KR102536544B1 - Wearable device for monitoring heart disease based on combined measurement of heart sound and electrocardiogram and operation method thereof - Google Patents

Abstract

Disclosed are a wearable device that performs combined measurement of an echocardiogram and an electrocardiogram and monitors heart disease based thereon, and an operating method thereof.
According to one embodiment of the present invention, the electrocardiogram patch for measuring the electrocardiogram by contacting the measurement target; a membrane for measuring a cardiac phonocardiogram for measuring a phonocardiogram of the measurement target; a data merging unit for merging electrocardiogram data measured through the electrocardiogram patch and echocardiogram data measured through the membrane for measuring echocardiography; and a communication unit configured to transmit combined data of the electrocardiogram and the echocardiogram to a data analysis device that detects a heart disease through data analysis.

Description

Wearable device for performing combined measurement of cardiogram and electrocardiogram and monitoring heart disease based thereon and method of operating the same

Various embodiments of the present invention relate to a technique for monitoring heart disease of a companion animal by analyzing data collected through a combined measurement of an echocardiogram and an electrocardiogram.

As the companion animal market grows rapidly, the number of companion animal diseases is also increasing. The occurrence of companion animal diseases is linked to the economic and emotional burden of guardians. In particular, 45.56% of companion dogs in Korea are counted as middle-aged dogs over 7 years of age, and the incidence of heart disease is increasing among middle-aged dogs. Accordingly, there is a demand for the development of an early diagnosis technology for heart disease targeting middle-aged dogs aged 7 years or older with frequent heart disease.

As a conventional companion animal diagnosis method, a method of listening to the heart sound using a stethoscope was mainly used. In the case of small dogs, the size of the heart sound is very small, making it difficult to hear, and heart sounds of more than 120 beats per minute cannot be heard. . In addition, there was also a problem that it was difficult to diagnose constrictive and obstructive heart disease, and that there was a large individual difference according to the veterinarian's clinical experience.

When using an electronic stethoscope, it has the advantage that it can be checked graphically even if the heart sound is small, but there was no equipment exclusively for companion animal clinical use, and even with this, there was a disadvantage that it was difficult to diagnose constrictive or obstructive heart disease. In addition, when a stethoscope is used, since companion animals are nervous in a veterinary hospital, abnormal data is derived, noise is generated due to vibration, and accurate diagnosis is difficult.

Accordingly, there is an urgent need for a method to solve the problems of the conventional companion animal diagnosis method.

Korean Patent Publication No. 10-2020-0063637

An object of various embodiments of the present invention is to detect heart disease by combining and analyzing electrocardiogram and echocardiogram, and another object is to improve the accuracy of detecting heart disease.

The problems to be solved by the present invention are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below.

According to one of various embodiments of the present invention for solving the above problems, in the wearable device for monitoring heart disease, the electrocardiogram patch for measuring the electrocardiogram by contacting a measurement target; a membrane for measuring a cardiac phonocardiogram for measuring a phonocardiogram of the measurement target; a data merging unit for merging electrocardiogram data measured through the electrocardiogram patch and echocardiogram data measured through the membrane for measuring echocardiography; and a communication unit configured to transmit combined data of the electrocardiogram and the echocardiogram to a data analysis device that detects a heart disease through data analysis.

The electrocardiogram patch may include a sensor composed of two electrodes, and each electrode of the electrocardiogram patch may be disposed at a spaced apart position on the wearable device.

The data analysis apparatus may be characterized in that the power source noise of the first frequency band is removed through a wavelet transformation algorithm, and then only the data of the second frequency band is obtained by passing only the data of the second frequency band from the data from which the power source noise of the first frequency band is removed. can

Power supply noise removal in the first frequency band through the wavelet transform algorithm may be performed using a low pass filter, and data in the second frequency band may be passed through the wavelet transform algorithm through the use of a high pass filter.

When merging electrocardiogram data and echocardiogram data, the data merging unit or the data analysis device may perform data merging by synchronizing and plotting the electrocardiogram data based on the R-spike of the electrocardiogram data. .

The data merging unit or the data analysis device may sequentially recognize two heart sounds generated after the R-spike as a first heart sound (S1) and a second heart sound (S2) on integrated data in which electrocardiogram data and echocardiogram data are merged. can

The data analysis device may detect a type of heart disease corresponding to a waveform feature of integrated data obtained by merging electrocardiogram data and echocardiogram data.

The data analysis apparatus may determine a method of analyzing characteristics of integrated data obtained by merging electrocardiogram data and electrocardiogram data based on the length, weight, height, or genetic characteristics of the animal wearing the wearable device.

According to another one of various embodiments of the present invention for solving the above problems, a method for performing heart disease detection by a data analysis apparatus for detecting heart disease through data analysis received from a wearable device, from the wearable device Receiving signal data obtained by merging an electrocardiogram and an echocardiogram; removing power supply noise of a first frequency band from data obtained by merging the electrocardiogram and the echocardiogram; passing only data of a second frequency band over data from which power supply noise of a first frequency band has been removed; sequentially recognizing two heart sounds generated after the R-spike as a first heart sound and a second heart sound on data through which only data of a second frequency band has passed; and detecting a heart disease based on the recognized first heart sound and second heart sound.

The heart disease detection method of the data analysis device, after receiving signal data in which the electrocardiogram and the echocardiogram are merged from the wearable device and removing power supply noise of a first frequency band therefrom, the electrocardiogram and the echocardiogram are merged The method may further include dividing the data into electrocardiogram data and electrocardiogram data and extracting the data, and passing only the data of the second frequency band is performed on the separately extracted electrocardiogram data and the electrocardiogram data, respectively. After the step of passing the frequency band data, the step of plotting the heart sound data in synchronization with the R-spike of the electrocardiogram data; can be made on the basis of

According to an embodiment of the present invention, it is possible to detect heart disease in an integrated manner by merging electrocardiogram data and echocardiogram data. data analysis can be performed.

The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

1 is a diagram schematically showing an environment in which a wearable device for heart disease monitoring according to an embodiment of the present invention operates.
2 is a configuration diagram of a wearable device according to an embodiment of the present invention.
3 is a configuration diagram of a monitoring system including a wearable device according to an embodiment of the present invention.
4 is a block diagram showing the configuration of a wearable device according to an embodiment of the present invention, FIG. 5 is a configuration diagram of hardware for extracting electrocardiogram data, and FIG. 6 is a configuration diagram of hardware for extracting echocardiogram data. .
7 is a diagram for explaining a wavelet transform algorithm according to an embodiment of the present invention.
8 is a diagram for explaining a process of recognizing a heart sound through a heart sound and electrocardiogram data in a data analysis device according to an embodiment of the present invention.
9 is a diagram for explaining how a wearable device and a data analysis apparatus operate according to an embodiment of the present invention.

Terminology used herein is for describing the embodiments and is not intended to limit the present invention. In this specification, singular forms also include plural forms unless specifically stated otherwise in a phrase. As used herein, "comprises" and/or "comprising" does not exclude the presence or addition of one or more other elements other than the recited elements. Like reference numerals throughout the specification refer to like elements, and “and/or” includes each and every combination of one or more of the recited elements. Although "first", "second", etc. are used to describe various components, these components are not limited by these terms, of course. These terms are only used to distinguish one component from another. Accordingly, it goes without saying that the first element mentioned below may also be the second element within the technical spirit of the present invention.

When it is said that a certain part "includes" a certain component throughout the specification, it means that it may further include other components without excluding other components unless otherwise stated. In addition, terms such as "...unit" and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented as hardware or software or a combination of hardware and software. .

Hereinafter, various embodiments of the present invention will be described with reference to the accompanying drawings.

The wearable device disclosed in this specification can be applied regardless of the type of human or animal, but for convenience of description, it will be described by taking an example that the wearable device is installed and utilized on a companion animal.

In the present specification, electrocardiogram data may be interpreted as an electrocardiogram signal, and the electrocardiogram data may be interpreted as having the same meaning as a cardiogram signal.

1 is a diagram schematically showing an environment in which a wearable device 100 for heart disease monitoring according to an embodiment of the present invention operates.

The operating environment of the wearable device 100 may include the wearable device 100, the data analysis device 200, and the management server 300, in addition to additional configurations such as a user terminal, an administrator terminal, and an external server. can be included

The wearable device 100 includes an electrocardiogram patch 110 that measures an electrocardiogram by contacting a measurement target, an echocardiogram measurement membrane 120 that measures the electrocardiogram of the measurement target, and electrocardiogram data measured through the electrocardiogram patch 110. A data merging unit 130 that merges the echocardiogram data measured through the membrane 120 for measuring the echocardiogram and a communication unit 140 that transmits the merged data of the electrocardiogram and the echocardiogram to the data analysis device 200, the data It may be configured to include a storage unit 150 and a control unit 160 for storing.

According to an embodiment of the present invention, in the wearable device 100, only electrocardiogram data and echocardiogram data are collected, and the operation of detecting whether heart disease exists and the type of heart disease through data processing and analysis It may be performed on a separate data analysis device 200.

Unlike this, according to another embodiment, the data analysis device 200 that processes and analyzes data may be included in the wearable device 100 .

The electrocardiogram patch 110 may be located at a place in contact with the body of a measurement target when the measurement target wears the wearable device 100 . The ECG patch 110 serves to measure electrical signals of the heart through electrodes attached to the skin.

As shown in FIG. 1, the ECG patch 110 according to an embodiment of the present invention may be made of a sensor composed of two electrodes, and each electrode of the ECG patch 110 is spaced apart on the wearable device 100 can be placed in

The membrane 120 for measuring the echocardiography may be disposed adjacent to the electrocardiogram patch 110 on the wearable device 100 and may be configured in a form including a diaphragm and a bell.

The membrane 120 for measuring the echocardiography can record sounds collected through the MEMS microphone, and can save and store them in various file formats. According to an embodiment, the heart sound collected through the membrane 120 for measuring the heart sound may be stored on the storage unit 150 .

The data merging unit 130 may perform merging of electrocardiogram data measured through the electrocardiogram patch 110 and electrocardiogram data measured through the membrane 120 for measuring echocardiography.

According to an embodiment, the data merging of the data merging unit 130 may simply merge the electrocardiogram signal and the echocardiogram signal in the form of raw data as they are measured. It could also be to analyze the ECG data and merge them by synchronizing them in a specific way.

As an example, the data merging unit 130 analyzes the electrocardiogram data and the electrocardiogram data and synchronizes them in a specific way. Synchronization of can be performed.

The waveform of the electrocardiogram is generally divided into P wave, QRS wave, and T wave. The data merging unit 130 may perform merging of the electrocardiogram data and the electrocardiogram data by synchronizing and plotting the electrocardiogram data based on the R-spike of the QRS wave of the electrocardiogram data.

This synchronization method may not be performed by the data merging unit 130, but may be a merging method performed on the data analysis device 200 to be described later.

The communication unit 140 may transmit integrated data merged by the data merging unit 130 to the data analysis device 200 that detects heart disease through data analysis.

The communication unit 140 enables the wearable device 100 to communicate with the data analysis device 200 and other external devices. The communication network used by the communication unit 140 to perform communication may be configured regardless of its communication mode, such as wired and wireless, for example, a local area network (LAN) and a metropolitan area network (MAN). Area Network), wide area network (WAN), etc. may be implemented in various communication networks.

According to one embodiment, as shown in FIG. 1, the communication unit may perform communication with the data analysis device 200, router, server, etc. by utilizing Bluetooth Low Energy (BLE) technology, unlike WiFi. (Wireless Fidelity) technology may be used to perform communication with the data analysis device 200, router, server, and the like.

The storage unit 150 serves to store electrocardiogram data and echocardiogram data collected through the electrocardiogram patch 110 and the membrane 120 for measuring echocardiography. The storage unit 150 may include, for example, a memory, a cache, a buffer, and the like, and may be composed of software, firmware, hardware, or a combination of at least two or more of these.

According to one embodiment, the storage unit 150 may be configured in the form of a Micro SD card.

The controller 160 may play a role of controlling other elements within the wearable device 100 . According to one embodiment, the control unit 160 may be configured in the form of a board on which a microcontroller is mounted, and an operating system for controlling an embedded system may be mounted and operated.

2 is a configuration diagram of a wearable device 100 according to an embodiment of the present invention.

Referring to FIG. 2 , the wearable device 100 according to an embodiment of the present invention is configured in the form of a belt and can be mounted on the body of a measurement target such as a human or an animal.

3 is a configuration diagram of a monitoring system including the wearable device 100 according to an embodiment of the present invention.

Referring to FIG. 3 , the wearable device 100 disclosed through the present invention may be utilized in various environments.

According to an embodiment, when the wearable device 100 is used for home use, a user using the wearable device 100 in the home can access the wearable device 100 through a user terminal owned by the user. In this case, connection between the user terminal and the wearable device 100 may be performed through a program or application installed in the user terminal, and communication between the user terminal and the wearable device may be performed through Bluetooth, Wi-Fi, and the like.

When a user at home registers the wearable device 100 through the user terminal, the user terminal may transmit registration information about the wearable device 100 to the management server 300, and as the wearable device 100 operates Collected data may be transmitted to the management server 300 .

Thereafter, the management server 300 may transmit the data received from the data analysis device 200 , that is, integrated data of the electrocardiogram and the echocardiogram measured and merged with respect to the measurement target to the data analysis device 200 .

The data analysis device 200 may analyze the data received from the management server 300 and detect a heart disease of a measurement target using the wearable device 100 based on the analysis result.

In FIG. 3 , the management server 300 is exemplified and displayed as a veterinary hospital cloud server, and the data analysis device 200 is exemplified and displayed as a veterinary hospital PC. Unlike this, the data analysis device 200 and the management server 300 may be composed of various types of electronic devices or servers.

When the wearable device 100 is used in a place other than a home, such as a hospital, a manager using the wearable device 100 at the place can access the wearable device 100 through a manager terminal managed by the manager. In this case, connection between the user terminal and the wearable device 100 may be performed through a program or application installed in the manager terminal, and communication between the manager terminal and the wearable device may be performed through Bluetooth, Wi-Fi, and the like.

According to an embodiment, the manager terminal may be configured and operated as one device with the data analysis device 200. A manager in the hospital may register the wearable device 100 on the management server 300 through the data analysis apparatus 200 .

The data analysis apparatus 200 may analyze data received from the wearable device 100 and detect a heart disease of a measurement target using the wearable device 100 based on the analysis result. The data analysis device 200 may transmit data to be analyzed, analysis results, and the like to the management server 300 to be stored.

4 is a block diagram showing the configuration of a wearable device 100 according to an embodiment of the present invention, FIG. 5 is a configuration diagram of hardware for extracting electrocardiogram data, and FIG. 6 is a block diagram of hardware for extracting echocardiogram data. It is a composition diagram.

Referring to FIG. 4 , PCG data measured through the membrane 120 for measuring echocardiography may be collected through an I2S communication method through a MEMS microphone. Electrocardiogram (ECG) data may be collected through the electrocardiogram patch 110 in contact with the measurement target, and the electrocardiogram data collected through the electrocardiogram patch 110 may be collected through various types of filters, amplifiers, and converters as shown in FIG. and the like.

The wearable device 100 according to an embodiment of the present invention may include sensors such as an acceleration sensor, a gyroscope sensor, and a Global Positioning System (GPS).

In addition, the communication unit 140 in the wearable device 100 may communicate with external devices through various communication methods other than Bluetooth and WiFi.

Communication between components included in the wearable device 100 may be performed through various communication methods such as I2S, 12C, SPI, CAN, and UART. It can also be done through the kernel.

Referring to FIG. 5 , electrocardiogram data collected through the electrocardiogram patch 110 is subjected to removal of power noise of a first frequency band by a circuit implemented with a wavelet transform algorithm, and data obtained by removing power noise of the first frequency band is By passing through the filter, only data of the second frequency band may be passed and obtained.

Power supply noise removal in the first frequency band through the wavelet transform algorithm is performed using a low pass filter, and passing only the data in the second frequency band is performed through the use of a high pass filter. can

According to an embodiment of the present invention, the power noise of the first frequency band may be a 60 Hz band, and the second frequency band may be set to a 1 Hz to 3 Hz band.

Referring to FIG. 6 , the membrane 120 for measuring the echocardiogram may be acquired by collecting sound through a MEMS microphone hole.

Referring to FIGS. 5 and 6 , collected electrocardiogram data and echocardiogram data may be processed through a control unit (CPU) in the wearable device 100 and stored in the storage unit 150 in the form of various files. It may be transmitted to other devices or servers through the communication unit 140 .

7 is a diagram for explaining a wavelet transform algorithm according to an embodiment of the present invention.

Referring to FIG. 7 , waveforms for functions used in processing electrocardiogram data and echocardiogram data measured through the wearable device 100 are shown, and electrocardiogram (ECG) data and echocardiogram (PCG) data are wavelet-converted The shape of the change is shown.

In FIG. 7, the scaling function is a low-pass filter that can serve to remove power supply noise of a specific frequency band, and the wavelet function is a high-pass filter that serves to pass only a specific frequency band. can do.

The wearable device 100 or the data analysis apparatus 200 may remove noise included in the electrocardiogram and the echocardiogram through wavelet transform using such a function.

8 is a diagram for explaining a process of recognizing a heart sound through a heart sound and electrocardiogram data in the data analysis device 200 according to an embodiment of the present invention.

The data analysis apparatus 200 of FIG. 8 receives the data obtained by simply merging the electrocardiogram and the echocardiogram through a communication method such as Bluetooth or WiFi from the wearable device, and checks the accuracy of the data using a checksum method. , power supply noise can be removed by applying a wavelet transformation algorithm.

Thereafter, the data analysis device 200 separately extracts electrocardiogram data and echocardiogram data from data in which the electrocardiogram and the echocardiogram are simply merged, and performs wavelet transformation on each data to obtain a specific frequency band (eg, 1 Hz to 3 Hz). ) can be extracted.

The data analysis device 200 may perform plotting by synchronizing the electrocardiogram data based on the R-spike of the electrocardiogram data, and thereafter, the first heart sound and the second heart sound in order of two heart sounds generated after the R-spike. can be recognized as

The first heart sound is a sound generated when the mitral and tricuspid valves of the heart are closed, and the second heart sound is a sound generated when the aortic and pulmonary valves are closed.

According to an embodiment, data in a floating state in which electrocardiogram data and electrocardiogram data are synchronized in the data analysis device 200 may be displayed through the display unit. On the screen displayed through the display unit of the data analysis device 200, a P wave, a QRS wave, a T wave, etc. may be displayed in a state in which the electrocardiogram data and the echocardiogram data are synchronized, and the R-spike wave among the QRS waves is displayed. Afterwards, the first heart sound S1 and the second heart sound S2 may be displayed.

The data analysis device 200 may then detect a corresponding type of heart disease according to waveform characteristics of data obtained by merging the electrocardiogram data and the echocardiogram data. As the recognition of the first heart sound S1 and the second heart sound S2 is more clearly performed on the data obtained by combining the electrocardiogram data and the echocardiogram data, the accuracy of analysis of the entire waveform on the data may be improved. The data analysis device 200 comprehensively analyzes the entire waveform of the combined data of the electrocardiogram data and the echocardiogram data, and compares the waveform with the waveform when a specific heart disease exists to detect whether or not the measurement target has heart disease and the type of heart disease. can do.

9 is a diagram for explaining how the wearable device 100 and the data analysis apparatus 200 operate according to an embodiment of the present invention.

In FIG. 9 , steps S910 to S930 are described as operations performed by the wearable device 100 , and subsequent steps S940 to S980 are described as operations performed by the data analysis apparatus 200 . However, the scope of the present invention is not limited to the subject performing each of these steps, and each step may be performed in any one of the wearable device 100, the data analysis device 200, and the management server 300.

The wearable device 100 may be mounted on a target for measuring heart disease (S910). When the wearable device 100 is mounted on a measurement target, the electrocardiogram patch 110 may be mounted in a form in contact with the body near the heart as shown in FIG. It can be mounted to be placed at the location to be measured.

The wearable device 100 may then obtain electrocardiogram data and echocardiogram data of the measurement target (S920). Acquisition of electrocardiogram data and echocardiogram data may be performed through the electrocardiogram patch 110 and the membrane 120 for measuring echocardiography, as described above.

Thereafter, the wearable device 100 may simply merge the collected electrocardiogram data and the electrocardiogram data according to the acquired time and transmit the merged data to the data analysis apparatus 200 (S930). According to an embodiment, the wearable device 100 transmits the acquired electrocardiogram and echocardiogram data to the management server 300, and the management server 300 transmits the received data to the data analysis device 200. Data may be passed.

The data analysis apparatus 200 may remove the power supply noise of the first frequency band from the data received from the wearable device 100, and then separate the data from which the power supply noise has been removed into electrocardiogram data and echocardiogram data (S940).

Thereafter, the data analysis apparatus 200 may pass only the second frequency band for each of the electrocardiogram data and the electrocardiogram data separated after the power source noise is removed (S950).

The data analysis apparatus 200 may merge the electrocardiogram data and the electrocardiogram data in a state in which only the second frequency band has passed in a synchronized manner (S960). In detail, the merging of the electrocardiogram data and the electrocardiogram data may be performed by plotting the electrocardiogram data based on the R-spike of the electrocardiogram data.

The data analysis device 200 may sequentially recognize noise generated after the R-spike as the first heart sound (S1) and the second heart sound (S2) on the data in which the electrocardiogram data and the echocardiogram data are synchronized (S970). ).

The data analysis device 200 performs analysis based on the finally recognized waveforms including the first heart sound and the second heart sound to determine whether the measurement target has heart disease and what kind of heart disease is suspected. Whether or not it can be detected (S980). That is, the data analysis apparatus 200 can detect heart disease through the entire waveform of the merged data through synchronization, and the subject to be analyzed in the data is not limited to the first heart sound and the second heart sound.

Heart disease detection by the data analysis device 200 may be performed in different ways depending on the characteristics of the person wearing the wearable device 100 . In addition, when mounting on a non-human animal for the purpose of detecting a heart disease in an animal, a method or criterion for performing data analysis may be differently determined based on the size, weight, height, or genetic characteristics of the animal.

The genetic characteristics may be information about what kind of animal the animal is and what kind of genetic disease it has, and the length, weight, height, or genetic characteristics of the animal are entered by a companion raising the animal and the data analysis device ( 200) or may be transmitted to the management server 300.

That is, according to the wearable device 100 of the present invention, the accuracy of heart disease detection can be increased by performing customized data analysis on animals of various types and conditions.

According to another embodiment of the present invention, the data transmitted from the wearable device 100 to the data analysis apparatus 200 is a state in which the electrocardiogram data and the echocardiogram data are separated, rather than a state in which the electrocardiogram data and the echocardiogram data are simply merged. , and the data analysis device 200 performs power supply noise removal of the first frequency band on the data separated into electrocardiogram data and echocardiogram data differently from that illustrated in FIG. 9 and removes power noise of the second frequency band After passing only the data, data merging through synchronization can be performed.

That is, the electrocardiogram data and the echocardiogram data received by the data analysis apparatus 200 from the wearable device 100 may be in a simply merged state or may be in a separate state.

When the electrocardiogram data and the echocardiogram data are in a merged state, the data analysis device 200 removes power source noise and separates the data into electrocardiogram data and echocardiogram data, and then passes only a specific frequency band from each data and synchronizes the data. to merge the two types of data again. In this way, after the data analysis device 200 separates and processes the electrocardiogram data and the electrocardiogram data, synchronization is performed in a specific method and merged again, so that the first heart sound and the second heart sound can be recognized in a more accurate form. Accordingly, the accuracy of heart disease detection can be improved.

As described above, according to various embodiments of the present invention, by merging electrocardiogram data and echocardiogram data and determining heart disease based thereon, it is possible to more accurately detect heart disease caused by valve stenotic disease and regurgitation insufficiency. there is.

Steps of a method or algorithm described in connection with an embodiment of the present invention may be implemented directly in hardware, implemented in a software module executed by hardware, or implemented by a combination thereof. A software module may include random access memory (RAM), read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, hard disk, removable disk, CD-ROM, or It may reside in any form of computer readable recording medium well known in the art to which the present invention pertains.

Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art to which the present invention pertains can be implemented in other specific forms without changing the technical spirit or essential features of the present invention. you will be able to understand Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive.

100: wearable device
200: data analysis device
300: management server

Claims (10)

In a wearable device for monitoring heart disease,
An electrocardiogram patch that measures an electrocardiogram by contacting a measurement target;
a membrane for measuring a cardiac phonocardiogram for measuring a phonocardiogram of the measurement target;
a data merging unit for merging electrocardiogram data measured through the electrocardiogram patch and echocardiogram data measured through the membrane for measuring echocardiography; and
Includes a communication unit that transmits the combined data of the electrocardiogram and the echocardiogram to a data analysis device that detects heart disease through data analysis;
The data merging unit or the data analysis device, when merging the electrocardiogram data and the electrocardiogram data, synchronizes and plots the electrocardiogram data based on the R-spike of the electrocardiogram data. Wearable device.
According to claim 1,
The ECG patch,
It consists of a sensor composed of two electrodes,
Characterized in that each electrode of the electrocardiogram patch is disposed at a spaced apart position on the wearable device, the wearable device.
According to claim 1,
The data analysis device,
A wearable device characterized by removing power source noise of a first frequency band through a wavelet transform algorithm and then passing only data of a second frequency band from data from which the power source noise of the first frequency band has been removed.
According to claim 3,
The first frequency band power supply noise removal through the wavelet transformation algorithm is performed through the use of a low-pass filter,
Passing the data of the second frequency band through the wavelet transform algorithm is achieved through the use of a high pass filter, the wearable device.
delete According to claim 1,
The data merging unit or data analysis device,
A wearable device that sequentially recognizes two heart sounds generated after the R-spike as a first heart sound (S1) and a second heart sound (S2) on integrated data in which electrocardiogram data and echocardiogram data are merged.
According to claim 1,
The data analysis device,
A wearable device characterized by detecting a type of heart disease corresponding to a waveform feature of integrated data obtained by merging electrocardiogram data and echocardiogram data.
According to claim 1,
The data analysis device,
Characterized in that, based on the length, weight, height or genetic characteristics of the animal wearing the wearable device, a method of analyzing characteristics on integrated data in which electrocardiogram data and echocardiogram data are merged is determined. Wearable device.
A method for detecting heart disease by a data analysis device that detects heart disease through data analysis received from a wearable device,
receiving signal data in which an electrocardiogram and an echocardiogram are merged from the wearable device;
removing power supply noise of a first frequency band from data obtained by merging the electrocardiogram and the echocardiogram;
passing only data of a second frequency band over data from which power supply noise of a first frequency band has been removed;
plotting the electrocardiogram data in synchronization based on the R-spike of the electrocardiogram data;
sequentially recognizing two heart sounds generated after the R-spike as a first heart sound and a second heart sound on data through which only data of a second frequency band has passed; and
A heart disease detection method of a data analysis device comprising the step of detecting a heart disease based on the recognized first heart sound and second heart sound.
According to claim 9,
After receiving the combined signal data of the electrocardiogram and the echocardiogram from the wearable device and removing power supply noise of a first frequency band therefrom,
Further comprising extracting the merged data of the electrocardiogram and the phonocardiogram by dividing the data into electrocardiogram data and phonocardiogram data,
The step of passing only the data of the second frequency band is separately performed on the extracted electrocardiogram data and the electrocardiogram data,
The heart disease detection method of the data analysis device, wherein the recognition of the first heart sound and the second heart sound is performed based on data merged through plotting.

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