Method and device for analyzing abnormality of user state on basis of smart all-in-one heart patch

Abstract

According to an embodiment of the present specification, a method for providing, by a user device, user analysis information on the basis of a smart all-in-one heart patch may comprise the steps of: receiving a heart-related signal acquired from the smart all-in-one heart patch; providing the heart-related signal as an input to a state monitoring learning model; automatically detecting whether a user has an abnormality on the basis of inference of the state monitoring learning model; and performing analysis of user information on the basis of the detection of whether the user has an abnormality and displaying the analyzed user information.

Description

Method and device for analyzing user condition abnormalities based on a smart all-in-one heart patch

[0001] The present invention relates to a method and device for analyzing user condition abnormalities based on a smart all-in-one cardiac patch. More specifically, the present invention relates to a method for monitoring and managing user condition using a smart all-in-one cardiac patch device attachable to the human body.

[0002]

[0003] Existing systems measure heartbeats and analyze the signals generated by these heartbeats to identify abnormalities or illnesses in users. However, because these systems analyze these signals through specific devices provided by medical institutions, users had to visit a medical institution and use the device to measure their heartbeats to check for abnormalities or illnesses.

[0004] However, heartbeats can fluctuate depending on various factors, such as the user's physical or psychological state. Therefore, short-term heartbeat signals measured by medical institutions may have limitations in identifying abnormalities or diseases. Considering the above, the following describes a method and device that is attached to the human body to measure and transmit heartbeat signals in real time, enabling real-time monitoring and confirming the user's condition based on this data.

[0005]

[0006] The present specification relates to a method and device for analyzing a user's abnormal condition based on a smart all-in-one heart patch.

[0007] The present specification relates to a method and device for building an artificial intelligence (AI) / machine learning (ML) learning model based on heart-related information for multiple users acquired based on a smart all-in-one heart patch.

[0008] This specification relates to a smart all-in-one cardiac patch system and its operating method.

[0009] The present specification relates to a method and device for monitoring signals generated from the heart in real time based on a smart all-in-one cardiac patch device to provide information on whether a user's condition is abnormal.

[0010]

[0011] According to one embodiment of the present specification, a method for a user device to provide user analysis information based on a smart all-in-one heart patch may include: receiving a heart-related signal acquired from the smart all-in-one heart patch; providing the heart-related signal as an input to a condition monitoring learning model; automatically detecting whether a user is abnormal based on inference of the condition monitoring learning model; performing user information analysis based on the detection of whether the user is abnormal; and displaying the analyzed user information.

[0012] Additionally, according to one embodiment of the present specification, the condition monitoring learning model is obtained from the cloud, and the cloud can receive heart-related signals of a smart all-in-one heart patch connected to each of the plurality of user devices from a plurality of user devices, and update the condition monitoring learning model based on the plurality of heart-related signals.

[0013] Additionally, according to one embodiment of the present specification, the cloud acquires multiple heart-related signals in real time, acquires more heart-related raw data based on batch load, and the multiple heart-related signals acquired in real time and the heart-related raw data acquired based on batch load can be processed in parallel and reflected in a condition monitoring learning model.

[0014] In addition, according to one embodiment of the present disclosure, the smart all-in-one heart patch acquires a heart-related signal based on user identification information and transmits the acquired signal to a user device, and the user device records the heart-related signal acquired from the smart all-in-one heart patch together with a session key, a medium access control (MAC) address-based identifier of the user device, and a unique time based on the user identification information, and transmits heart-related information to the cloud based on the recording, wherein the heart-related information can be transmitted to the cloud together with a signal type, a data access time, and a data change time based on the user identification information.

[0015] Additionally, according to one embodiment of the present specification, the cloud can derive record information excluding user identification information from information obtained from a user device, and encode the record information with a hexadecimal key and provide it as learning material for a state monitoring learning model based on administrator authority.

[0016] Additionally, according to one embodiment of the present specification, the smart all-in-one cardiac patch can sense and transmit to a user device at least one of an electrocardiogram (ECG), which is an electrical signal related to a heartbeat, a seismocardiogram (SCG), which is a low-frequency vibration signal, and a phonocardiogram (PCG), which is a cardiac sound wave signal.

[0017] Additionally, according to one embodiment of the present disclosure, the user device may obtain additional information related to a heart-related signal and generate heart-related information based on the additional information.

[0018] Additionally, according to one embodiment of the present disclosure, the user device may display analyzed user information based on an interface including user-related information and analysis information.

[0019]

[0020] The present specification has the effect of providing a method for analyzing a user's abnormal condition based on a smart all-in-one heart patch.

[0021] The present specification has the effect of providing a method for building an artificial intelligence (AI) / machine learning (ML) learning model based on heart-related information for multiple users acquired based on a smart all-in-one heart patch.

[0022] The present specification has the effect of providing a smart all-in-one cardiac patch system and an operating method thereof.

[0023] The present specification has the effect of monitoring signals generated from the heart in real time based on a smart all-in-one cardiac patch device to provide information on whether the user's condition is abnormal.

[0024] The problem to be solved by this specification is not limited to what has been described above, and can be expanded to various matters that can be derived from the embodiments of the invention described below.

[0025]

[0026] FIG. 1 is a diagram illustrating an example of an operating environment of a system according to one embodiment of the present specification.

[0027] FIG. 2 is a block diagram for explaining the internal configuration of a computing device (200) in one embodiment of the present specification.

[0028] FIG. 3 is a diagram illustrating a smart all-in-one cardiac patch device and multiple user devices according to one embodiment of the present disclosure.

[0029] FIG. 4 is a diagram illustrating a smart all-in-one cardiac patch system according to one embodiment of the present disclosure.

[0030] FIG. 5 is a diagram illustrating a method for a user device to provide analysis information according to one embodiment of the present disclosure.

[0031] FIG. 6 is a diagram illustrating the structure of a smart all-in-one cardiac patch according to one embodiment of the present specification.

[0032] FIG. 7 is a drawing showing the internal structure of a smart all-in-one smart patch according to one embodiment of the present specification.

[0033] FIG. 8 is a diagram illustrating a method for detecting anomalies based on machine learning according to one embodiment of the present specification.

[0034] FIG. 9 is a diagram illustrating a method for analyzing a signal acquired based on user status information according to one embodiment of the present specification.

[0035] FIG. 10 is a diagram illustrating a method for learning a learning model based on a cloud according to one embodiment of the present specification.

[0036] FIG. 11 is a diagram illustrating a method for updating a state monitoring learning model according to one embodiment of the present specification.

[0037] FIG. 12 is a diagram illustrating a method for a user device to display heart-related information according to one embodiment of the present disclosure.

[0038] FIG. 13 is a diagram illustrating a smart all-in-one cardiac patch system according to one embodiment of the present disclosure.

[0039] FIG. 14 is a diagram illustrating a method for performing user information security operations according to one embodiment of the present specification.

[0040] FIG. 15 is a diagram illustrating a smart all-in-one cardiac patch method and device according to one embodiment of the present specification.

[0041] FIG. 16 is a diagram illustrating a method for providing heart-related information to a user according to one embodiment of the present invention.

[0042]

[0043] In describing the embodiments of this specification, if a detailed description of a known configuration or function is judged to obscure the gist of the embodiments of this specification, a detailed description thereof will be omitted. In addition, parts of the drawings that are not related to the description of the embodiments of this specification have been omitted, and similar parts have been designated with similar drawing reference numerals.

[0044] In the embodiments of this specification, when a component is said to be "connected," "coupled," or "connected" to another component, this may include not only a direct connection, but also an indirect connection in which another component exists in between. Furthermore, when a component is said to "include" or "have" another component, unless specifically stated otherwise, this does not exclude the other component, but rather means that the other component may be included.

[0045] In the embodiments of this specification, the terms first, second, etc. are used only for the purpose of distinguishing one component from another component, and do not limit the order or importance between components unless specifically stated otherwise. Therefore, within the scope of the embodiments of this specification, a first component in an embodiment may be referred to as a second component in another embodiment, and similarly, a second component in an embodiment may be referred to as a first component in another embodiment.

[0046] In the embodiments of this specification, distinct components are used to clearly illustrate their respective characteristics and do not necessarily imply separation. That is, multiple components may be integrated into a single hardware or software unit, or a single component may be distributed into multiple hardware or software units. Therefore, even if not specifically mentioned, such integrated or distributed embodiments are also included within the scope of the embodiments of this specification.

[0047] In this specification, the term "network" may encompass both wired and wireless networks. In this case, the term "network" may refer to a communications network that enables data exchange between devices, systems, and devices, and is not limited to a specific network.

[0048] Embodiments described herein may be entirely hardware, partially hardware and partially software, or entirely software. As used herein, "unit," "device," or "system" refers to a computer-related entity such as hardware, a combination of hardware and software, or software. For example, a unit, module, device, or system as used herein may be, but is not limited to, a running process, a processor, an object, an executable, a thread of execution, a program, and / or a computer. For example, both an application running on a computer and the computer itself may correspond to a unit, module, device, or system as used herein.

[0049] Additionally, in this specification, a device may be a mobile device such as a smartphone, tablet PC, wearable device, or HMD (Head Mounted Display), as well as a fixed device such as a PC or home appliance with display functions. Furthermore, as an example, a device may be an in-vehicle cluster or an IoT (Internet of Things) device. In other words, in this specification, a device may refer to any device capable of operating an application, and is not limited to a specific type. For convenience of explanation, the device on which an application operates is referred to as a device below.

[0050] In this specification, the network communication method is not limited, and connections between each component may not be made using the same network method. The network may include not only communication methods utilizing communication networks (e.g., mobile communication networks, wired Internet, wireless Internet, broadcasting networks, satellite networks, etc.), but also short-range wireless communication between devices. For example, the network may include all communication methods that enable objects to network with each other, and is not limited to wired communication, wireless communication, 3G, 4G, 5G, or other methods. For example, wired and / or networks include Local Area Network (LAN), Metropolitan Area Network (MAN), Global System for Mobile Network (GSM), Enhanced Data GSM Environment (EDGE), High Speed ​​Downlink Packet Access (HSDPA), Wideband Code Division Multiple Access (W-CDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Bluetooth, Zigbee, Wi-Fi, VoIP (Voice over Internet Protocol), LTE Advanced, IEEE802.16m, WirelessMAN-Advanced, HSPA+, 3GPP Long Term Evolution (LTE), Mobile WiMAX (IEEE 802.16e), UMB (formerly EV-DO Rev. C), Flash-OFDM, iBurst and MBWA (IEEE 802.20) It may refer to a communication network using one or more communication methods selected from the group consisting of systems, HIPERMAN, Beam-Division Multiple Access (BDMA), Wi-MAX (World Interoperability for Microwave Access), and ultrasonic communication, but is not limited thereto.

[0051] The components described in various embodiments are not necessarily essential components, and some may be optional. Therefore, embodiments comprising a subset of the components described in the embodiments are also included within the scope of the embodiments of the present disclosure. Furthermore, embodiments including other components in addition to the components described in various embodiments are also included within the scope of the embodiments of the present disclosure.

[0052] Hereinafter, embodiments of the present specification will be described in detail with reference to the drawings.

[0053] FIG. 1 is a diagram illustrating an example of the operating environment of a system according to one embodiment of the present specification. Referring to FIG. 1, one or more user devices (110-1, 110-2) and one or more servers (120, 130, 140) are connected via a network (1). FIG. 1 is merely an example for explaining the invention, and the number of user devices or servers is not limited to that shown in FIG. 1.

[0054] One or more user devices (110-1, 110-2) may be fixed or mobile terminals implemented as a computer system. The one or more user devices (110-1, 110-2) may be, for example, a smart phone, a mobile phone, a navigation device, a computer, a laptop, a digital broadcasting terminal, a PDA (Personal Digital Assistants), a PMP (Portable Multimedia Player), a tablet PC, a game console, a wearable device, an IoT (Internet of Things) device, a VR (Virtual Reality) device, an AR (Augmented Reality) device, etc. For example, in the embodiments, the user device (110) may mean one of various physical computer systems that can communicate with other servers (120 to 140) through a network (1) using a wireless or wired communication method.

[0055] Each server may be implemented as a computer device or multiple computer devices that communicate with one or more user devices (110-1, 110-2) via a network (1) to provide commands, codes, files, contents, services, etc. For example, the server may be a system that provides each service to one or more user devices (110-1, 110-2) connected via the network (1). As a more specific example, the server may be a computer program that is installed and run on one or more user devices (110-1, 110-2), and may provide a service (e.g., provision of information, etc.) intended by the application to one or more user devices (110-1, 110-2). As another example, the server may distribute a file for installing and running the above-described application to one or more user devices (110-1, 110-2) and receive user input information to provide a corresponding service.

[0056] FIG. 2 is a block diagram illustrating the internal configuration of a computing device (200) according to one embodiment of the present specification. This computing device (200) may be applied to one or more user devices (110-1, 110-2) or servers (120-140) described above with reference to FIG. 1, and each device and server may have the same or similar internal configuration by adding or excluding some components.

[0057] Referring to FIG. 2, a computing device (200) may include a memory (210), a processor (220), a communication module (230), and a transceiver (240). The memory (210) is a non-transitory computer-readable recording medium and may include a non-permanent mass storage device such as a random access memory (RAM), a read only memory (ROM), a disk drive, a solid state drive (SSD), a flash memory, etc. Here, the non-permanent mass storage device such as a ROM, an SSD, a flash memory, a disk drive, etc. may be included in the above-described device or server as a separate permanent storage device distinct from the memory (210). In addition, the memory (210) may store an operating system and at least one program code (for example, a browser installed and operated on a user device (110), or a code for an application installed on a user device (110) to provide a specific service). These software components may be loaded from a computer-readable recording medium separate from the memory (210). This separate computer-readable recording medium may include a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD / CD-ROM drive, a memory card, etc.

[0058] In another embodiment, the software components may be loaded into the memory (210) via a communication module (230) rather than a computer-readable recording medium. For example, at least one program may be loaded into the memory (210) based on a computer program (e.g., the application described above) that is installed by files provided by developers or a file distribution system (e.g., the server described above) that distributes the installation files of the application via a network (1).

[0059] The processor (220) may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input / output operations. Instructions may be provided to the processor (220) by the memory (210) or the communication module (230). For example, the processor (220) may be configured to execute instructions received according to program code stored in a storage device such as the memory (210).

[0060] The communication module (230) can provide a function for the user device (110) and the server (120 - 140) to communicate with each other via the network (1), and can provide a function for each of the device (110) and / or the server (120 - 140) to communicate with other electronic devices.

[0061] The transceiver (240) may be a means for interfacing with an external input / output device (not shown). For example, external input devices may include devices such as a keyboard, mouse, microphone, camera, etc., and external output devices may include devices such as a display, speaker, haptic feedback device, etc. As another example, the transceiver (240) may be a means for interfacing with a device that integrates input and output functions, such as a touchscreen.

[0062] In addition, in other embodiments, the computing device (200) may include more components than the components of FIG. 2 depending on the nature of the device to which it is applied. For example, when the computing device (200) is applied to a user device (110), it may be implemented to include at least some of the above-described input / output devices, or may further include other components such as a transceiver, a Global Positioning System (GPS) module, a camera, various sensors, a database, etc. As a more specific example, when the user device is a smartphone, it may be implemented to further include various components that are generally included in a smartphone, such as an acceleration sensor or a gyro sensor, a camera module, various physical buttons, buttons using a touch panel, input / output ports, and a vibrator for vibration.

[0063]

[0064] For example, the smart all-in-one cardiac patch system described below may operate through the computing device (200) of FIG. 2 based on the network of FIG. 1. More specifically, the smart all-in-one cardiac patch system may include a smart all-in-one cardiac patch that acquires cardiac-related signals, a user device that acquires signals measured through the cardiac patch, and a smart all-in-one cardiac patch server that acquires and processes signals measured from a plurality of user devices. Here, each device may be a device that operates based on the computing device (200) of FIG. 2, but is not limited to the embodiment. In addition, each device may exchange signals based on the network of FIG. 1, but is not limited to the embodiment. For convenience of explanation, the following description will be based on the smart all-in-one cardiac patch, the user device, and the smart all-in-one cardiac patch server, but may not be limited to the names.

[0065] FIG. 3 is a diagram illustrating a smart all-in-one cardiac patch device and a plurality of user devices according to one embodiment of the present disclosure. Referring to FIG. 3, the smart all-in-one cardiac patch (310) can be attached to a human body. The smart all-in-one cardiac patch (310) can be attached to a human body to acquire cardiac-related signals. Here, the cardiac-related signals acquired by the smart all-in-one cardiac patch (310) can include at least one of an electrocardiogram (ECG), a seismocardiogram (SCG), and a phonocardiogram (PCG). Here, the ECG can be an electrical signal related to a heartbeat, the SCG can be a low-frequency vibration signal of the heart, and the PCG can be a cardiac sound wave. In other words, the smart all-in-one cardiac patch (310) can acquire at least one or more of an electrical signal, a vibration signal, and an acoustic signal related to a heartbeat.

[0066] Here, as an example, the smart all-in-one heart patch (310) can be attached to the heart location on the front of the human body to acquire heart-related signals. As another example, the smart all-in-one heart patch (310) can be attached to the heart location on the back of the human body to acquire heart-related signals. As another example, a plurality of smart all-in-one heart patches (310) can be attached to the human body. Specifically, the smart all-in-one heart patches (310) can be attached to both the heart locations on the front of the human body and the back of the human body. Here, heart-related signals can be acquired from each of the plurality of smart all-in-one heart patches (310) and compared, and heart-related signals can be acquired based on the compared signals, thereby increasing the accuracy of heart-related signal measurement. As another example, the smart all-in-one heart patch (310) can acquire additional information related to the heartbeat or the human body. As an example, the smart all-in-one heart patch (310) can further acquire information on the user's body temperature or the amount of moisture in the epidermis. The user's body temperature or skin moisture content may be information that can influence the acquisition of heart-related signals through the smart all-in-one heart patch (310), and the smart all-in-one heart patch (300) can further acquire such information. For example, in low temperatures such as winter, the user's body temperature may decrease, causing the heartbeat to slow down, and the smart all-in-one heart patch (310) can further acquire body temperature, external temperature, and other information.

[0067] As another example, the smart all-in-one heart patch (310) can acquire location information, environmental information, and other information. Specifically, the heart-related signal pattern of a user using the smart all-in-one heart patch (310) may differ depending on whether the user is indoors or outdoors. Alternatively, the heart-related signal may differ depending on whether the user is at home, where they feel mentally stable, or in an office space where they work. Here, the smart all-in-one heart patch (310) can measure the user's location information and transmit it to the user device. As another example, the smart all-in-one heart patch (310) can acquire information about the user's surroundings as environmental information. For example, the environmental information may be information that affects the heartbeat, such as temperature, humidity, airflow, and other information about the user's surroundings. In other words, the smart all-in-one heart patch (310) can acquire additional heartbeat-related information, but is not limited thereto.

[0068] Thereafter, the smart all-in-one heart patch (310) can transmit the acquired signal to the user device (410, 420, 430). For example, the user device (410, 420, 430) may be a smartphone (410), a tablet (420), a smart watch (430), or other devices used by a user who has the smart all-in-one heart patch (310) attached, and is not limited to a specific form. However, for the convenience of explanation, the following description will be based on the tablet (420) among the user devices, but may not be limited thereto. Thereafter, the user device (410, 420, 430) can perform monitoring based on the signal acquired from the smart all-in-one heart patch (310). In addition, the user device (410, 420, 430) can transmit the signal acquired from the smart all-in-one heart patch (310) to a server. As another example, the user device may be a device that operates within a preset distance from the smart all-in-one heart patch (310). As a specific example, the user device may be a smart watch (430). Here, the user device may obtain the above-described location information and environmental information within a preset distance from the smart all-in-one heart patch (310), and is not limited to the above-described embodiment. As an example, the smart watch (430) among the user devices may measure the above-described location information and environmental information within a preset distance from the smart all-in-one heart patch (310) and transmit the measured information to another user device (e.g., tablet, 420). That is, the tablet (420) may obtain a heart-related signal from the smart all-in-one heart patch (310) and obtain additional user-related information through the smart watch (430), but may not be limited to the above-described embodiment.

[0069] FIG. 4 is a diagram illustrating a smart all-in-one cardiac patch system according to one embodiment of the present disclosure. Referring to FIG. 4, the smart all-in-one cardiac patch system may include a smart all-in-one cardiac patch (310), a user device (420), and a cloud (or server, 500). In addition, the smart all-in-one cardiac patch system may further include other components and may not be limited to a specific form. Referring to FIG. 4(a), the user device (420) may obtain the above-described signals from the smart all-in-one cardiac patch (310). As an example, the signals may further include ECG, SCG, PCG, and other information, and are not limited to a specific embodiment. Here, as an example, the smart all-in-one cardiac patch (310) may be attached to a cardiac location on the front of the human body to obtain cardiac signals. As another example, the smart all-in-one cardiac patch (310) may be attached to a cardiac location on the back of the human body to obtain cardiac signals, as described above.

[0070] As another example, multiple smart all-in-one cardiac patches (310) can be attached to the human body. Specifically, the smart all-in-one cardiac patches (310) can be attached to both the front and back of the human body at the heart locations. Here, cardiac signals can be acquired and compared from each of the multiple smart all-in-one cardiac patches (310), and the cardiac signals can be acquired based on the compared signals, thereby increasing the accuracy of cardiac signal measurement.

[0071] In addition, the user device (420) may obtain additional information. For convenience of explanation, the user device (420) may refer to heart-related information including signals and additional information obtained from the smart all-in-one heart patch (310), but may not be limited thereto. When the user device (420) obtains heart-related information from the smart all-in-one heart patch (310), the user device (420) may display and provide the heart-related information to the user. In addition, as an example, the user device (420) may obtain heart-related information from the smart all-in-one heart patch (310) in real time or based on a preset cycle. The user device (420) may analyze and monitor at least one of user status information and disease information through the heart-related information obtained in real time or based on a preset cycle. Here, the user device (420) may display and provide the analysis information to the user. As an example, the user device (420) may provide the analysis information based on a preset cycle. As a specific example, the user device (420) may provide at least one of daily information, weekly information, monthly information, and long-term information, and is not limited to a specific form. That is, the user device (420) may obtain heart-related information from the smart all-in-one heart patch (310) in real time or based on a preset cycle, derive analysis information from the heart-related information, and provide the information to the user.

[0072] As another example, referring to FIG. 4(b), the user device (420) can transmit heart-related information acquired from the smart all-in-one heart patch (310) to the cloud (500). Here, the cloud (500) can acquire signals from each of the plurality of user devices (420) that acquire signals from the smart all-in-one heart patch (310), perform analysis, and transmit the analyzed information to the user device (420). As another example, the cloud (500) can perform learning on a condition monitoring learning model based on the heart-related information acquired from the plurality of user devices (420). Thereafter, the cloud (500) can transmit the learned condition monitoring learning model to each user device (420). Each user device (420) can provide the heart-related information acquired from the user as input to the condition monitoring learning model to perform inference, and automatically derive whether the user's condition is abnormal as an output value, which will be described later.

[0073] Also, as an example, FIG. 5 is a diagram illustrating a method for a user device (420) to provide analysis information according to an embodiment of the present disclosure. Referring to FIG. 5, the user device (420) may acquire a signal from a smart all-in-one cardiac patch (310) in real time or based on a preset cycle as described above, and perform analysis thereon. Thereafter, the user device (420) may generate and display the user report information of FIG. 5. As an example, the interface providing the user report information may include user-related information (611) and analysis information (612). As an example, the user-related information (611) may include the user's name, age, gender, height, weight, blood type, allergies, diseases, and other information about the user, and is not limited to a specific form. In addition, the user report information may further include analysis information (612) derived based on the heart-related information. For example, the analysis information (612) may include heart rate, oxygen saturation, body temperature, glucose level, and other information. In addition, the analysis information (612) may include test information performed based on heart-related information acquired from the smart all-in-one heart patch (310). Here, the test information may be information that analyzes and provides the acquired heart-related information for a specific purpose. As another example, the analysis information (612) may further include prescription information. The user device may analyze the heart-related information acquired from the smart all-in-one heart patch (310) based on the prescription information and generate and display corresponding information. That is, the user device (420) may derive user report information based on the heart-related information acquired from the smart all-in-one heart patch (310) and display the corresponding information.Through the above, the user can be aware of his / her condition and perform additional actions based on test information and prescription information.

[0074] FIG. 6 is a diagram illustrating the structure of a smart all-in-one cardiac patch according to one embodiment of the present disclosure. Referring to FIG. 6, the smart all-in-one cardiac patch may be either the first type (310) or the second type (320). In addition, the smart all-in-one cardiac patch may be of other types or shapes and is not limited to a specific shape. For example, referring to FIG. 6(a), the smart all-in-one cardiac patch may include silicone gel and silicone elastomer. The silicone gel is a deformable material that allows the smart all-in-one cardiac patch to adhere to the shape of the human body surface and not be detached. The silicone elastomer may be a material with excellent elasticity, absorbency, and tensile strength, and may allow the smart all-in-one cardiac patch to adhere to and remain on the human body. That is, the portion that adheres to the human body surface may be composed of silicone gel and silicone elastomer, thereby allowing the smart all-in-one cardiac patch to remain attached to the human body. Additionally, electrodes and a wireless charging coil may be included inside the silicone gel and silicone elastomer. Here, the electrodes may be ECG electrodes and may be gold electrodes made of gold, but are not limited thereto, and electrodes made of other materials may be configured. Additionally, the wireless charging coil may be configured to perform battery charging, and the smart all-in-one cardiac patch may be charged based on the same. Additionally, polyimide and copper traces may be included inside the silicone gel and silicone elastomer. Here, the polyimide may be a polymer material having thermal stability and high mechanical strength. For example, the first type (310) smart all-in-one cardiac patch may be configured in the same polyimide form.This allows the polyimide to be deformed together with the smart all-in-one heart patch when the smart all-in-one heart patch is stretched or bent when attached to the human body, and allows the smart all-in-one heart patch to remain attached without falling off from the human body.

[0075] Additionally, copper tracking can enable the smart all-in-one cardiac patch to track and transmit signals acquired through the high conductivity of copper. Furthermore, the smart all-in-one cardiac patch may further include components for acquiring signals and transmitting them to a user device, and a battery for operating the smart all-in-one cardiac patch. As an example, the components may include configurations for acquiring ECG as an electrical signal, SCG as a low-frequency vibration signal, and PCG as an acoustic signal, as described above, and are not limited to a specific form. Furthermore, as an example, the battery may serve to maintain power for transmitting the signals acquired by the smart all-in-one cardiac patch to the user device. As an example, the smart all-in-one cardiac patch is a low-power device and can be powered for a long period of time by the battery. As another example, the battery may be attached to the human body and charged according to the user's movements. As described above, the smart all-in-one cardiac patch is a low-power device and can operate through power charged according to the user's movements, but may not be limited to the above-described embodiment.

[0076] FIG. 7 is a diagram illustrating the internal structure of a smart all-in-one smart patch according to one embodiment of the present disclosure. Referring to FIG. 7, the smart all-in-one heart patch may include the polyimide described above. For example, FIG. 7 is described based on a first type smart all-in-one heart patch (310) for convenience of explanation, but may not be limited thereto. Referring to FIG. 7, the polyimide in the smart all-in-one heart patch (310) may include a component part (311) and a connecting part (312). Here, the component part (311) may be a region in the polyimide where the components described above are attached and positioned. For example, in FIG. 7(a) and FIG. 7(b), the component part (311) may be composed of a first component part (311-1) in a central region and a second component part (311-2) in a distal region, but may not be limited to the embodiment. In addition, each component (311) may be connected to each other through a connecting portion (312). Here, the above-described components may not be attached to the connecting portion (312). For example, the connecting portion (312) may be deformed according to the relaxation or contraction of the smart all-in-one cardiac patch (310). More specifically, the smart all-in-one cardiac patch (310) may be composed of the silicone gel as described above, and the silicone gel may be relaxed or contracted. For example, the connecting portion (312) may be relaxed or contracted together with the relaxation or contraction of the silicone gel. As a specific example, in FIG. 7(a), the connecting portion (312) may be relaxed up to a preset relaxation rate so that the smart all-in-one cardiac patch (310) may be relaxed. For example, the relaxation rate may be 20%, but this is only one example and is not limited to the embodiment.

[0077] Also, as an example, the connecting portion (312) can be deformed according to bending. More specifically, the smart all-in-one cardiac patch (310) can be composed of the silicone gel as described above, and the silicone gel can be bent. As an example, the connecting portion (312) can be bent together according to the bending of the silicone gel. As a specific example, in FIG. 7(b), the connecting portion (312) can be bent to a preset angle. Here, the preset bending angle can be 90 degrees, but this is only one example and is not limited to the embodiment. The smart all-in-one cardiac patch (310) can be attached to the human body based on the structure described above. As an example, the smart all-in-one cardiac patch (310) can be relaxed or contracted depending on the position to which it is attached, and a portion of it can be bent. That is, the shape of the smart all-in-one cardiac patch (310) can be partially deformed depending on the position to which it is attached to the human body, thereby increasing the strength of attachment to the human body. In addition, the first component (311-1) of the central region of the component (311) may include a component that receives a heart-related signal measured from a human body and transmits the signal to a user device externally. In addition, the second component (311-2) of the distal region may include sensors for directly measuring a heart-related signal from a human body, and the signals obtained from the sensors may be transmitted to the components of the first component (311-1), and through the above, the smart all-in-one cardiac patch (310) may obtain and transmit a heart-related signal.

[0078] FIG. 8 is a diagram illustrating a method for detecting abnormalities based on machine learning according to one embodiment of the present disclosure. Referring to FIG. 8, a smart all-in-one cardiac patch system can provide cardiac analysis information based on AI / ML (artificial intelligence / machine learning). More specifically, the smart all-in-one cardiac patch (310) can acquire cardiac signals and transmit them to a user device, as described above. Here, the user device can automatically detect abnormalities by performing inference based on the signals acquired by the embedded algorithm or the condition monitoring learning model (S810). For example, the user device can be equipped with an embedded algorithm or a condition monitoring learning model. Here, the embedded algorithm or the condition monitoring learning model can automatically detect abnormalities in the user's condition. As a specific example, the user device can acquire cardiac signals from the smart all-in-one cardiac patch (310) and compare them with information stored in a database. In addition, the user device can perform inference based on the preprocessed information after performing filtering, wavelet noise removal, and other preprocessing operations. For example, the learning model can perform inference based on rescaling or convolution neural network (CNN) classification operations, and automatically detect whether the acquired signal is abnormal. Thereafter, the user device can calculate analysis information based on the information about the abnormality (S830) and display the analysis information on the user device (S840). For example, the user device can compare signal information acquired daily with information about the abnormality through daily trend analysis, calculate scoring information based on the comparison, and display the scoring information on the user device.That is, the user device can analyze signals acquired from the smart all-in-one cardiac patch (310) based on AI / ML and provide the user with analysis information, and is not limited to a specific form. Here, as an example, the user device can receive a cloud-based, pre-learned condition monitoring learning model, and provide heart-related information as input to the condition monitoring learning model to derive an abnormality as an output value.

[0079] In addition, as an example, a signal acquired from a smart all-in-one heart patch (310) may be analyzed to reflect user status information. As an example, FIG. 9 is a diagram illustrating a method of analyzing a signal acquired based on user status information according to an embodiment of the present disclosure. Referring to FIG. 9, a signal acquired from a smart all-in-one heart patch (310) needs to be processed to reflect user status information. Specifically, the user status may include a standing state, a talking state, a walking state, a jogging state, and other states. Here, the heart-related signal may be acquired differently depending on the user status. For example, when a user is conversing with another user (i.e., a talking state), the user's voice signal may be included as noise in the heart-related signal. Therefore, there is a need to derive information in a form in which the noise is removed from the heart-related signal. As another example, when a user is jogging (i.e., a jogging state), the heart rate may increase, and accordingly, the acquired heart-related signal may be different. Considering the above, the user device can acquire additional user status information when acquiring heart-related signals. In addition, the user status information can be reflected in the embedded algorithm or learning model described above. Abnormality detection can be derived based on the user status information. As a specific example, if the user is jogging, the embedded algorithm or learning model can perform inference based on the jogging state as user status information and determine whether there is an abnormality. In other words, the embedded algorithm or learning model can build normal information about the user's jogging state, and automatically detect whether there is an abnormality if the signal acquired during the jogging state is different from the normal information. However, this is merely an example and is not limited to the above embodiment. That is, the signal acquired from the smart all-in-one cardiac patch (310) can be analyzed to reflect the user's status, and the analyzed information can be displayed through the user device.

[0080] As another example, an embedded algorithm or learning model for detecting abnormalities in heart-related signals may be trained based on the cloud, and a user device may acquire the embedded algorithm or learning model trained based on the cloud. FIG. 10 is a diagram illustrating a method for training a learning model based on the cloud according to an embodiment of the present specification. Referring to FIG. 10, a condition monitoring learning model for detecting abnormalities in heart-related signals in a smart all-in-one heart patch system may be trained based on the cloud. As an example, a plurality of user devices may be linked to a cloud endpoint, and each of the plurality of user devices may be linked to a smart all-in-one heart patch of a specific user to acquire heart-related information. (S1010) Each of the plurality of user devices may transmit the acquired heart-related information to the cloud (S1020), and the cloud may transmit the information to the backend based on an app engine (S1030). Here, the backend may use the heart-related information acquired from the plurality of user devices through the cloud to train the condition monitoring learning model. For example, the backend can update a condition monitoring learning model based on the acquired multiple signals and database, and transmit the updated learning model back to the user device. (S1040) The user device can perform inference on the heart-related signals acquired from the smart all-in-one heart patch based on the acquired condition monitoring learning model to detect abnormalities.

[0081] Here, as an example, FIG. 11 is a diagram illustrating a method for updating a condition monitoring learning model according to an embodiment of the present specification. Referring to FIG. 11, the cloud can obtain real-time information based on streaming. That is, real-time heart-related information is obtained from each smart all-in-one heart patch linked to a plurality of user devices (S1110), and the heart-related information can be generated as application data (S1120) and transmitted to the cloud (S1130). In addition, the cloud can obtain heart-related information for a plurality of user devices and perform data processing (S1140). Here, as an example, batch load information can be further obtained (S1110), and the obtained batch load information can be transmitted to the cloud (S1170). Here, the batch load information can be information related to a data set on which learning is to be performed. For example, the cloud can perform data processing in parallel on heart-related information and batch load information acquired in real time (S1140), and perform analysis based on each piece of information performed in parallel to update a condition monitoring learning model (S1150). Thereafter, the updated information can be transmitted to a user device (S1180), and the user device can display heart-related information analyzed based on the updated condition monitoring learning model (S1190). In addition, batch load information can also be transmitted to the user device, and the user device can analyze and display heart-related signals based on the information.

[0082] As an example, FIG. 12 is a diagram illustrating a method for a user device to display heart-related information according to an embodiment of the present disclosure. Referring to FIG. 12, the user device (420) may derive and display analysis information based on a signal acquired from a smart all-in-one heart patch, thereby providing information to the user. Here, the user device (420) may perform analysis on the acquired heart-related signal based on a cloud-based learned condition monitoring learning model or embedded algorithm. In addition, the user device (420) may store the signal acquired through the smart all-in-one heart patch (310) and perform monitoring based on the stored signal information to analyze the user's condition. Through this, the user device (420) may provide analysis information to the user, and the analysis information may be provided at preset intervals. In addition, the analysis information may be provided by reflecting the user's condition information, as described above.

[0083] Here, as an example, FIG. 13 is a diagram illustrating a smart all-in-one cardiac patch system according to an embodiment of the present specification. As an example, the smart all-in-one cardiac patch system may include a smart all-in-one cardiac patch (300), a user device (400), and a cloud (300) as described above. As an example, the smart all-in-one cardiac patch (300) may be configured in different types as described above. Specifically, the smart all-in-one cardiac patch (300) may be a first type (310), such as a 1-1 type (310-1) or a 1-2 type (310-2), but may not be limited to a specific form. In addition, the second type (320) may be a 2-1 type (320-1) or a 2-2 type (320-2), but may not be limited to a specific form. In addition, as an example, the smart all-in-one cardiac patch may be manufactured in different types and is not limited to a specific form. Here, the smart all-in-one cardiac patch (300) can be linked to each user device (400), which may be a smartphone, laptop, desktop, or other device. Thereafter, the cloud (500) can receive cardiac information acquired from each user device (400). For example, each user device (400) can transmit the acquired cardiac information to the cloud (500) via a network. Here, the cloud (500) may be a server, a platform, stored data, or other form, and may not be limited to a specific form.

[0084] Also, as an example, FIG. 14 is a diagram illustrating a method for performing a user information security operation according to an embodiment of the present specification. As an example, the smart all-in-one heart patch system can obtain heart-related information from a user device to which each smart all-in-one heart patch is connected. However, the information obtained from each smart all-in-one heart patch may be personal information about each user, and a security operation for the information may be required for user privacy and security. Referring to FIG. 14, the user device may assign user identification information to the user, and obtain a heart-related signal from the smart all-in-one heart patch based on the user identification information. (S1410) In addition, the user device may obtain additional heart-related information based on the user identification information to generate heart-related information, as described above. As an example, the user identification information may be a user ID (patient_id), and the smart all-in-one heart patch may sense and transmit a heart-related signal corresponding to the user identification information. Thereafter, the acquired heart-related information including the acquired heart-related signal and additional information can be recorded according to a session key, a device MAC address base identifier, and a unique time based on user identification information. (S1420) The user device can perform an analysis based on the recorded information based on the user identification information and generate report information to be reported to the cloud. (S1430) That is, the user device can acquire heart-related information for the corresponding user based on the user identification information, generate report information based thereon, and transmit the report information to the cloud. As described above, the cloud can acquire heart-related information for each user.Here, the report information reported from the user device can be transmitted to the cloud along with the signal type, data access time, and data modification time based on user identification information. Here, the report information transmitted based on the user identification information may be information that identifies each user, and if the information that identifies each user is used as is, privacy and security issues may arise. Therefore, the cloud can perform an operation of deriving highlight information from the acquired report information without identifiers. That is, the cloud can obtain report information, signal type, data access time, and data modification time information from the user device based on user identification information, and then generate highlight information without user identification information. Thereafter, the cloud can grant administrator access (authorized). Here, the highlight information can be encoded using a hexadecimal key that can access raw data, and the cloud can update a learning model or embedded algorithm based on the encoded data (S1450).

[0085] FIG. 15 is a diagram illustrating a method and device for a smart all-in-one cardiac patch according to one embodiment of the present disclosure. Referring to FIG. 15, the smart all-in-one cardiac patch (300) may include at least one of a housing portion (301), a body portion (302), a component portion (303), a signal amplifier portion (304), a battery portion (305), and a skin model portion (306). For example, the smart all-in-one cardiac patch (300) may be in the form of the first type (310) or the second type (320) described above, or any other type, but is not limited thereto. Here, the housing portion (301) may include the silicone gel and silicone elastomer described above. That is, the housing portion (301) may protect each component from the outside of the body portion (302), the component portion (303), the signal amplifier portion (304), and the battery portion (305). However, the skin model part (306) may be configured to allow the smart all-in-one heart patch (300) to be attached and maintained on the human body from the outside of the housing part (301). In addition, electrodes and a wireless charging coil may be located inside the housing part (301). Here, the electrodes may be ECG electrodes, and the ECG electrodes may be made of a gold material, but are not limited to this embodiment. For example, the outside of the housing part (301) may be attached to the human body, and heart-related signals generated in the human body may be transmitted through the ECG electrodes. In addition, the wireless charging coil may be configured to charge the battery of the smart all-in-one heart patch, as described above. The body part (302) inside the housing part (301) may include a component part (302-1) and a connection part (302-2). For example, the body part (302) may include a component part (302-1) formed of the polyimide described above, a component part (303), and a connecting part (302-2) connecting the component part (302-1).Here, the component (302-1) may include a first component for the central region and a second component for the distal region, and the first component and the second component may be connected via a connection portion (302-2). For example, the first component may include a first component portion that controls a heart-related signal acquired from a user's human body and transmits it to an external user device, and the second component portion may include a second component portion that directly senses and acquires a heart-related signal from the user's human body. That is, the component portion (303) may be located in the above-described component portion (302-1) to acquire a heart-related signal from the human body and transmit it to the user device (400) as an external device. For example, the component portion (303) may include a first component portion as a control portion that controls the sensed heart-related signal and a second component portion as a sensing portion that senses an actual heart-related signal, but is not limited to the embodiment. In addition, the signal amplification unit (304) can amplify a heart-related signal obtained from a human body using the above-described copper trace and transmit it to the user device (400). As an example, the signal amplification unit (304) may further include a transceiver that transmits a signal to the user device (400), but is not limited to the embodiment.

[0086] In addition, the battery unit (305) may include a battery to maintain power of the smart all-in-one heart patch (300), as described above. For example, the smart all-in-one heart patch is a low-power device that can maintain power for a long time through the battery. In addition, the skin model unit (306) may be configured to allow the smart all-in-one heart patch (300) to be hidden in the shape of human skin outside the housing unit (301), as described above. For example, the smart all-in-one heart patch (300) may acquire at least one of an electrical signal, an ECG, a low-frequency vibration signal, and a PCG, an acoustic signal, as a heart-related signal, and transmit the acquired signal to the user device (400). In addition, for example, the battery may serve to maintain power so that the smart all-in-one heart patch can transmit the acquired signal to the user device.

[0087] Thereafter, the user device (400) can analyze and display the user status based on the status monitoring learning model. Furthermore, the user status analysis may be provided using a status monitoring learning model pre-trained with heart-related information acquired from multiple user devices (400) based on the cloud (500), but is not limited to this embodiment.

[0088] Additionally, as an example, the smart all-in-one cardiac patch system may be a system including the above-described smart all-in-one cardiac patch (300), user device (400), and cloud (500), but may not be limited to the embodiment.

[0089] FIG. 16 is a diagram illustrating a method for providing heart-related information to a user according to one embodiment of the present invention.

[0090] Referring to FIG. 16, a heart-related signal can be acquired from a smart all-in-one heart patch (S1610). Thereafter, the heart-related signal can be provided as an input to a condition monitoring learning model (S1620), and an abnormality can be detected based on the inference of the condition monitoring learning model (S1630). Thereafter, the user device can analyze whether the user's condition is abnormal based on the detected abnormality (S1640), and display the analyzed information to provide it to the user (S1650).

[0091] The embodiments described above may be implemented at least in part as computer programs and recorded on a computer-readable recording medium. A computer-readable recording medium on which a program for implementing the embodiments is recorded includes any type of recording device that stores data that can be read by a computer. Examples of computer-readable recording media include ROMs, RAMs, CD-ROMs, magnetic tapes, and optical data storage devices. Furthermore, the computer-readable recording medium may be distributed across network-connected computer systems, such that computer-readable codes are stored and executed in a distributed manner. Furthermore, functional programs, codes, and code segments for implementing the embodiments will be readily understood by those skilled in the art to which the embodiments pertain.

[0092] Although the present specification has been described with reference to the embodiments illustrated in the drawings, these are merely exemplary, and those skilled in the art will understand that various modifications and variations of the embodiments are possible. However, such modifications should be considered within the technical protection scope of the present specification. Therefore, the true technical protection scope of the present specification should be determined to include other implementations, other embodiments, and equivalents to the claims, based on the technical spirit of the appended claims.

[0093]

[0094] The above may also apply to other systems.

Claims

1. A method for providing user analysis information to a user device based on a smart all-in-one heart patch, A step of receiving a heart-related signal obtained from a smart all-in-one heart patch; A step of providing the above heart-related signal as input to a condition monitoring learning model; A step of automatically detecting whether a user is abnormal based on the inference of the above-mentioned status monitoring learning model; A method for providing user analysis information, comprising the step of performing user information analysis based on detection of whether the user is abnormal and displaying the analyzed user information.

2. In paragraph 1, The above state monitoring learning model is obtained from the cloud, The cloud receives the heart-related signals of the smart all-in-one heart patch connected to each of the plurality of user devices from the plurality of user devices, A method for providing user analysis information, wherein the condition monitoring learning model is updated based on a plurality of the above heart-related signals.

3. In paragraph 2, The above cloud Acquire multiple cardiac-related signals in real time, Acquire more heart-related raw data based on batch load, A method for providing user analysis information, wherein a plurality of heart-related signals acquired in real time and the heart-related raw data acquired based on the batch load are processed in parallel and reflected in the condition monitoring learning model.

4. In paragraph 2, The smart all-in-one heart patch obtains the heart-related signal based on user identification information and transmits it to the user device, The user device records the heart-related signals obtained from the smart all-in-one heart patch along with a session key, a medium access control (MAC) address-based identifier of the user device, and a unique time based on the user identification information, A method for providing user analysis information, wherein heart-related information is transmitted to the cloud based on the above record, and the heart-related information is transmitted to the cloud together with a signal type, data access time, and data change time based on the user identification information.

5. In paragraph 4, A method for providing user analysis information, wherein the cloud derives record information excluding the user identification information from information obtained from the user device, encodes the record information with a hexadecimal key, and provides it as learning material for the status monitoring learning model based on administrator authority.

6. In paragraph 1, The smart all-in-one heart patch is a method for providing user analysis information, wherein the smart all-in-one heart patch senses at least one of an electrocardiogram (ECG), which is an electrical signal related to a heartbeat, a seismocardiogram (SCG), which is a low-frequency vibration signal, and a phonocardiogram (PCG), which is a heart sound wave signal, and transmits the sensed signal to the user device.

7. In paragraph 6, The above user device A method for providing user analysis information, which further obtains additional information related to the above heart-related signal and generates heart-related information based on the additional information.

8. In paragraph 1, A method for providing user analysis information, wherein the user device displays the analyzed user information based on an interface including user-related information and analysis information.

9. A computer program stored on a computer-readable recording medium that executes a method for providing user analysis information according to claims 1 to 8 in combination with hardware.

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