, or antenna module 197) are integrated into a single component (eg, display module 160). It can be.

The processor 120, for example, executes software (eg, the program 140) to cause at least one other component (eg, hardware or software component) of the electronic device 101 connected to the processor 120. It can control and perform various data processing or calculations. According to one embodiment, as at least part of data processing or operation, the processor 120 transfers instructions or data received from other components (e.g., sensor module 176 or communication module 190) to volatile memory 132. , processing commands or data stored in the volatile memory 132 , and storing resultant data in the non-volatile memory 134 . According to one embodiment, the processor 120 may include a main processor 121 (eg, a central processing unit or an application processor) or a secondary processor 123 (eg, a graphics processing unit, a neural network processing unit ( NPU: neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor). For example, when the electronic device 101 includes the main processor 121 and the auxiliary processor 123, the auxiliary processor 123 may use less power than the main processor 121 or be set to be specialized for a designated function. can The secondary processor 123 may be implemented separately from or as part of the main processor 121 .

The secondary processor 123 may, for example, take the place of the main processor 121 while the main processor 121 is in an inactive (eg, sleep) state, or the main processor 121 is active (eg, running an application). ) state, together with the main processor 121, at least one of the components of the electronic device 101 (eg, the display module 160, the sensor module 176, or the communication module 190) It is possible to control at least some of the related functions or states. According to one embodiment, the auxiliary processor 123 (eg, image signal processor or communication processor) may be implemented as part of other functionally related components (eg, camera module 180 or communication module 190). have. According to an embodiment, the auxiliary processor 123 (eg, a neural network processing device) may include a hardware structure specialized for processing an artificial intelligence model. AI models can be created through machine learning. Such learning may be performed, for example, in the electronic device 101 itself where the artificial intelligence model is performed, or may be performed through a separate server (eg, the server 108). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning or reinforcement learning, but in the above example Not limited. The artificial intelligence model may include a plurality of artificial neural network layers. Artificial neural networks include deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), It may be one of deep Q-networks or a combination of two or more of the foregoing, but is not limited to the foregoing examples. The artificial intelligence model may include, in addition or alternatively, software structures in addition to hardware structures.

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

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 .

The input module 150 may receive a command or data to be used for a component (eg, the processor 120) of the electronic device 101 from an outside of the electronic device 101 (eg, a user). The input module 150 may include, for example, a microphone, a mouse, a keyboard, a key (eg, a button), or a digital pen (eg, a stylus pen).

The sound output module 155 may output sound signals to the outside of the electronic device 101 . The sound output module 155 may include, for example, a speaker or a receiver. The speaker can be used for general purposes such as multimedia playback or recording playback. A receiver may be used to receive an incoming call. According to one embodiment, the receiver may be implemented separately from the speaker or as part of it.

The display module 160 can visually provide information to the outside of the electronic device 101 (eg, a user). The display module 160 may include, for example, a display, a hologram device, or a projector and a control circuit for controlling the device. According to one embodiment, the display module 160 may include a touch sensor set to detect a touch or a pressure sensor set to measure the intensity of force generated by the touch.

The audio module 170 may convert sound into an electrical signal or vice versa. According to one embodiment, the audio module 170 acquires sound through the input module 150, the sound output module 155, or an external electronic device connected directly or wirelessly to the electronic device 101 (eg: Sound may be output through the electronic device 102 (eg, a speaker or a headphone).

The sensor module 176 detects an operating state (eg, power or temperature) of the electronic device 101 or an external environmental state (eg, a user state), and generates an electrical signal or data value corresponding to the detected state. can do. According to one embodiment, the sensor module 176 may include, for example, a gesture sensor, a gyro sensor, an air pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a bio sensor, It may include a temperature sensor, humidity sensor, or light sensor.

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

The connection terminal 178 may include a connector through which the electronic device 101 may be physically connected to an external electronic device (eg, the 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 (eg, a headphone connector).

The haptic module 179 may convert electrical signals into mechanical stimuli (eg, vibration or movement) or electrical stimuli that a user may perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module 179 may include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

The camera module 180 may capture still images and moving images. According to one embodiment, the camera module 180 may include one or more lenses, image sensors, image signal processors, or flashes.

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

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

The communication module 190 is a direct (eg, wired) communication channel or a wireless communication channel between the electronic device 101 and an external electronic device (eg, the electronic device 102, the electronic device 104, or the server 108). Establishment and communication through the established communication channel may be supported. The communication module 190 may include one or more communication processors that operate independently of the processor 120 (eg, an application processor) and support direct (eg, wired) communication or wireless communication. According to one embodiment, the communication module 190 is a wireless communication module 192 (eg, 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 (eg, : A local area network (LAN) communication module or a power line communication module). Among these communication modules, a corresponding communication module is a first network 198 (eg, a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network 199 (eg, legacy It may communicate with the external electronic device 104 through a cellular network, a 5G network, a next-generation communication network, the Internet, or a telecommunications network such as a computer network (eg, a LAN or a WAN). These various types of communication modules may be integrated as one component (eg, a single chip) or implemented as a plurality of separate components (eg, multiple chips). The wireless communication module 192 uses subscriber information (eg, International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module 196 within a communication network such as the first network 198 or the second network 199. The electronic device 101 may be identified or authenticated.

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

The antenna module 197 may transmit or receive signals or power to the outside (eg, an external electronic device). According to 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 (eg, PCB). According to one embodiment, the antenna module 197 may include a plurality of antennas (eg, 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 is selected from the plurality of antennas by the communication module 190, for example. can be chosen A signal or power may be transmitted or received between the communication module 190 and an external electronic device through the selected at least one antenna. According to some embodiments, other components (eg, a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module 197 in addition to the radiator.

According to various embodiments, the antenna module 197 may form a mmWave antenna module. According to one embodiment, the mmWave antenna module includes a printed circuit board, an RFIC disposed on or adjacent to a first surface (eg, a lower surface) of the printed circuit board and capable of supporting a designated high frequency band (eg, mmWave band); and a plurality of antennas (eg, array antennas) disposed on or adjacent to a second surface (eg, a top surface or a side surface) of the printed circuit board and capable of transmitting or receiving signals of the designated high frequency band. can do.

At least some of the components are connected to each other through a communication method between peripheral devices (eg, a bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI)) and signal ( e.g. commands or data) can be exchanged with each other.

According to an embodiment, commands or data may be transmitted or received between the electronic device 101 and the external electronic device 104 through the server 108 connected to the second network 199 . Each of the external electronic devices 102 or 104 may be the same as or different from the electronic device 101 . According to an embodiment, all or part of operations executed in the electronic device 101 may be executed in one or more external electronic devices among the external electronic devices 102 , 104 , or 108 . For example, when the electronic device 101 needs to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device 101 instead of executing the function or service by itself. Alternatively or additionally, one or more external electronic devices may be requested to perform the function or at least part of the service. One or more external electronic devices receiving the request may execute at least a part of the requested function or service or an additional function or service related to the request, and deliver the execution result to the electronic device 101 . The electronic device 101 may provide the result as at least part of a response to the request as it is or additionally processed. To this end, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device 101 may provide an ultra-low latency service using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device 104 may include an internet of things (IoT) device. Server 108 may be an intelligent server using machine learning and/or neural networks. According to one embodiment, the external electronic device 104 or server 108 may be included in the second network 199 . The electronic device 101 may be applied to intelligent services (eg, smart home, smart city, smart car, or health care) based on 5G communication technology and IoT-related technology.

Electronic devices according to various embodiments disclosed in this document may be devices of various types. The electronic device may include, for example, a portable communication device (eg, a smart phone), a computer device, a portable multimedia device, a portable medical device, a camera, an electronic device, or a home appliance. An electronic device according to an embodiment of the present document is not limited to the aforementioned devices.

Various embodiments of this document and terms 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, like reference numerals may be used for like or related elements. The singular form of a noun corresponding to an item may include one item or a plurality of items, unless the relevant context clearly dictates otherwise. In this document, "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 "A Each of the phrases such as "at least one of , B, or C" may include any one of the items listed together in that phrase, or all possible combinations thereof. Terms such as "first", "second", or "first" or "secondary" may simply be used to distinguish a given component from other corresponding components, and may be used to refer to a given component in another aspect (eg, importance or order) is not limited. A (e.g., first) component is said to be "coupled" or "connected" to another (e.g., second) component, with or without the terms "functionally" or "communicatively." When mentioned, it means that the certain component may be connected to the other component directly (eg by wire), wirelessly, or through a third component.

The term "module" used in various embodiments of this document may include a unit implemented in hardware, software, or firmware, and is interchangeably interchangeable with terms such as, for example, logic, logical blocks, parts, or circuits. can be used as A module may be an integral part or the smallest unit of a part or part thereof that performs one or more functions. For example, according to one embodiment, the module may be implemented in the form of an application-specific integrated circuit (ASIC).

Various embodiments of this document provide one or more instructions stored in a storage medium (eg, internal memory 136 or external memory 138) readable by a machine (eg, electronic device 101). It may be implemented as software (eg, the program 140) including them. For example, a processor (eg, the processor 120 ) of a device (eg, the electronic device 101 ) may call at least one command among one or more instructions stored from a storage medium and execute it. This enables the device to be operated to perform at least one function according to the at least one command invoked. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' only means that the storage medium is a tangible device and does not contain a signal (e.g. electromagnetic wave), and this term refers to the case where data is stored semi-permanently in the storage medium. It does not discriminate when it is temporarily stored.

According to one embodiment, the method according to various embodiments disclosed in this document may be included and provided in a computer program product. Computer program products may be traded between sellers and buyers as commodities. A computer program product is distributed in the form of a device-readable storage medium (e.g. compact disc read only memory (CD-ROM)), or through an application store (e.g. Play Store ^TM ) or on two user devices (e.g. It can be distributed (eg downloaded or uploaded) online, directly between smart phones. In the case of online distribution, at least part of the computer program product may be temporarily stored or temporarily created in a storage medium readable by a device such as a manufacturer's server, an application store server, or a relay server's memory.

According to various embodiments, each component (eg, module or program) of the above-described components may include a single object or a plurality of entities, and some of the plurality of entities may be separately disposed in other components. have. According to various embodiments, one or more components or operations among the aforementioned corresponding components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (eg modules or programs) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by a corresponding component among the plurality of components prior to the integration. . According to various embodiments, the actions performed by a module, program, or other component are executed sequentially, in parallel, iteratively, or heuristically, or one or more of the actions are executed in a different order, or omitted. or one or more other actions may be added.

Hereinafter, examples 200a, 200b, and 200c of systems (or environments) including electronic devices (eg, the signal applying device 210, the sensing device 230, and the analyzing device 250) according to various embodiments are described. ) is explained. Since the description of the electronic device 101 described above in FIG. 1 may be applied to electronic devices described below (eg, the signal applying device 210, the sensing device 230, and the analyzing device 250), Redundant descriptions are omitted.

2A is a diagram for explaining an example 200a of a system (or environment) according to various embodiments. 2B is a diagram for explaining another example 200b of a system according to various embodiments. 2c is a diagram for explaining another example 200c of a system according to various embodiments. However, it is not limited to those shown in FIGS. 2A to 2C , and the system may be implemented to include more or fewer devices.

According to various embodiments, referring to FIGS. 2A to 2C , the system includes devices for collecting a plurality of types (or various types) of sensing data (hereinafter, sensing devices 230 ) and a sensing device 230 . A device implemented to apply a physical signal having a specific pattern to each of the devices (hereinafter, a signal applying device 210), or a device for processing (eg, time synchronization) and analyzing the collected sensing data (hereinafter, an analysis device (hereinafter, an analysis device) 250)) may be implemented to include at least one of them. The names of the sensing device 230, the signal applying device 210, and the analyzing device 250 are names for classifying the roles and/or functions of electronic devices, and one device is the sensing device 230, the signal applying device ( 210), or at least one of the analysis device 250. For example, one device may be the sensing device 230 and the analyzing device 250 . According to the operation of the devices included in the system (eg, the signal application device 210, the sensing device 230, and the analysis device 250), based on the pattern signal 201 included in various types of sensing data Various types of sensing data are visually synchronized, and analysis is performed based on the visually synchronized sensing data, thereby improving accuracy of analysis of the sensing data and increasing the possibility of new diagnosis and medical discovery according to the analysis. Hereinafter, examples of each device included in the system (eg, the signal applying device 210, the sensing device 230, and the analyzing device 250) will be described.

According to various embodiments, each of the sensing devices 230 (eg, the first sensing device 230a, the second sensing device 230b, ..., the nth sensing device 230c) may receive at least one piece of sensing data. It can be implemented to obtain. For example, each of the sensing devices 230 (eg, the first sensing device 230a, the second sensing device 230b, ..., the n-th sensing device 230c) includes at least one sensor (eg, : The first sensor 231a, the second sensor 231b, ... , and the nth sensor 231c), and the at least one sensor (eg, the first sensor 231a, the second sensor ( 231b), ..., and the nth sensor 231c) may be used to obtain data. For example, the at least one sensor (eg, the first sensor 231a, the second sensor 231b, and the nth sensor 231c) includes sensors for measuring various types of biosignals, and For example, sensors for measuring biosignals such as electrocardiogram, electromyogram, brainwave, body temperature, respiration, pressure, pulse wave (eg, photoplethysmogram (PPG)), and bioimpedance may be included. However, the at least one sensor (eg, the first sensor 231a, the second sensor 231b, ..., and the n-th sensor 231c) is not limited to the description, and data of other types than bio-signals. It may include various types of sensors for measuring , or at least one sensor (eg, the first sensor 231a, the second sensor 231b, ..., and the nth sensor 231c) instead of time Obtaining devices may be provided for acquiring data and/or information of a kind requiring synchronization. Each of the sensors (eg, the first sensor 231a, the second sensor 231b, ... , and the n-th sensor 231c) each have various types of physical signals (eg, It may be implemented to time-series (or continuously) measure values of light, current or voltage (eg, measure the amount of light or measure the magnitude of current or voltage). For example, the sensor for measuring the light venous wave may include an optical sensor for measuring light reflected when light is irradiated to a part of the body. As another example, a sensor for measuring an electrocardiogram may include electrodes (eg, sensor electrodes) for measuring a current or voltage value returned from a body part. Without being limited to the above description, the sensors (eg, the first sensor 231a, the second sensor 231b, ..., and the n-th sensor 231c) are various types of sensors for detecting various types of biosignals. It may be implemented to measure a physical signal of , and since this is a well-known technique, a detailed description thereof will be omitted. In addition, each of the sensing devices 230 has a designated type through the at least one sensor (eg, the first sensor 231a, the second sensor 231b, ..., and the nth sensor 231c). Sensing data sampled at a specified frequency may be obtained by obtaining at least one data representing a biosignal and processing (eg, digitizing) the obtained at least one data at a specified sampling frequency. The obtained sensing data may include digital data acquired according to a sampling frequency (eg, data acquired per sampling period). Since a specific sampling frequency is shared among the sensing devices 230 included in the system, data acquired by each sensing device 230 may be sampled with the same sampling frequency. The sensing device 230 is a wearable device (eg, a first sensor 231a, a second sensor 231b, ..., and an n-th sensor 231c) including at least one sensor described above. It may be implemented as a smart watch, a smart patch, or a head-mounted display (HMD) device), but is not limited to the description and includes at least one sensor (eg, a first sensor 231a, a second sensor 231b) , ... , and the nth sensor 231c) and/or devices (or modules) implemented to acquire data requiring time synchronization.

According to various embodiments, the signal application device 210 may generate and/or output various types of physical signals (eg, light, current, or voltage) 201 having a specific pattern (eg, or waveform). For example, the pattern represents a change in the value of a physical signal during a specific time period. For example, the pattern may include a waveform (eg, a sine wave, square wave, pulse, ramp wave) having a specified period during a specific time period. Examples of the pattern will be described later with reference to FIGS. 3 to 5 . The signal applying device 210 may simultaneously apply a physical signal 201 having the same pattern of a type that can be measured by each of the plurality of sensing devices 230 to each of the plurality of sensing devices 230 . For example, as shown in FIG. 2A , the signal applying device 210 may be implemented separately from the plurality of sensing devices 230 . The signal applying device 210 includes a plurality of sensing devices 230 (eg, a first sensing device 230a, a second sensing device ( 230a), ... , the physical signal 201 having the same pattern corresponding to each of the plurality of sensing devices 230 may be applied to each of the nth sensing devices 230c). For example, when the first sensor 231a included in the first sensing device 230a is an optical sensor and the second sensor 231b included in the second sensing device 230b is an electrode, the signal is applied. The device 210 simultaneously provides (or outputs) light having a specific pattern to the first sensor using a light generating device (eg, an LED) in response to occurrence of a designated event (eg, identifying that a physical button is pressed). ), and an electrical signal (eg, voltage or current) having a specific pattern may be provided (or applied) to the second sensor using an electrical signal generating device. A plurality of sensing devices 230 implemented as shown in FIG. 2A (eg, a first sensing device 230a, a second sensing device 230b, ... , an nth sensing device 230c) and The separately implemented signal applying device 210 will be described later with reference to FIGS. 3 and 4 . In addition, for example, as shown in FIG. 2C, a plurality of signal applying devices (eg, a first signal applying device 210a, a second signal applying device 210b, ..., an n-th signal applying device 210c) )) are included in each of the sensing devices 230 (eg, the first sensing device 230a, the second sensing device 230b, ... , the nth sensing device 230c) and correspond to the sensors It can be implemented to output a physical signal having a specified pattern of a kind. Each of the plurality of signal applying devices (eg, the first signal applying device 210a, the second signal applying device 210b, ..., the n-th signal applying device 210c) generates a designated event (eg, In response to receiving a request (or instruction) to cause a signal to be generated, simultaneously sending a physical signal having the same pattern to each sensor (eg, the first sensor 231a, the second sensor 231b, ... , and It may be provided as the nth sensor 231c). Inducing signal generation for controlling each of the signal applying devices (eg, the first signal applying device 210a, the second signal applying device 210b, ..., the nth signal applying device 210c) The request may be simultaneously generated and provided to each of the signal applying devices (eg, the first signal applying device 210a, the second signal applying device 210b, ..., the n-th signal applying device 210c). have.

According to various embodiments, the analysis device 250 may receive sensing data from the sensing devices 230, process the received sensing data (eg, time synchronization), and analyze the processed sensing data. can For example, the processing of the sensing data includes an operation of arranging the sensing data based on the signal 201 having the same pattern included in each of the sensing data and a sampling frequency (or sampling time) of some of the sensing data. It may include an operation to adjust. In one embodiment, the analysis device 250 may be at least one sensing device (eg, the first sensing device 230a) selected from among the plurality of sensing devices 230 as shown in FIG. 2A . For example, among the plurality of sensing devices 230 , a device having a high processing capability (eg, a processor having a high computing capability) may be selected as the analysis device 250 . For example, a smart watch may be selected as the analysis device 250 . In another embodiment, the analysis device 250 may be implemented separately from the plurality of sensing devices 230 as shown in FIG. 2B. The separately implemented analysis device 250 may be implemented as a terminal (eg, a smart phone), and may be implemented as various types of devices capable of performing analysis operations without being limited thereto.

Hereinafter, examples of configurations of the signal applying device 210 , the sensing device 230 , and the analyzing device 250 according to various embodiments will be described.

3 is a diagram for explaining an example of configurations of a signal application device 210, a sensing device 230, and an analysis device 250 according to various embodiments. However, without being limited to what is shown in FIG. 3 , devices may be implemented to include more or fewer components. Hereinafter, FIG. 3 will be described with reference to FIGS. 4A to 4B and FIG. 5 .

4A is a diagram for explaining an example of a signal applying device 210 according to various embodiments. 4B is a diagram for explaining an example of a signal generated by the signal applying device 210 according to various embodiments. The signal (eg, square wave) having a pattern shown in FIG. 4B is an example, and signals having various types of patterns may be generated without being limited to those described and/or illustrated as described above. 5 is a diagram for explaining another example of configurations of a sensing device 230, a signal application device 210, and an analysis device 250 according to various embodiments.

Hereinafter, an example of a configuration of the signal applying device 210 according to various embodiments will be described first.

According to various embodiments, referring to FIG. 3 , the signal applying device 210 includes a first communication circuit 340, a first memory 330, and a plurality of signal generating devices 320 (eg, a first generating device). 321 , a second generating device 323 , an nth generating device 325 ), and a processor 310 including a signal generating module 311 .

According to various embodiments, the first communication circuit 340 is an external electronic device (eg, a plurality of sensing devices 230, an analysis device 250, or another external device (eg, a server)) in various types of communication methods. ) and may transmit and/or receive data. The communication method may be a communication method for establishing a direct communication connection such as Bluetooth and Wi-Fi direct, a communication method using an access point (AP) (eg, Wi-Fi communication), or a cellular communication using a base station. It may include at least one of communication methods (eg, 3G, 4G/LTE, 5G) using. Since the first communication circuit 340 may be implemented in the same manner as the communication module 190 described above in FIG. 1 , duplicate descriptions will be omitted.

According to various embodiments, the first memory 330 may store various types of information. Since the first memory 330 may be implemented in the same way as the memories 132 and 134 described above in FIG. 1 , duplicate descriptions will be omitted. In one embodiment, the information stored in the first memory 330 may include instructions that, when executed, cause the processor 310 to perform an operation. In another embodiment, the information stored in the first memory 330 may include information on a plurality of patterns. The pattern may include a waveform (eg, sine wave, square wave, pulse, ramp wave) having a designated period. For example, referring to FIG. 4B , the pattern may include square waves (or square waves) 431 , 433 , 435 , 437 , 438 , and 439 of various cycles. Meanwhile, information on various types of patterns that can be analyzed may be stored without being limited to the types of waveform patterns shown and/or described. In another embodiment, the information stored in the first memory 330 may include information (or a driving algorithm) for driving each of the plurality of signal generators 320 to output signals of a specific pattern. have.

According to various embodiments, each of the plurality of signal generating devices 320 may generate and/or output a specific type of signal having a specific pattern. For example, one signal generator is implemented to generate and/or output a measurable type of physical signal from the sensor 360 included in the above-described sensing device 230, and a processor 310 (eg: According to the control of the signal generating module 311, a physical signal of a specific pattern may be output. The type of the physical signal corresponds to a type of physical signal measurable by a sensor included in each of the sensing devices 230. For example, the physical signal is light, an electrical signal such as voltage and/or current, or a movement such as vibration. It exists in nature and can include various types of measurable physical information, such as temperature and temperature. For example, referring to 401 of FIG. 4A , the signal applying device 210 may include a light generating device (eg, a light emitting diode (LED)) 321 as a signal generating device. In this case, an inner space 410 may be formed (or a hole may be formed) such that the upper surface of the signal applying device 210 is open, and the light generating device 321 may be disposed on a lower surface of the inner space. In addition, a sensor (eg, optical vein wave measurement) of a specific sensing device 230 (eg, the first sensing device 230a (eg, smart watch) of FIG. A physical structure for supporting the first sensing device 230a may be formed so that the sensor) is disposed at a position for measuring light output from the light generating device 321 . As another example, referring to 401 of FIG. 4A , the signal applying device 210 is an electrical signal generating device including electrodes (eg, a positive electrode 323a and a negative electrode 323b) as a signal generating device ( 323) may be included. Electrodes of the electrocardiogram patch 230b for electrocardiogram measurement may be connected to the electrodes 323a and 323b included in the electrical signal generator 323, respectively. In addition, without being limited to what has been described and/or shown, the signal generating devices 320 and the sensing devices 230 (eg, the first sensing device 230a and the second sensing device 230b) may be transmitted through body parts. It may be connected to the signal generating device (eg, human body communication). For example, in a state where electrodes of the second sensing device 230b (eg, an electrocardiogram patch) are attached to the body, each electrode may be electrically connected through a body part (eg, skin) to which the patch is attached. At this time, the anode electrode 323a and the cathode electrode 323b of the electrical signal generator 323 are connected to each of the electrodes of the electrocardiogram patch or attached to the body, and the electrical signal generator 323 generates an electrical signal When generating, the generated electrical signal may be applied to one electrode and another electrode of the ECG patch through a part of the body.

Hereinafter, the processor 310 will be described.

According to various embodiments, the processor 310 may include at least one of an application processor (AP), a central processing unit (CPU), a graphic processing unit (GPU), a display processing unit (DPU), or a neural processing unit (NPU). can include At least some of the modules (eg, the signal generation module 311) included in the processor 310 described below may be implemented (eg, executed) in software, firmware, hardware, or a combination of at least two of them. can For example, the modules may be in the form of applications, programs, computer codes, instructions, routines, or processes executable by the processor 310. can be implemented as Accordingly, when the modules are executed by the processor 310, the modules may cause the processor 310 to perform an operation associated with the module (or a function that the module may provide). In this case, the modules may be stored in the first memory 330, but are not limited thereto (eg, stored in a memory implemented in the processor 310). Alternatively, the modules may be implemented as part of a specific application. Alternatively, without being limited to what has been described and/or shown, each module may be implemented as separate hardware (eg, a processor and a control circuit) from the processor 310 .

According to various embodiments, the signal generating module 311 may control some of the plurality of signal generating devices 320 to simultaneously output a physical signal of a specified pattern. The pattern represents the value of a physical signal at each point in time during a specific time period. For example, the pattern may include a waveform (eg, sine wave, square wave, pulse, ramp wave) having a designated period. Meanwhile, without being limited to the types of waveform patterns shown and/or described, the signal generation module 311 may control to output physical signals of various types of analyzeable patterns. For example, referring to FIG. 4B , the pattern may include square waves (or square waves) 431, 433, 435, 437, 438, and 439 of various cycles. Information on the patterns may be stored in the first memory 330 as described above. The signal generating module 311 generates one of a plurality of signal generating devices 320 based on information on patterns included in the first memory 330 based on the occurrence of an event for generating and/or outputting a signal. Each of the parts can be controlled to output signals of a specific pattern at the same time. For example, the occurrence of the event is a button implemented in the signal application device 210 (eg, a hardware button (eg, a button 415 shown in 401 of FIG. 4A), an electronic button displayed on a touch screen) It may include being pressed, or receiving a request (or message, or instruction) to output a signal, but is not limited thereto, and various events that cause signal generation and/or output may cause the signal application device 210 can be set in advance. For example, referring to 401 of FIG. 4A, a physical button 415 is formed on the outer surface of the signal applying device 210, and referring to 402 of FIG. 4A, as the physical button 415 is pressed, the signal applying device 210 Signal generating devices (eg, a light generating device (eg, LED) 321 and an electrical signal generating device (eg, a positive electrode 323a and a negative electrode 323b)) in the power supply unit 421 implemented in ) ) may be electrically connected to generate and/or output a signal. In this case, the processor 310 (eg, the signal generating module 311) may control each signal applying device 210 to which power is applied to output signals of the same pattern. The processor 310 (eg, the signal generating module 311) selects a specific pattern (eg, a square wave of a specific period) from pattern information stored in the first memory 330, and each of the signal generating devices ( 320) (eg, the first generating device 321, the second generating device 323, and the nth generating device 325) may be controlled to generate and/or output a specific type of signal in a specific pattern.

Meanwhile, referring to FIG. 5 , at least one component of the signal applying device 210 (eg, the signal generating device 320 and the signal generating module 311) may be implemented in the sensing device 230. For example, as shown in FIG. 2C described above, when the signal applying device 210 is implemented in the sensing device 230, at least one component of the signal applying device 210 (eg, the signal generating device 320 ) and the signal generating module 311) may be implemented in the sensing device 230 . Accordingly, the sensing device 230 may apply a physical signal of a specific pattern to the sensor 360 using the signal generating device 320 based on the signal generating module 311 . The signal generating device 320 provided in the sensing device 230 may be implemented at a location close to the sensor 360 in order to apply a physical signal to the sensor 360 .

Hereinafter, examples of the sensing device 230 and the analyzing device 250 according to various embodiments will be described.

According to various embodiments, referring to FIG. 3 , a sensing device 230 (eg, the first sensing device 230) includes a second communication circuit 380, a second memory 370, a sensor 360, and a processor 350 including a sensing data acquisition module 351 , a data alignment module 353 , and a data correction module 355 .

According to various embodiments, the second communication circuit 380 and the second memory 370 may be implemented as the above-described first communication circuit 340 and the first memory 330, so duplicate descriptions are omitted.

According to various embodiments, the sensor 360 may include at least one sensor. For example, the sensor 360 includes sensors for measuring various types of biosignals, such as electrocardiogram, electromyogram, brainwave, body temperature, respiration, pressure, and pulse wave (eg, photoplethysmogram (PPG)). , sensors for measuring biosignals such as bioimpedance. However, it is not limited to what has been described, and the at least one sensor may include various types of sensors for measuring other types of data other than biosignals, or, instead of at least one sensor, the type of data requiring visual synchronization and/or Alternatively, acquisition devices for obtaining information may be provided. Each of the sensors 360 time-sequentially (or continuously) measures (eg, measures the amount of light) of various types of physical signals (eg, light, current, or voltage) for measuring the aforementioned biosignal. , measuring the magnitude of current or voltage). For example, the sensor for measuring the light venous wave may include an optical sensor for measuring light reflected when light is irradiated to a part of the body. As another example, the electrocardiogram sensor may include electrodes for measuring current or voltage values returned from a body part.

An example of the processor 350 will be described below. Since the processor 350 may be implemented in the same way as the above-described first processor, duplicate descriptions will be omitted. Meanwhile, without being limited to what is shown and/or described, the processor 350 may be implemented to include only some of the modules (eg, the sensing data acquisition module 351, the data alignment module 353, and the data correction module 355). may be For example, when the sensing device 230 is implemented to perform an operation as the analysis device 250, it may include a data alignment module 353 and a data correction module 355 together with the sensing data acquisition module 351. , When the analysis device 250 is implemented to be unable to perform an operation, only the sensing data acquisition module 351 may be included. For example, in the case where the analysis device 250 is separately implemented as described in FIG. 2B or in the case of a sensing device that does not operate as the analysis device 250, the sensing device is not limited to that shown in FIG. 3 ( The processor 350 of 230 may be implemented to include only the sensing data acquisition module 351 .

According to various embodiments, the sensing data acquisition module 351 may acquire and process data detected using the sensor 360 . For example, the sensing data acquisition module 351 acquires an analog signal (or analog data) using the sensor 360, samples the analog signal at a designated sampling frequency, and generates a digital signal (or digital data) (hereinafter, sensing data). For example, the sampling frequency (or sampling rate) represents the number of times data is acquired per second. For example, when the sampling frequency is 20 Hz, the sensing data acquisition module 351 acquires data from the data acquired using the sensor at a period of 1/20 second. Data can be sampled by acquiring data. Accordingly, the sensing data may include digital data acquired with a specific sampling frequency. The sampling frequency may be identically set for each of the plurality of sensing devices 230 . In one embodiment, the sensing data acquisition module 351 obtains a physical signal having a specified pattern output from the signal applying device 210 using the sensor 360, samples the acquired physical signal, and performs digitized sensing. data can be obtained. In another embodiment, the sensing data acquisition module 351 may acquire a biosignal using the sensor 360 and obtain digitized sensing data by sampling the obtained biosignal.

According to various embodiments, the data alignment module 353 may align a plurality of sensing data based on a signal having a pattern included in each of the plurality of sensing data. For example, the data alignment module 353 determines that the timing of a signal of a specific pattern included in reference data selected from among a plurality of sensing data and the timing of a signal of a specific pattern included in the other remaining sensing data are different on the same time axis. A plurality of sensing data may be aligned to correspond (eg, the same).

According to various embodiments, the data correction module 355 may process some of the plurality of sensed data so that the lengths of the plurality of sensed data correspond to each other. For example, the data correction module 355 may perform a plurality of sensing data based on a sampling frequency calculated based on a time length between signals each having a specific pattern included in reference data selected from among a plurality of sensing data. Among them, the sampling frequency (or sampling time) of the remaining sensing data may be adjusted.

Hereinafter, an example of operations of the signal applying device 210 , the sensing device 230 , and the analyzing device 250 according to various embodiments will be described. Hereinafter, for convenience of description, the signal applying device 210 and the sensing device 230 described in FIG. 2A are implemented separately, and one sensing device 230 among the sensing devices 230 is selected as the analysis device 250. However, unless otherwise noted, examples described below are examples in which the analysis device 250 described in FIG. 2B is separately implemented or the signal applying device 210 in the sensing device 230 described in FIG. 2C. ) may also be applied to an example in which ) is implemented, so redundant descriptions are omitted.

According to various embodiments, the signal application device 210 may provide a signal of a specified pattern to each of the sensing devices 230 in response to the occurrence of a specified event. The analysis device 250 (eg, a device selected from among the sensing devices 230) synchronizes the times of the plurality of sensing data collected by the sensing devices 230 after applying a signal of a specified pattern, thereby performing time-synchronized sensing. data can be analyzed.

6 is a flowchart 600 for describing an example of an operation of electronic devices according to various embodiments. The operations shown in FIG. 6 are not limited to the order shown and may be performed in various orders. Also, according to various embodiments, more operations than the operations shown in FIG. 6 or at least one operation less than that shown in FIG. 6 may be performed. Hereinafter, FIG. 6 will be described with reference to FIGS. 7 and 8A to 8B.

7 is a diagram for explaining an example of an operation of obtaining sensing data using the sensing devices 230 after a signal having a specific pattern is applied by the signal applying device 210 according to various embodiments. . 8A is a diagram for explaining an example of an operation of acquiring sensing data of the sensing devices 230 according to various embodiments. 8B is a diagram for explaining an example of an operation of synchronizing the times of sensing data of the analysis device 250 according to various embodiments.

According to various embodiments, the signal applying device 210 identifies the occurrence of an event for signal generation in operation 601, and uses some of the plurality of signal generating devices 320 in operation 603 to have a designated pattern. A plurality of signals can be generated. For example, the occurrence of the event for generating the signal may include pressing a hardware button as shown in 701 of FIG. 7 , but displayed on a touch screen (not shown) implemented in the signal applying device 210 It may include that an electronic button to be selected is selected. In addition, without being limited to what has been described and/or shown, the generation of the event for generating the signal may include receiving a request (or message, or instruction) for outputting the signal. The request may be transmitted to the signal applying device 210 from a remote device for controlling the signal applying device 210 . As shown in 701 of FIG. 7 based on the occurrence of the event, the signal applying device 210 may include some (eg, a light generating device) of a plurality of signal generating devices 320 included in the signal applying device 210. 320a and the electrical signal generating device 320b) may be controlled to output physical signals 713a and 713b of a specific pattern. As described above, the specific pattern represents a change in the value of a physical signal during a specific time period, and may include, for example, a waveform having a designated period (eg, a sine wave, a square wave (or square wave), a pulse wave, and a ramp wave). The signal applying device 210 selects a specific pattern based on information on patterns stored in a memory (eg, the first memory 330) and outputs a signal in a specific pattern among the signal generating devices 320. Some (eg, light generator 320a and electrical signal generator 320b) may be controlled (or driven). For example, when the selected pattern is a square wave (or square wave) of 5 Hz, the signal application device 210 ) applies power of a specific value in the form of a square wave of 5 Hz to the light generator 320a and the electricity generator to control the light 713a in the form of a square wave of 5 Hz to be output from the light generator 320a, and to output the electric signal It is possible to control the generator 320b to output a 5Hz square wave electric signal 713b (eg, voltage or current) The signal applying device 210 randomly selects one pattern from among the plurality of patterns. Alternatively, patterns may be selected in a designated order (eg, in order of numbers when identification numbers are set in patterns) Hereinafter, the signal applying device 210 is used to signal generating devices 320 (eg, light generating devices). Examples of operations for controlling the device 320a and the electrical signal generating device 320b will be described.

In an embodiment, the signal application device 210 may control all of the plurality of signal generators 320 to output physical signals 713a and 713b of a specific pattern at the same time based on the occurrence of an event.

In another embodiment, the signal application device 210 identifies some of the plurality of signal generators 320 based on the occurrence of an event, and controls the identified some signal generators to output physical signals 713a and 713b. can do. For example, the signal applying device 210 identifies some of the plurality of signal generating devices 320 detected as having the sensor devices 600a and 600b disposed (or connected or engaged), and identifies some of the identified signals. The generating devices 320 may be controlled. For example, the signal applying device 210 includes a sensor (eg, a proximity sensor) for detecting the arrangement of the sensing device 230 in a peripheral area where the signal generating device is provided, and sensing around the signal generating device using the sensor. It can detect that device 230 is deployed. As another example, based on an electrical value generated when the signal applying device 210 is fastened to or connected to a signal generating device (eg, the electrical signal generating device 320b), the sensing device 230 is connected to the signal generating device. Connection (or engagement) can be detected. Also, for example, the signal applying device 210 may identify some of the plurality of signal generating devices 320 corresponding to a combination of biosignals and control some of the identified signal generating devices. For example, the bio-signal combination may indicate types of bio-signals. For example, the bio-signal combination may include an electrocardiogram and a photovenous wave. Without being limited to the described example, the combination of the biosignals may be implemented to include various types of biosignals according to a user's setting. In the signal application device 210, information about a plurality of bio-signal combinations indicating types of bio-signals requiring time synchronization and information about a signal generating device corresponding to each combination may be stored in advance. When receiving information on a specific bio-signal combination, the signal applying device 210 may identify a signal generating device corresponding to a specific bio-signal combination among a plurality of signal generating devices 320 based on the pre-stored information. can For example, when the combination of the specific bio-signal includes an electrocardiogram and an optical venous wave, the signal applying device 210 provides an optical signal to a sensor for measuring an electrocardiogram among a plurality of signal generating devices 320. The generating device 320a and the electrical signal generating device 320b for providing a signal to the sensor for measuring the photovenous wave may be identified. In one embodiment, the signal applying device 210 provides information on a combination of bio-signals (eg, displayed on a touch screen (not shown)) and receives a selection of a specific bio-signal combination from among the displayed combinations. can In another embodiment, the signal application device 210 may receive information about a specific bio-signal combination from an external device (eg, the analysis device 250).

According to various embodiments, the occurrence of the event for generating the signal may be performed multiple times, and accordingly, a plurality of signals having a pattern may be included in sensing data obtained from each of the sensor devices 230 . For example, the signal application device 210 generates a physical signal according to an event at the time of starting the analysis of the bio-signal, and generates a physical signal according to the event at the time of ending the analysis of the bio-signal. can make it

Meanwhile, according to various embodiments, when the signal generating device is implemented in the sensing devices 230 as shown in FIG. 2C, the signal generating device included in the specific sensing devices 230 generates a specific pattern based on the occurrence of an event. It is possible to perform an operation of outputting a signal having , which will be described later with reference to FIGS. 14 and 15 .

According to various embodiments, one sensing device 230 (eg, the first sensing device 600a) receives a first signal having a designated pattern in operation 605, and another sensing device 230 (eg, the second sensing device 600a) The sensing device 600b may receive the second signal having a designated pattern in operation 607 . The user W1 may place or connect a plurality of sensing devices 230 including at least one sensor requiring time synchronization to the signal applying device 210 . For example, as shown in 701 of FIG. 7 , the first sensing device 600a (eg, smart watch) is located around a signal generating device (eg, light generating device 320a) on the signal applying device 210. and the second sensing device 600b (eg, an electrocardiogram patch) may be connected to another signal generating device (eg, the electrical signal generating device 320b). After the sensing devices 230 (eg, the first sensing device 600a and the second sensing device 600b) are disposed and/or connected, as described above, the signal applying device 210 generates a specified event. Based on , the signal generating devices 320a and 320b may be controlled to output signals 713a and 713b of a specific pattern. Accordingly, signals of a specific pattern are provided to sensors (eg, the optical sensor 711) included in each of the sensing devices 230 (eg, the first sensing device 600a and the second sensing device 600b). can In addition, without being limited to what has been described and/or shown, the sensing devices 230 (eg, the first sensing device 600a and the second sensing device 600b) may transmit the signal generating devices 320a and 320b through body parts. ) (e.g. human body communication). For example, in a state in which the electrodes of the ECG patch are attached to the body, the respective electrodes may be electrically connected through a body part (eg, skin) to which the patch is attached. At this time, when the electrical signal generator 320b generates an electrical signal while the positive electrode and the negative electrode of the electrical signal generator 320b are connected to each of the electrodes of the patch or attached to the body, the generated electrical signal is generated. An electrical signal may be applied to one electrode and another electrode through a body part.

According to various embodiments, one sensing device 230 (eg, the first sensing device 600a) performs an operation of acquiring sensing data using the first sensor in operation 609, and another sensing device 230 ( Example: In operation 611, the second sensing device 600b may obtain sensing data using the second sensor. For example, each of the plurality of sensing devices 230 may obtain signals 713a and 713b of a specific pattern output from the signal applying device 210 by using a sensor for measuring a biosignal. As an example, referring to 701 of FIG. 7 , the first sensing device 600a (eg, a smart watch) uses the light detection sensor 711 for detecting a light venous wave to detect a light generating device (of the signal applying device 210). 320a) obtains the optical signal 713a of a specific pattern, and the second sensing device 600b (eg, an electrocardiogram patch) uses electrodes for electrocardiogram detection to generate electrical signals of the signal application device 210. An electrical signal (eg, current or voltage change) 713b of a specific pattern output from 320b may be obtained. Also, for example, each of the plurality of sensing devices 230 may obtain a biosignal of the user W1 by using a sensor. For example, as shown in 702 of FIG. 7 , each of the plurality of sensing devices 230 may be worn by the user W1 after receiving the signal having the specific pattern. In a state worn by the user W1, each of the plurality of sensing devices 230 may obtain a biosignal using a sensor. The first sensing device 600a (eg, smart watch) detects the photovenous vein wave signal of the user W1 using the optical sensor 711 for measuring the photovenous vein wave, and the second sensing device 600b may detect the ECG signal of the user W1 using electrodes for measuring the ECG. Since the operation of detecting the biological signal using each of the sensors is a well-known technique, a detailed description thereof will be omitted. As described above, the plurality of sensing devices 230 (eg, the first sensing device 600a and the second sensing device 600b) may sample signals acquired using the sensors using a specific sampling frequency. . For example, the sampling frequency indicates the number of times data is acquired per second, and for example, when the sampling frequency is 20 Hz, the sensing devices 230 (eg, the first sensing device 600a and the second sensing device 600b) Data may be sampled by acquiring data at a 1/20 second cycle from data obtained using a silver sensor. Accordingly, the sensing data may include a plurality of digital data acquired according to the sampling frequency. In one embodiment, the plurality of sensing devices 230 may establish a communication connection with each other to share information on the same sampling frequency and sample data at the same sampling frequency. In another embodiment, the plurality of sensing devices 230 receive information on the same sampling frequency from an external device (eg, separately implemented analysis device 250 (eg, smart phone 721)), Data can be sampled at the same sampling frequency.

According to various embodiments, sensing data obtained from each of the plurality of sensing devices 230 may include a signal having at least one pattern and a biosignal. For example, referring to FIG. 8A , the first sensing data 801 and the second sensing data 802 obtained from each of the sensing devices 230a and 230b are a plurality of signals 713a having a pattern in specific time periods. , 811a, 813a, 713b, 811b, 813b) and data representing biosignals in the remaining time sections. At this time, at least one of the plurality of signals 713a, 811a, 813a, 713b, 811b, and 813b having a pattern included in the sensing data (eg, the first sensing data 801 and the second sensing data 802) Signals 713a and 713b of have specific patterns of physical signals output from the signal applying device 210 and may correspond to each other.

According to various embodiments, one of the plurality of sensing devices 230 (eg, the first sensing device 600a) (hereinafter referred to as the analysis device 250) is configured to analyze the sensing data in operation 613. The occurrence of an event can be identified. For example, being selected as the analysis device 250 from among the plurality of sensing devices 230 (eg, the first sensing device 600a and the second sensing device 600b) or operating as the analysis device 250 The sensing device 230 may identify occurrence of an event for bio-signal analysis. In one embodiment, the sensing device 230 executes and/or drives an application (or program) for bio-signal analysis, and generates an event for bio-signal analysis (eg, bio-signal analysis) using the application. menu selection for ) can be identified. When the sensing device 230 identifies the occurrence of the event, an operation as the analysis device 250 may be performed (eg, sensing data collection and time synchronization). Meanwhile, the analysis device 250 (eg, the first sensing device 600a and the second sensing device 600b) is provided separately from the sensing devices 230 (eg, the first sensing device 600a and the second sensing device 600b), without being limited to those described and/or illustrated. As the application (or program) is executed in the smart phone 721 of 702 of FIG. 7 , the analysis device 250 may perform an operation (eg, sensing data collection and time synchronization).

According to various embodiments, the analysis device 250 (eg, the first sensing device 600a) identifies a device to request sensing data in operation 615, requests sensing data from the identified device in operation 617, and in operation 619 Sensing data can be received from For example, as shown in 702 of FIG. 7 , the first sensing device 600a selected as the analysis device 250 receives second sensing data collected by the second sensing device 600b from the second sensing device 600b. can receive In an embodiment, the sensing device 230 (eg, the first sensing device 600a) identifies devices (eg, the second sensing device 600b) establishing a communication connection with the sensing device 230. and may request sensing data collected from the identified devices as the identified devices. In another embodiment, the first sensing device 600a identifies some devices that collect the analysis-requested sensing data among devices that have established a communication connection with the first sensing device 600a, and performs sensing with the identified some devices. data can be requested. Information on the type of sensing data collected by each device may be previously stored in the first sensing device 600a. When the type of sensing data to be analyzed is selected using the aforementioned application (or program) for analyzing biosignals, the first sensing device 600a corresponds to the type of sensing data identified based on the previously stored information. devices may be identified, and sensing data may be requested from the identified devices. Meanwhile, the analysis device 250 implemented separately from the sensing devices 230 (eg, the first sensing device 600a and the second sensing device 600b) is not limited to the description and/or the illustrated sensing device. It is also possible to request sensing data from the sensing devices 230 and receive sensing data from the sensing devices 230 . On the other hand, without being limited to what has been described and/or illustrated, the first sensing device 600a may obtain sensing data using a plurality of sensors included in the first sensing device 600a.

Meanwhile, not limited to what has been described and/or shown, a device that performs an operation as the analysis device 250 without performing an operation of identifying the occurrence of an event and an operation of requesting sensing data from the sensing devices 230 (eg, : The first sensing device 600a or the separately implemented analysis device 250 may automatically periodically or non-periodically receive sensing data from the sensing devices 230 communicatively connected thereto.

According to various embodiments, the analysis device 250 (eg, the first sensing device 600a) may further receive additional information together with the sensing data. For example, the additional information may further include the type of biosignal indicated by the sensing data and information (eg, unique ID, identifier) on a device that acquired the sensing data. Accordingly, the analysis device 250 (eg, the first sensing device 600a) may identify each of the sensing data (eg, the first sensing data 801 and the second sensing data 802).

According to various embodiments, the analysis device 250 (eg, the first sensing device 600a) may synchronize the times of a plurality of sensed data based on a signal having a designated pattern in operation 621 . For example, as shown in 810 of FIG. 8B , the first sensing device 600a detects a specific time period 815 of sensing data (eg, first sensing data 801 and second sensing data 802). In order to compare and/or analyze some data corresponding to (eg, a time window), an operation of synchronizing the times of some data (eg, first sensing data 801 and second sensing data 802) is performed. can do. The specific time period 815 may be set in various ways according to the settings of the user W1. In the operation of synchronizing the time, the data (eg, the first sensing data 801 and the second sensing data 802) acquired at the same time point are transferred to the same time point (or the same time axis) on the same time axis (or ordinal axis). order) may mean an operation to set data. For example, the first digital data included in the first sensing data 801 is acquired based on the detection of the photovenous vein wave of the user W1 at a point in time, and the first digital data included in the second sensing data 802 is obtained. 2 digital data may be obtained based on the electrocardiogram of the user W1 detected at the same time point. In this case, each of the sensing data (eg, the first sensing data 801 and the second sensing data 802) may be obtained with different sampling frequencies. For example, each sensing device (eg, the first sensing device 600a and the second sensing device 600b) collects sensing data at the same sampling frequency (eg, detects data from each sensor at the same sampling frequency). However, due to sampling errors during collection (e.g., software errors or hardware errors), the sampling frequency (or sampling time) of each sensing device has an error (e.g., greater than a specific sampling frequency). value of the sampling frequency, or change to a small value of frequency). Accordingly, each of the sensing devices (eg, the first sensing device 600a and the second sensing device 600b) receives sensing data (eg, the first sensing device 600b) at different (or predetermined difference) sampling frequencies. Data 801 and second sensing data 802 may be collected. For example, the first sensing data 801 may be collected with a relatively lower sampling frequency (or longer sampling time) than the second sensing data 802 . Accordingly, referring to FIG. 10B, the pattern signals 713b, 811b, and 813b of the second sensing data 802 are generated in the time interval between the pattern signals 713a, 811a, and 813a of the first sensing data 801. It may be longer, but is not limited to what has been described and/or shown. The operation of synchronizing the times is a time axis (or an order axis) so that the first digital data included in the first sensing data 801 and the second digital data included in the second sensing data 802 can be compared together. ) may include an operation of setting to be associated with a specific time point (or specific order). Accordingly, the first sensing device 600a may compare and analyze the first digital data and the second digital data set to be associated with a specific time point (or specific sequence).

According to various embodiments, the aforementioned specific time period 815 is a time when the user wants to perform complex analysis on the plurality of sensing data (eg, the first sensing data 801 and the second sensing data 802). can In one embodiment, a device operating as an analysis device (eg, the first sensing device 600a) displays an execution screen of an application (or program) for the complex analysis, and the user displays the sensing data on the execution screen. (eg, an interface for setting a time for complex analysis of the first sensing data 801 and the second sensing data 802 may be provided. The user can set the specific time period 815 on the interface. Accordingly, a device operating as an analysis device (eg, the first sensing device 600a) may perform complex analysis for the time period 815 set by the user. In another embodiment, a device (eg, the first sensing device 600a) operating as an analysis device is selected from among the plurality of sensing data (eg, the first sensing data 801 and the second sensing data 802). Pattern signals (eg, pattern signals 713a, 713b, 811a, and 811b) included in at least a part are identified, and pattern signals (eg, pattern signals 713a, 713b, 811a, and 811b) are included. A menu containing information about time periods may be displayed. For example, a device operating as an analysis device (eg, the first sensing device 600a) calculates a time period 815 including the first pattern signal 713a and the second pattern signal 811a, A menu including information on the time period 815 may be displayed. At this time, a device operating as an analysis device (eg, the first sensing device 600a) is configured for a designated time from the point of time of each of the pattern signals (eg, the first pattern signal 713a and the second pattern signal 811a). Information on the time period 815 may be obtained by calculating a time period defined as a point of time before and after a point of time. When a device (eg, the first sensing device 600a) operating as an analysis device selects one time period (eg, the time period 815) among a plurality of time periods included in the menu by the user, the time period A composite analysis can be performed on (815).

According to various embodiments, the first sensing device 600a determines the time of a plurality of sensing data based on a signal indicating a specific pattern included in each of the pieces of data corresponding to a specific time period 815 of the plurality of sensing data. can be synchronized. For example, as shown in 820 of FIG. 8B , the first sensing device 600a may perform a specific time period (eg, first sensing data 801 and second sensing data 802) of a plurality of sensing data (eg, first sensing data 801 and second sensing data 802). 815) to identify the pattern signals 713a, 713b, 811a, and 811b, and to process a plurality of sensing data so that each of the same pattern signals 713a, 713b, 811a, and 811b is located at the same time point. can be done Based on the processing operation, as shown in 802 of FIG. 8B, the length of time between pattern signals of a plurality of sensing data (eg, first sensing data 801 and second sensing data 802) ( Example: the length of time between the first signal 713a and the second signal 811a of the first sensing data 801 and the length of time between the first signal 713b and the second signal 811b of the second sensing data 802 time length) may be equal to each other. The operation of processing the plurality of sensing data (eg, the first sensing data 801 and the second sensing data 802) is an operation of adjusting a timing of a pattern signal included in the sensing data and/or between pattern signals. It may include an operation of adjusting the sampling frequency of. An operation of processing the plurality of sensed data (eg, the first sensed data 801 and the second sensed data 802 ) will be described in detail with reference to FIGS. 9 to 11 .

According to various embodiments, the analysis device 250 (eg, the first sensing device 600a) may analyze a plurality of time-synchronized sensing data in operation 623 . For example, the first sensing device 600a is a biological signal between pattern signals of a plurality of sensing data (eg, first sensing data 801 and second sensing data 802) included in a specific time period. By comparing data representing , it is possible to analyze a biosignal. For example, the first sensing device 600a identifies a value of the second sensing data 802 at a time point of data having a specific peak value detected in the first sensing data 801, and based on the values, the user The state of W1 may be diagnosed, or the correlation between two bio-signals represented by each of the sensing data 801 and 802 or the accuracy of one sensing data 801 may be analyzed.

Hereinafter, an example of operations of the signal applying device 210 , the sensing device 230 , and the analyzing device 250 according to various embodiments will be described. Hereinafter, for convenience of description, the signal applying device 210 and the sensing device 230 described in FIG. 2A are implemented separately, and one sensing device 230 among the sensing devices 230 is selected as the analysis device 250. However, unless otherwise noted, examples described below are examples in which the analysis device 250 described in FIG. 2B is separately implemented or the signal applying device 210 in the sensing device 230 described in FIG. 2C. ) may also be applied to an example in which ) is implemented, so redundant descriptions are omitted.

According to various embodiments, the analysis device 250 processes a plurality of sensing data for time synchronization of the plurality of sensing data based on at least one signal having a pattern included in each of the plurality of acquired sensing data. action can be performed. The processing of the plurality of sensing data may include adjusting and aligning the viewpoints of the pattern signals included in the sensing data and/or adjusting the sampling frequency (or sampling time) between the pattern signals included in the sensing data. It may include an operation of processing the length of time between them to correspond to each other.

9 is a flowchart 900 for explaining an example of an operation of an electronic device (eg, the analysis device 250) according to various embodiments. The operations shown in FIG. 9 are not limited to the order shown and may be performed in various orders. Also, according to various embodiments, more operations than the operations shown in FIG. 9 may be performed, or at least one operation less than that shown in FIG. 9 may be performed. Hereinafter, FIG. 9 will be described with reference to FIGS. 10A to 10B and FIG. 11 .

10A is a diagram for explaining an example of an operation of arranging a plurality of sensing data of the analysis device 250 according to various embodiments. 10B is a diagram for explaining an example of an operation of adjusting a sampling frequency of at least some of a plurality of sensed data of the analysis device 250 according to various embodiments. 11 is a diagram for explaining an example of optical vein wave data and electrocardiogram data synchronized with time according to various embodiments.

According to various embodiments, an electronic device (eg, the analysis device 250) may obtain a plurality of sensing data by using a sensor and/or a communication circuit in operation 901 . In one embodiment, the sensing device 230 selected as the analysis device 250 or performing an operation as the analysis device 250 uses the sensor 360 provided in the sensing device 230 to obtain sensing data. and may receive sensing data acquired by the other sensing devices 230 from the other sensing devices 230 using a communication circuit. In another embodiment, a plurality of sensing devices 230 from a plurality of sensing devices 230 to which an analysis device 250 implemented separately from the sensing devices 230 establishes a communication connection using a communication circuit. Collected sensing data may be received. In another embodiment, the sensing device 230 may obtain a plurality of sensor data indicating different types of biosignals by using the plurality of sensors 360 included in the sensing device 230 . As an example, the analysis device 250 may obtain sensing data 1101 representing an electrocardiogram signal and sensing data 1103 representing a photovenous wave, as shown in FIG. 11 .

According to various embodiments, the electronic device (eg, the analysis device 250) may select first sensing data 1000a to be a reference among a plurality of sensing data as shown in 1001 of FIG. 10 in operation 903. . The reference sensing data may be reference data to be compared with the rest of the sensing data (or to be used as a true value). For example, as will be described later, the analysis device 250 determines other sensing data (eg, second sensing data (eg, second sensing data 1000b)), or other sensing data (eg, second sensing data 1000b) based on the sampling frequency of the reference sensing data (eg, first sensing data 1000a). )) can adjust the sampling frequency. In one embodiment, the analysis device 250 randomly detects a reference among a plurality of sensing data (eg, first sensing data 1000a, second sensing data 1000b, and third sensing data 1000c). data can be selected. In another embodiment, the analysis device 250 determines that the accuracy is the highest among a plurality of sensing data (eg, the first sensing data 1000a, the second sensing data 1000b, and the third sensing data 1000c). The determined sensing data may be selected as sensing data to be a reference. The accuracy may mean time accuracy of sensing data. For example, the analysis device 250 determines the time accuracy of the sensing data according to the type of biosignal represented by the sensing data, the type of sensor for acquiring the sensing data, and/or the type of physical signal corresponding to the sensing data. can judge For example, time accuracy of sensing data obtained by electrodes for electrocardiogram measurement may be higher than time accuracy of sensing data obtained by an optical sensor for photovenous wave measurement. In the analysis device 250, information on accuracy is stored in advance for each type of biosignal represented by the sensing data or for each type of sensor from which the sensing data was obtained, and the analysis device 250 performs the sensing data obtained based on the information. Accuracy corresponding to the data can be identified. Based on the identification of the accuracy, the analysis device 250 may determine sensing data having the highest accuracy (eg, the first sensing data 1000a) as reference data. Also, for example, the analysis device 250 may determine time accuracy of the sensing data based on information affecting accuracy, such as a collection time of the sensing data. For example, the analysis device 250 may determine that the sensing data has lower accuracy as the collection time of the sensing data increases.

According to various embodiments, the electronic device (eg, the analysis device 250) identifies a first signal having a first pattern included in the first sensing data 1000a and each of the remaining at least one sensing data in operation 905 and , in operation 907, the first sensing data 1000a and the rest of the sensing data such that a time point of the first signal included in the first sensing data 1000a corresponds to a time point of the first signal included in at least one sensing data. Data can be sorted. For example, the analysis device 250 includes reference sensing data (eg, first sensing data 1000a) and remaining sensing data (eg, second sensing data 1000b) as shown in 1002 of FIG. 10A. A specific time period 1031 (e.g., a time window ( Based on the signals 1011a, 1013a, 1011b, 1013b, 1011c, and 1013c having patterns included in the time window), a plurality of sensing data (eg, first sensing data 1000a, second sensing data 1000b) ), and the third sensing data 1000c) may be aligned. As described above, the specific time period 1031 may be set according to the user's settings, and redundant descriptions will be omitted. In an embodiment, the analysis device 250 determines the earliest (or first) signals 1011a and 1013a having a pattern included in reference sensing data (eg, the first sensing data 1000a). Based on the time point of the sequential) signal (eg, the first pattern signal 1011a), the remaining sensing data (eg, the second sensing data 1000b) on the time axis (or order axis) that becomes the reference point And times of the remaining sensing data may be adjusted so as to be the timing (or the same order) of the same signals 1011b and 1011c within the designated time period 1031 of the third sensing data 1000c. For example, the analysis device 250 identifies a first time point t1 on one time axis of the first pattern signal 1011a of the reference sensing data (eg, the first sensing data 1000a), and Second time points t2 and t3 of the first pattern signals 1011b and 1011c of the sensing data (eg, the second sensing data 1000b and the third sensing data 1000c) may be identified. As will be described later, the time point of the pattern signal may be interpreted as a time period in which the pattern signal is detected, or may be interpreted as a specific point in time (eg, a point in time when a specific pattern signal starts) during a time period in which the pattern signal is detected. The analysis device 250 calculates a difference between the identified first time point t1 and the second time points t2 and t3, and calculates the remaining sensing data (eg, the second sensing data 1000b) by the calculated difference. and the third sensing data 1000c) may be adjusted (eg, added or subtracted). As an example, the analysis device 250, as shown in FIG. 11 , generates a signal 1111 representing a specific pattern of sensing data 1101 representing an electrocardiogram signal and the same pattern of sensing data 1103 representing a photovenous wave. It can be aligned by making the viewpoint of the signal 1131 the same. On the other hand, without being limited to what has been described and/or shown, among a plurality of signals having a pattern included in a designated time period, a signal other than the fastest signal (eg, 1011a) (eg, 1013a) may be selected as a reference signal. may be

According to various embodiments, the analysis device 250 determines the remaining sensing data (eg, first sensing data 1000a) based on characteristics of a signal (eg, 1011a) having a specific pattern of the reference sensing data (eg, first sensing data 1000a). A signal having the specific pattern included in the second sensing data 1000b and the third sensing data 1000c may be detected (or identified). For example, the characteristic may include at least one of a magnitude of a signal value forming a pattern, a period of a signal value, or a change in a signal value. In one embodiment, the analysis device 250 identifies characteristics of signals within a specified time period 1031 of the first sensing data 1000a as a reference, and at least one signal having a specific pattern based on the identified characteristics. can be detected (or identified). For example, the analysis device 250 pre-stores information on characteristics of each pattern (eg, at least one of the size of a signal value, the period of a signal value, or a change in a signal value), and stores the previously stored information and At least one signal having a specific pattern may be detected by comparing characteristics of signals within the identified designated time period 1031 . For example, the analysis device 250 repeats the value of the signal at a cycle of 1/10 second in a first time period within a time period 1031 designated in reference sensing data (eg, the first sensing data 1000a), When a characteristic in which the signal value maintains a maximum value for 1/20 second within 1/10 second and a minimum value for the remaining 1/20 second is identified, the identified characteristic is determined by referring to previously stored information. It can be identified by the liver as corresponding to a square wave pattern with a period of 1/10 second. Accordingly, the analysis device 250 may determine that the signal of the first time period is a square wave pattern signal with a period of 1/10 second. The analysis device 250 generates a signal having a square wave pattern with a period of 1/10 second from the remaining sensing data (eg, the second to third sensing data 1000b and 1000c) based on the method of analyzing the detected characteristics. By detecting, a signal having the same pattern may be detected from a plurality of sensed data (eg, first to third sensed data 1000a, 1000b, and 1000c).

According to various embodiments, the analysis device 250 selects a specific time point associated with a signal (eg, the first signal) having a pattern of sensing data (eg, the first sensing data 1000a) as a reference, and selects the selected specific time point. Based on the viewpoint, the viewpoint of the remaining sensing data may be adjusted. For example, as described above, the analysis device 250 detects a signal having a specific pattern corresponding to the identified characteristic by identifying characteristics of a signal in a time period (hereinafter, a pattern time period), and Among them, a reference point in time t1 can be selected. In one embodiment, the analysis device 250 may select a time point at which a pattern time period in which a signal having a specific pattern is detected starts as a reference time point. At this time, the analysis device 250 may set a delay and select a time point that is later by a preset time than the time point at which the pattern time period starts as a reference time point. It is not limited to what has been described, and in another embodiment, the analysis device 250 may use a criterion such as an end time point of a pattern time period in which a signal having a specific pattern is detected, or an average time point (eg, an intermediate time point between a start time and an end time). You can also choose when to become.

According to various embodiments, the electronic device (eg, the analysis device 250) generates a second signal having a second pattern included in the aligned first sensing data 1000a and the at least one sensing data in operation 909 . In operation 911, the first time length between the first signal and the second signal included in the first sensing data 1000a and the first signal and the second signal included in the at least one sensing data An operation of processing the remaining sensing data may be performed so that the second length of time between the sensing data corresponds to each other. For example, the analysis device 250 may include other than reference sensing data (eg, first sensing data 1000a) and a reference signal (eg, first pattern signal 1011a) within a specific time period 1013. Other signals (eg, the second pattern signal 1013a) are identified, and other remaining sensing data is based on the sampling frequency between the signals (eg, the first pattern signal 1011a and the second pattern signal 1013a). The time lengths between the sensing data (eg, the first to third sensing data 1000a, 1000b, and 1000c) correspond to each other by adjusting the sampling frequency of the second to third sensing data 1000b and 1000c. can be processed to do so. The other signal identified above may have a pattern different from that of the reference signal, but may have a corresponding pattern without being limited thereto. For example, as shown in 1003 of FIG. 10B, the analysis device 250 receives a second pattern signal 1013a having a pattern subsequent to the first pattern signal 1011a in the reference first sensing data 1000a. can be detected. The second pattern signal 1013a may be a signal having a pattern detected at the last point in the specific time period 1013, or may be a signal having a pattern immediately following the first pattern signal 1011a without being limited thereto. . Since the operation of detecting the signal having the pattern can be performed (eg, analyzing characteristics) as described above, a duplicate description will be omitted. The analyzer may calculate a reference sampling frequency by dividing the length of time between the first pattern signal 1011a and the second pattern signal 1013a detected in the first sensing data 1000a by the number of samplings. The sampling number may be calculated by multiplying a predetermined sampling frequency by a time length between the first pattern signal 1011a and the second pattern signal 1013a, but the first pattern signal 1011a and the second pattern signal 1013a It may also be obtained by directly identifying the number of samplings in between. As shown in 1003 of FIG. 10B, the analysis device 250 calculates the sampling frequency of the remaining sensing data (eg, the second sensing data 1000b and the third sensing data 1000c) (eg, 1/T1, 1/T2). When the calculated sampling frequency and the reference sampling frequency are different, the analysis device 250 adjusts the calculated sampling frequency to correspond to the reference sampling frequency (or the calculated sampling time, as shown in 1004 of FIG. 10B). (e.g. 1/T1', 1/T2') can be adjusted to correspond to the standard sampling time. According to the adjustment, the first pattern signal (eg, the first sensing data 1000a) and the remaining sensing data (eg, the second sensing data 1000b and the third sensing data 1000c) Time lengths between 1011b and 1011c and the second pattern signals 1013b and 1013c may correspond to each other (eg, the same) (eg, |t4-t1|). As an example, the analysis device 250, as shown in FIG. 11 , determines the length of time between a signal 1111 representing a specific pattern of the sensing data 1101 representing an electrocardiogram signal and a signal 1113 representing another pattern, and The sampling rate of the sensing data 1103 representing the photovenous wave is adjusted such that the length of time between the signal 1131 representing the same pattern and the signal 1133 representing the different pattern of the sensing data 1103 representing the photovenous wave are the same. can Accordingly, the analysis device 250 provides data (or signal) 1115 having a specific peak value of the sensing data 1101 representing the electrocardiogram signal and data having a specific peak value of the sensing data 1103 representing the photovenous wave. (or signal) 1135 can be compared and analyzed. Meanwhile, between the pattern signals (eg, between the first pattern signals 1011a, 1011b, and 1011c and the second pattern signals 1013a, 1013b, and 1013c) The line (|) in denotes data obtained according to a specific sampling frequency, and the number of data is reduced for convenience of description, but it is obvious to those skilled in the art that more data can be obtained without being limited to what is shown. can do.

According to various embodiments, an electronic device (eg, the analysis device 250) includes reference sensing data (eg, first sensing data 1000a) and remaining sensing data (eg, second to third sensing data (eg, second to third sensing data (eg, first sensing data 1000a)). 1000b, 1000c), comparing time lengths between signals having patterns (eg, first pattern signals 1011a, 1011b, 1011c and second pattern signals 1013a, 1013b, 1013c), and In this case, the sampling frequency (or sampling time interval) of the remaining sensing data may be continuously adjusted. For example, the analysis device 250 increases the sampling frequency (or decreases the sampling time) of the corresponding sensing data when the time length is longer than that of the reference sensing data, and increases the time length of the reference sensing data. When the time length is shorter, the sampling frequency of the corresponding sensing data may be reduced (or the sampling time may be increased). When the length of time corresponds, the analysis device 250 may complete (or refrain from) the operation of adjusting the sampling frequency.

According to various embodiments, an electronic device (eg, analysis device 250) among a plurality of sensing data (eg, first to third sensing data 1000a, 1000b, and 1000c) as shown in FIG. 10B. Signals (eg, first pattern signals 1011a, 1011b, 1011c) and second pattern signals 1013a, 1013b, As the sampling frequency (or sampling time) between 1013c) is adjusted, the time points of the pattern signals (eg, the third pattern signals 1015a, 1015b, and 1015c) after the specific time period 1031 are also aligned with each other (eg, : viewpoints can correspond to each other). Meanwhile, the viewpoints of the pattern signals (eg, the third pattern signals 1015a, 1015b, and 1015c) after the specific time period 1031 may not be aligned (eg, a specific time period) without being limited to what is shown and/or described. due to changes in the sampling frequency since the liver). On the other hand, without being limited to what is shown and/or described, the electronic device (eg, the analysis device 250) includes a plurality of sensing data (eg, first to third sensing data 1000a) included in a specific time period 1031. , 1000b, 1000c)) may be acquired, and the sampling frequency (or sampling time) of the obtained partial data may be adjusted.

Hereinafter, an example of operations of the signal applying device 210 , the sensing device 230 , and the analyzing device 250 according to various embodiments will be described. Hereinafter, for convenience of explanation, the signal applying device 210 and the sensing device 230 described in FIG. 2A are separately implemented, and one sensing device 230 among the sensing devices 230 is selected as the analysis device 250. However, unless otherwise noted, examples described below are examples in which the analysis device 250 described in FIG. 2B is separately implemented or the signal applying device 210 in the sensing device 230 described in FIG. 2C. ) may also be applied to an example in which ) is implemented, so redundant descriptions are omitted.

According to various embodiments, the analysis device 250 filters only sensing data including signals having the same pattern within a specified time period among a plurality of collected sensing data to synchronize the time of the filtered sensing data. action can be performed.

12 is a flowchart 1200 for explaining an example of an operation of the electronic device 101 according to various embodiments. The operations shown in FIG. 12 are not limited to the order shown and may be performed in various orders. Also, according to various embodiments, more operations than the operations shown in FIG. 12 or at least one operation less may be performed. Hereinafter, FIG. 12 will be described with reference to FIG. 13 .

13 is a diagram for explaining an example of an operation of filtering a plurality of sensed data of an electronic device according to various embodiments.

According to various embodiments, the analysis device 250 may acquire a plurality of sensing data in operation 1201 . For example, the analysis device 250, as shown in 1301 of FIG. 13 , uses a sensor and/or a communication circuit to collect a plurality of sensing data (eg, first sensing data (eg, first sensing data ( 1300a), second sensing data 1300b, and third sensing data 1300c) may be obtained. An operation of acquiring a plurality of sensed data by the analysis device 250 may be performed in the same manner as operation 901 of the analysis device 250 described above, and thus duplicate descriptions are omitted. For example, the sensing device 230 that operates as the analysis device 250 or the separately implemented analysis device 250 may obtain sensing data from all of the sensing devices 230 communicatively connected to each other.

According to various embodiments, the analysis device 250 may select only sensing data having the same pattern from among a plurality of sensing data in operation 1203 . For example, referring to 1301 of FIG. 13 , the analysis device 250 includes a plurality of sensing data (eg, first sensing data 1300a, second sensing data 1300b, and third sensing data 1300c). At least one signal (1311, 1313, 1315, 1321, 1323) having a pattern included in each may be detected. In an embodiment, referring to 1302 of FIG. 13 , the analysis device 250 includes a plurality of sensing data (eg, first sensing data 1300a, second sensing data 1300b, and third sensing data 1300c). ) By comparing the detected signals 1311, 1313, and 1321, some sensing data having signals 1311 and 1313 corresponding to each other within a designated time window (eg, first sensing data ( 1300a) and second sensing data 1300b) may be selected. In another embodiment, the analysis device 250 may set a threshold value (eg, first sensing data 1300a, second sensing data 1300b, and third sensing data 1300c) among a plurality of sensing data (eg, first sensing data 1300a, second sensing data 1300b, and third sensing data 1300c). : Some sensing data (eg, first sensing data 1300a, second sensing data 1300b) having the same pattern signals 1311 and 1313 as many as two) may be selected.

According to various embodiments, the analysis device 250 may perform time synchronization of the selected sensing data in operation 1205 and analyze the time synchronized sensing data. For example, the processing of the plurality of sensing data (eg, the first sensing data 1300a and the second sensing data 1300b) may include adjusting and aligning the viewpoints of pattern signals included in the sensing data; and /or an operation of processing time lengths between pattern signals to correspond to each other by adjusting a sampling frequency (or sampling time) between pattern signals included in the sensing data. An operation of processing the sensing data among operations 1205 of the analysis device 250 may be performed in the same manner as operations 903 to 911 of FIG. 9 of the analysis device 250 described above, and thus duplicate descriptions are omitted.

Hereinafter, an example of operations of the signal applying device 210 , the sensing device 230 , and the analyzing device 250 according to various embodiments will be described. Hereinafter, an example in which the signal applying device 210 is implemented in the sensing device 230 described in FIG. 2C will be described. Unless otherwise noted, examples described below may also be applied to the foregoing embodiments, and thus redundant descriptions are omitted.

According to various embodiments, in response to the occurrence of a designated event, a signal generating device included in each of the sensing devices 230 may apply a physical signal having a pattern to the sensor.

14 is a flowchart 1400 for explaining an example of an operation of electronic devices (eg, a signal application device, a sensing device, and an analysis device) according to various embodiments. The operations shown in FIG. 14 are not limited to the order shown and may be performed in various orders. Also, according to various embodiments, more operations than the operations shown in FIG. 14 or at least one operation less may be performed. Hereinafter, FIG. 14 will be described with reference to FIG. 15 .

15 is a diagram for explaining an example of an operation of a signal generating device included in each of the sensing devices 230 according to various embodiments.

According to various embodiments, one sensing device 230 (eg, the first sensing device 1400a) identifies an event for signal generation in operation 1401 and another sensing device 230 (eg, the second sensing device 230 (eg, the second sensing device 1400a) in operation 1403. The sensing device 1400b may be requested to generate signals 1511 and 1531 having patterns. For example, when identifying the occurrence of an event for bio-signal analysis, the first sensing device 1400a generates a message (or instructions) for requesting generation of a signal having a pattern, and transmits the generated message to other sensing devices. A message may be sent to device 230 . In one embodiment, the operation of identifying the occurrence of the event may include identifying the occurrence of an event for bio-signal analysis in operation 613 of the sensing device 230 described above, and duplicate descriptions are omitted. In another embodiment, the operation of identifying the occurrence of the event is receiving a preset input for generating a pattern signal (eg, receiving a gesture input for generating a pattern signal, an application (or program) for biometric analysis) Receiving an input for selecting a menu for pattern signal generation implemented in). The message may include at least one of information about a specific pattern to be generated together with information (eg, instructions) that causes a signal having a pattern to be output, or information about a time point of outputting a signal. Based on the occurrence of the event, the sensing device 230 selects a specific pattern (eg, randomly or sequentially) based on information on a plurality of patterns stored in the sensing device 230, and selects the specific pattern. A message containing information about the pattern can be created. Meanwhile, the analysis device 250 implemented separately from the sensing devices 230 is not limited to what is described and/or illustrated, and the sensing devices 230 (eg, the first sensing device 1400a and the second sensing device ( Generation of a signal having a pattern may be requested in step 1400b)).

According to various embodiments, one sensing device 230 (eg, the first sensing device 1400a) may generate a first signal having a specified pattern in operation 1405 and obtain sensing data in operation 1407. Another sensing device 230 (eg, the second sensing device 1400b) may also generate a first signal having a designated pattern in operation 1409 and obtain sensing data in operation 1411 . For example, the first sensing device 1400a and the second sensing device 1400b identify information about a specific pattern included in the message, and as shown in FIG. 15 , a specific kind of physical Signal generating devices (eg, the light generating device 1501 and the electrical signal generating device 1503) may be controlled to simultaneously output the signals 1511 and 1531. In one embodiment, the first sensing device 1400a and the second sensing device 1400b are a signal generating device (eg, a light generating device (e.g., a light generating device) at a specific point in time based on the information on the time point of outputting the signal included in the message. 1501) and the electrical signal generator 1503), the physical signals 1511 and 1513 may be simultaneously output. In another embodiment, the first sensing device 1400a outputs the physical signal 1511 after a specified time (eg, a delay time for message transmission and processing) after transmitting the message, and the second sensing device 1400b ) may output a physical signal 1513 in response to receiving the message. Each of the sensing devices 230 (eg, the first sensing device 1400a and the second sensing device 1400b) is applied to the sensor (eg, the optical sensor 1513 and the electrodes 1533a to 1533b). After acquiring the sensing data for the physical signals 1511 and 1531, the biosignal of the user W1 is continuously measured using each sensor (eg, the optical sensor 1513 and the electrodes 1533a to 1533b). Indicative sensing data may be obtained.

Meanwhile, the signal generating device included in each of the sensing devices 230 may periodically generate and output a signal without performing an operation of identifying and requesting the occurrence of an event without being limited to what has been described and/or shown. have.

According to various embodiments, one sensing device 230 (eg, the first sensing device 1400a) identifies the occurrence of an event for analyzing the sensing data in operation 1413, identifies a device to request sensing data in operation 1415, and In operation 1417, sensing data may be requested from the identified device (eg, the second sensing device 1400b), and sensing data may be received from the device identified in operation 1419 (eg, the second sensing device 1400b). . For example, the first sensing device 1400a may identify occurrence of an event for bio-signal analysis, and request sensing data from at least some devices among devices established for communication connection based on the occurrence of the identified event. Since operations 1413 to 1419 of the first sensing device 1400a may be performed in the same manner as operations 613 to 619 of the first sensing device 1400a, overlapping descriptions are omitted. Meanwhile, not limited to what has been described and/or shown, a device that performs an operation as the analysis device 250 without performing an operation of identifying the occurrence of an event and an operation of requesting sensing data from the sensing devices 230 (eg, : The first sensing device 1400a or a separately implemented analysis device 250 (eg, the smart phone 1500) automatically periodically or aperiodically receives sensing data from the communicatively connected sensing devices 230. may be

According to various embodiments, one sensing device 230 (eg, the first sensing device 1400a) performs an operation of synchronizing the times of a plurality of sensing data based on a signal having a designated pattern in operation 1421, In operation 1423, a plurality of time-synchronized sensing data may be analyzed. For example, the first sensing device 1400a may analyze a biosignal by comparing data representing a biosignal among pattern signals of a plurality of sensing data included in a specific time period. For example, the first sensing device 1400a identifies a value of the second sensing data at a time point of data having a specific peak value detected in the first sensing data, and determines the state of the user W1 based on the values. Diagnosis or correlation between two bio-signals represented by each sensing data may be analyzed.

According to various embodiments, in an electronic device (eg, the first sensing device 230a of FIG. 3 ), a sensor (eg, the sensor 360 of FIG. 3 ); communication circuitry (eg, second communication circuitry 380 in FIG. 3 ); a memory (eg, the second memory 370 of FIG. 3); and at least one processor (eg, the processor 350 of FIG. 3); and, when instructions stored in the memory (eg, the second memory 370 of FIG. 3) are executed, the at least one processor (eg, the second memory 370 of FIG. 3) is executed. : Processor 350 of FIG. 3 : first sensing using the sensor (eg, sensor 360 of FIG. 3 ) and/or the communication circuit (eg, second communication circuit 380 of FIG. 3 ) Obtaining data and at least one sensing data, identifying a first signal having a first pattern included in each of the first sensing data and the at least one sensing data, and performing the first signal included in the first sensing data. The first sensing data and the at least one sensing data are aligned so that a time point of a signal corresponds to a time point of the first signal included in the at least one sensing data, and the aligned first sensing data and the at least one sensing data are aligned. Identifying a second signal having a second pattern included in each of the sensing data of and included in the first time length between the first signal and the second signal included in the first sensing data and the at least one sensing data An electronic device (eg: The first sensing device 230a of FIG. 3 may be provided.

According to various embodiments, the first sensing data is obtained by a first sensor, the second sensing data is obtained by a second sensor different from the first sensor, and the first sensing data is obtained by a second sensor. The first signal and the second signal are generated by a first type of physical signal applied to the first sensor, and the first signal and the second signal of the second sensing data are applied to the second sensor. An electronic device (eg, the first sensing device 230a of FIG. 3 ) generated by a physical signal of a second type different from the first type may be provided.

According to various embodiments, the first pattern represents at least one of a magnitude of a value of the first signal, a first period in which the value of the first signal is repeated, or a change in the value of the first signal. , The second pattern represents at least one of the magnitude of the value of the second signal, a second period in which the value of the second signal is repeated, or a change in the value of the second signal, an electronic device (eg: The first sensing device 230a of FIG. 3 may be provided.

According to various embodiments, the first signal having the first pattern includes a signal in the form of a first square wave, and the second signal having the second pattern includes a signal in the form of a second square wave, an electronic device ( Example: The first sensing device 230a of FIG. 3 may be provided.

According to various embodiments, the instructions may cause the at least one processor (eg, the processor 350 of FIG. 3 ) to compare the at least one data among the first sensing data and the at least one sensing data. An electronic device (eg, the first sensing device 230a of FIG. 3 ) may be provided to identify the first sensing data as reference data.

According to various embodiments, based on accuracy of each of the first sensing data and the at least one sensing data, the first sensing data is identified, and the accuracy of the first sensing data is determined by the at least one sensing data An electronic device (eg, the first sensing device 230a of FIG. 3 ) may be provided with higher accuracy than .

According to various embodiments, the instructions include the at least one processor (eg, the processor 350 of FIG. 3): identifying a plurality of signals each having a pattern included in a specific time period of the first sensing data; , An electronic device (e.g., in FIG. 3 A first sensing device 230a may be provided.

According to various embodiments, the instructions may cause the at least one processor (eg, the processor 350 of FIG. 3 ) to: generate the identified plurality of signals based on the time points associated with the identified plurality of signals. An electronic device (eg, the first sensing device 230a of FIG. 3 ) may be provided to identify the first signal associated with the earliest first point in time.

According to various embodiments, the instructions may cause the at least one processor (eg, the processor 350 of FIG. 3 ) to: determine a second time point of the first signal included in the specific time period of the at least one sensing data. Identifying, and when the first time point and the second time point are different, calculating a difference between the first time point and the second time point, and changing the points of view of the at least one sensing data by the calculated difference, A device (eg, the first sensing device 230a of FIG. 3 ) may be provided.

According to various embodiments, the instructions may cause the at least one processor (eg, the processor 350 of FIG. 3 ) to: among the plurality of signals included in the specific time period of the first sensing data, the first identify the second signal as different from the signal and, based on the first length of time between the first signal and the second signal, a second signal associated with the first sensed data between the first signal and the second signal; An electronic device (eg, the first sensing device 230a of FIG. 3 ) may be provided to calculate 1 sampling rate.

According to various embodiments, the instructions may cause the at least one processor (eg, the processor 350 of FIG. 3 ) to: identify the second signal that is the latest signal among the plurality of signals, the electronic device ( Example: The first sensing device 230a of FIG. 3 may be provided.

According to various embodiments, the instructions may cause the at least one processor (eg, the processor 350 of FIG. 3 ) to: identify the second signal included in the specific time period of the at least one sensed data; Based on the second length of time between the first signal and the second signal of the at least one sensing data, the at least one sensing data between the first signal and the second signal of the at least one sensing data Calculate a second sampling rate associated with, and when the second sampling rate is different from the first sampling rate, calculate a difference between the first sampling rate and the second sampling rate, and calculate the second sampling rate by the calculated difference. An electronic device (eg, the first sensing device 230a of FIG. 3 ) that changes the sampling rate may be provided.

According to various embodiments, in a method of operating an electronic device (eg, the first sensing device 230a of FIG. 3 ), the sensor (eg, the sensor 360 of FIG. 3 ) and/or the communication circuit (eg, the first sensing device 230a of FIG. 3 ) : Obtaining first sensing data and at least one sensing data using the second communication circuit 380 of FIG. 3 ); identifying a first signal having a first pattern included in each of the first sensing data and the at least one sensing data; arranging the first sensing data and the at least one sensing data such that a time point of the first signal included in the first sensing data corresponds to a time point of the first signal included in the at least one sensing data; identifying a second signal having a second pattern included in each of the aligned first sensing data and the at least one sensing data; and a first time length between the first signal and the second signal included in the first sensing data and a second time length between the first signal and the second signal included in the at least one sensing data. Correspondingly, an operation of performing an operation of processing at least a portion of the first sensing data and the at least one sensing data; including, an operation method may be provided.

According to various embodiments, the first sensing data is obtained by a first sensor, the second sensing data is obtained by a second sensor different from the first sensor, and the third sensing data of the first sensing data is obtained. The first signal and the second signal are generated by a first type of physical signal applied to the first sensor, and the first signal and the second signal of the second sensing data are applied to the second sensor. A method of operation, generated by a physical signal of a second kind different from the first kind, may be provided.

According to various embodiments, the first pattern represents at least one of a magnitude of a value of the first signal, a first period in which the value of the first signal is repeated, or a change in the value of the first signal. , The second pattern represents at least one of a magnitude of the value of the second signal, a second period in which the value of the second signal is repeated, or a change in the value of the second signal. can

According to various embodiments, a first signal having the first pattern includes a first square wave signal, and a second signal having the second pattern includes a second square wave signal. can be provided.

According to various embodiments, an operation of identifying the first sensing data as reference data to be compared with the at least one data from among the first sensing data and the at least one sensing data; including, an operating method this can be provided.

According to various embodiments, based on accuracy of each of the first sensing data and the at least one sensing data, the first sensing data is identified, and the accuracy of the first sensing data is determined by the at least one sensing data Higher than the accuracy of , an operating method can be provided.

According to various embodiments, an operation of identifying a plurality of signals each having a pattern included in a specific time period of the first sensing data; identifying the first signal from among the identified plurality of signals based on time points of the identified plurality of signals; And an operation of identifying a first time point of the first signal; including, an operating method may be provided.

According to various embodiments, in an electronic device (eg, the signal applying device 210 of FIG. 3 ), a first signal output device (eg, the first generating device 321 of FIG. 3 ); a second signal output device (e.g., the second generating device 323 in FIG. 3); a memory (eg, the first memory 330 of FIG. 3); and at least one processor (eg, the processor 310 of FIG. 3); and, when instructions stored in the memory (eg, the first memory 330 of FIG. 3) are executed, the at least one processor (eg, the first memory 330 of FIG. 3) is executed. : The processor 310 of FIG. 3): identifies the occurrence of an event for generating a signal, and based on the occurrence of the event, at a first point in time, a first signal having a first pattern using the first signal output device output a first signal of a kind, and cause the second signal output device to output a second signal of a second kind having the first pattern, wherein the first pattern is the value of the first signal and the second signal An electronic device (e.g., FIG. A signal applying device 210 of may be provided.

Claims (20)

In electronic devices,
sensor;
communication circuit;
Memory; and
at least one processor; wherein, when the instructions stored in the memory are executed, the at least one processor:
obtaining first sensing data and at least one sensing data using the sensor and/or the communication circuit;
Identifying a first signal having a first pattern included in each of the first sensing data and the at least one sensing data;
Aligning the first sensing data and the at least one sensing data so that a time point of the first signal included in the first sensing data corresponds to a time point of the first signal included in the at least one sensing data,
Identifying a second signal having a second pattern included in each of the aligned first sensing data and the at least one sensing data;
A first length of time between the first signal and the second signal included in the first sensing data and a second length of time between the first signal and the second signal included in the at least one sensing data correspond to each other. To perform an operation of processing at least some of the first sensing data and the at least one sensing data,
electronic device.
According to claim 1,
The first sensing data is obtained by a first sensor, the second sensing data is obtained by a second sensor different from the first sensor,
The first signal and the second signal of the first sensing data are generated by a first type of physical signal applied to the first sensor, and the first signal and the second signal of the second sensing data are Generated by a physical signal of a second type different from the first type applied to the second sensor,
electronic device.
According to claim 2,
The first pattern represents at least one of a magnitude of a value of the first signal, a first period in which the value of the first signal is repeated, or a change in the value of the first signal, and the second pattern represents the Indicating at least one of a magnitude of the value of the second signal, a second period at which the value of the second signal is repeated, or a change in the value of the second signal,
electronic device.
According to claim 3,
The first signal having the first pattern includes a signal in the form of a first square wave, and the second signal having the second pattern includes a signal in the form of a second square wave.
electronic device.
According to claim 1,
The instructions cause the at least one processor to:
Among the first sensing data and the at least one sensing data, to identify the first sensing data as reference data to be compared with the at least one data,
electronic device.
According to claim 5,
Based on the accuracy of each of the first sensing data and the at least one sensing data, to identify the first sensing data, wherein the accuracy of the first sensing data is higher than the accuracy of the at least one sensing data,
electronic device.
According to claim 5,
The instructions cause the at least one processor to:
Identifying a plurality of signals each having a pattern included in a specific time period of the first sensing data,
Based on the time points of the identified plurality of signals, identifying the first signal among the identified plurality of signals;
To identify a first time point of the first signal,
electronic device.
According to claim 7,
The instructions cause the at least one processor to:
Identifying the first signal associated with the earliest first time point among the identified plurality of signals based on the time points associated with the identified plurality of signals,
electronic device.
According to claim 7,
The instructions cause the at least one processor to:
Identifying a second time point of the first signal included in the specific time period of the at least one sensing data;
When the first time point and the second time point are different, calculating a difference between the first time point and the second time point;
To change the viewpoints of the at least one sensing data by the calculated difference,
electronic device.
According to claim 7,
The instructions cause the at least one processor to:
Identifying the second signal different from the first signal among the plurality of signals included in the specific time period of the first sensing data;
calculate a first sampling rate associated with the first sensed data between the first signal and the second signal based on the first length of time between the first signal and the second signal;
electronic device.
According to claim 10,
The instructions cause the at least one processor to:
To identify the second signal, which is the latest signal among the plurality of signals,
electronic device.
According to claim 10,
The instructions cause the at least one processor to:
Identifying the second signal included in the specific time period of the at least one sensing data,
Based on the second length of time between the first signal and the second signal of the at least one sensing data, the at least one sensing between the first signal and the second signal of the at least one sensing data calculate a second sampling rate associated with the data;
When the second sampling rate is different from the first sampling rate, calculating a difference between the first sampling rate and the second sampling rate;
To change the second sampling rate by the calculated difference,
electronic device.
In the method of operating an electronic device,
obtaining first sensing data and at least one sensing data by using a sensor and/or a communication circuit of the electronic device;
identifying a first signal having a first pattern included in each of the first sensing data and the at least one sensing data;
arranging the first sensing data and the at least one sensing data such that a time point of the first signal included in the first sensing data corresponds to a time point of the first signal included in the at least one sensing data;
identifying a second signal having a second pattern included in each of the aligned first sensing data and the at least one sensing data; and
A first length of time between the first signal and the second signal included in the first sensing data and a second length of time between the first signal and the second signal included in the at least one sensing data correspond to each other. Including,
how it works.
According to claim 13,
The first sensing data is obtained by a first sensor, the second sensing data is obtained by a second sensor different from the first sensor,
The first signal and the second signal of the first sensing data are generated by a first type of physical signal applied to the first sensor, and the first signal and the second signal of the second sensing data are Generated by a physical signal of a second type different from the first type applied to the second sensor,
how it works.
15. The method of claim 14,
The first pattern represents at least one of a magnitude of the value of the first signal, a first period in which the value of the first signal is repeated, or a change in the value of the first signal, and the second pattern represents the Indicating at least one of a magnitude of the value of the second signal, a second period in which the value of the second signal is repeated, or a change in the value of the second signal,
how it works.
According to claim 15,
The first signal having the first pattern includes a signal in the form of a first square wave, and the second signal having the second pattern includes a signal in the form of a second square wave.
how it works.
According to claim 13,
Among the first sensing data and the at least one sensing data, identifying the first sensing data as reference data to be compared with the at least one data; including,
how it works.
18. The method of claim 17,
Based on the accuracy of each of the first sensing data and the at least one sensing data, to identify the first sensing data, wherein the accuracy of the first sensing data is higher than the accuracy of the at least one sensing data,
how it works.
18. The method of claim 17,
identifying a plurality of signals each having a pattern included in a specific time period of the first sensing data;
identifying the first signal from among the identified plurality of signals based on time points of the identified plurality of signals; and
Including, an operation of identifying a first time point of the first signal;
how it works.
In electronic devices,
a first signal output device;
a second signal output device;
Memory; and
at least one processor; wherein, when the instructions stored in the memory are executed, the at least one processor:
identify the occurrence of an event for generating a signal;
Based on the occurrence of the event, a first type of first signal having a first pattern is output using the first signal output device at a first time point, and the second signal output device having the first pattern is output. A second signal of a second type is output, and the first pattern includes values of the first signal and the second signal, a first period in which the values of the first signal and the second signal are repeated, or indicative of at least one of a change in the value of the first signal and the second signal.
electronic device.

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