KR20220115038A - Biometric data measuring and reading system - Google Patents

Abstract

The present invention relates to a system for measuring and reading biometric data. The system for measuring and reading biometric data includes: a measurement system by which a user self-measures biometric data of the user; and a reading system, which performs disease prediction, infectious disease risk prediction, and severity reading on the basis of data received from the measurement system, so as to generate a reading result. Therefore, self-measurement is possible without the help of medical staff or professional personnel, thereby minimizing a risk of infection.

Description

Biometric data measurement and reading system

The present invention measures and reads biometric data including electrocardiogram, oxygen saturation, and a plurality of vital sign indicators at the same time, and reads biometric data using an artificial intelligence-based biodata reading algorithm to predict disease and read severity It's about the system.

Only with the patient's current biometric data can the patient's disease be diagnosed. In general, in a medical institution, a nurse periodically measures a patient's blood pressure, pulse, body temperature, electrocardiogram, oxygen saturation, etc. using a biometric data measuring device, and manually records the measured values. Nursing personnel and professional examination personnel are required to measure the patient's biometric data, and it takes a lot of time to measure and analyze the biometric data. In the case of some biometric data, for example, an electrocardiogram, a specialist for reading the electrocardiogram data is more required, and additional time is required to read and analyze the data.

It is essential to check vital signs (blood pressure, pulse, respiration rate, body temperature) at various sites, such as the waiting room and emergency room of a hospital, emergency room, screening clinic, living treatment center/isolation facility, infectious disease prevention site, and medical blind spot. In severe or semi-severe patients, oxygen saturation and electrocardiography are additionally required.

Due to the spread of new infectious diseases, for example, the corona virus infection (COVID-19), the fatigue of medical workers is reaching an extreme, and the shortage of medical equipment is serious. In such a situation, there is a high possibility of an accidental exposure of patients and healthcare workers during repeated examination of biometric data.

Republic of Korea Patent No. 10-2210215 (2021.01.26.) Republic of Korea Patent Registration No. 10-2197112 (2020.12.31.) Republic of Korea Patent Registration No. 10-2210242 (2021.01.26) Republic of Korea Patent Registration No. 10-2208759 (2021.01.22.)

SUMMARY OF THE INVENTION The present invention aims to solve the above-mentioned needs and/or problems.

In particular, the present invention provides a system for measuring and reading biometric data that enables users to easily measure their own biometric data and receive a reading result in real time.

The problems of 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 following description.

A system for measuring and reading biometric data according to an embodiment of the present invention includes: a measurement system in which a user measures his/her own biometric data; and a reading system for generating a reading result by reading a disease prediction, an infectious disease risk prediction, and a severity based on the data received from the measurement system.

The measurement system includes: electrodes and a sensor unit including a left hand electrode, a right hand electrode, a PPG sensor, a respiration rate sensor, a body temperature sensor, a blood pressure and a camera sensor; The signal received from the electrodes and sensors is amplified, noise is removed, and converted into a digital signal to convert electrocardiogram measurement data, oxygen saturation measurement values, blood pressure, pulse rate, respiratory rate, and vital signs measurement values including body temperature into digital signals. a sensor control unit that outputs; a user data input unit for receiving basic information of the user including the user's gender, age, and hospital room information; a user interface unit including a data output unit for outputting a result; a communication unit connected to the reading system through a wired/wireless communication network; and receiving the ECG measurement data, the oxygen saturation measurement value, and the vital sign measurement value from the sensor controller, and transmits the ECG measurement data oxygen saturation measurement value, and the vital sign measurement value together with the user's basic information to the communication unit and a central control unit that transmits to the reading system via , and provides the reading result from the reading system received via the communication unit to the data output unit.

The reading system generates a heart disease prediction result based on the electrocardiogram measurement data using an artificial intelligence-based biometric data reading algorithm that has learned the learning data, and measures the heart disease prediction result, the oxygen saturation measurement value, and the vital signs value and the user's basic information to generate an infectious disease risk prediction result, and the user's basic information and past medical records, the reading result of the electrocardiogram measurement data, the oxygen saturation measurement value, and the vital sign measurement value and a server for reading the severity based on the severity and generating a severity reading result.

The present invention relates to the degree of fatigue of medical personnel who have to periodically repeat the ECG and four vital signs (blood pressure, pulse, respiration rate, and body temperature) tests of users (patients, general public), and oxygen saturation and ECG tests for severe or semi-severe patients. can be drastically reduced.

The present invention can minimize the risk of infection because self-measurement is possible without the help of medical staff or professional personnel.

The present invention can improve the work of medical staff through automation of the measurement and recording of electrocardiogram and vital signs.

The biometric data reading system of the present invention can be applied to a remote diagnosis field in which non-face-to-face biometric data collection is possible.

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

1 is a block diagram of an overall service configuration for a biometric data measurement and reading system according to an embodiment of the present invention.
2A and 2B are diagrams illustrating biometric data measurement in the form of a desk or kiosk (KIOSK) according to an embodiment of the present invention.
3 is a diagram illustrating a system for measuring biometric data in the form of a notebook or laptop according to an embodiment of the present invention.
4 and 5 are diagrams showing an artificial intelligence-based biometric data reading algorithm.
6 is a diagram of Leads I to III, aVr, aVl, and aVf, which are six leads obtained from three electrodes.
7 is a view showing that a link service with companies and institutions is possible through the biometric data measurement system of the present invention and HIS linkage.
8 is a diagram illustrating a monitor system for remotely inquiring a result of reading biometric data measured from a plurality of devices to which the biometric data system is applied.

Advantages and features of the present invention, and a method of achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. The present invention is not limited to the embodiments disclosed below, but will be implemented in various different forms, and only the embodiments allow the disclosure of the present invention to be complete, and to those of ordinary skill in the art to which the present invention pertains It is provided to fully indicate the scope of the invention, and the invention is only defined by the scope of the claims.

The shapes, sizes, proportions, angles, numbers, etc. disclosed in the drawings for explaining the embodiments of the present invention are exemplary, and thus the present invention is not limited to the matters shown in the drawings. Like reference numerals refer to substantially like elements throughout. In addition, in describing the present invention, if it is determined that a detailed description of a related known technology may unnecessarily obscure the subject matter of the present invention, the detailed description thereof will be omitted.

In the case in which “comprising”, “includes”, “having”, “consisting”, etc. mentioned in this specification are used, other parts may be added unless 'only' is used. When a component is expressed in the singular, it may be interpreted as the plural unless otherwise explicitly stated.

In interpreting the components, it is interpreted as including an error range even if there is no separate explicit description.

In the case of a description of the positional relationship, for example, when the positional relationship between the two components is described as 'on One or more other elements may be interposed between those elements in which 'directly' or 'directly' are not used.

The first, second, etc. may be used to distinguish the components, but the functions or structures of these components are not limited to the ordinal number or component name attached to the front of the component.

The following embodiments may be partially or wholly combined or combined with each other, and technically various interlocking and driving are possible. Each embodiment may be implemented independently of each other or may be implemented together in a related relationship.

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

1 to 4 , a biometric data reading system according to an embodiment of the present invention includes a biometric data measuring system 1000 and a reading system 3000 connected to the measuring system 1000 through a wired/wireless communication network. to provide

The biometric data measurement system 1000 includes a sensor control unit 200 , a central control unit 100 , a user interface unit 101 , communication units 300 and 400 , and a power supply unit 500 connected to electrodes and a sensor unit.

The electrode and sensor unit includes electrodes 202 to 205 and sensors 206 to 209 . The electrodes 202 to 205 are electrocardiogram (ECG) electrodes for measuring an electrocardiogram of a user (patient, general public).

The electrodes 202-205 include a left hand electrode 202 contacting the left hand, a right hand electrode 203 contacting the user's right hand, a left foot electrode 204 contacting the user's left foot, and a right foot contacting the user's right foot. electrode 205 and the like. Here, the left foot electrode 204 and the right foot electrode 205 may be omitted from the electrode and sensor unit.

The Lead I electrocardiogram signal may be obtained only by the left-hand electrode 202 and the right-hand electrode 203 . In the electrocardiogram measurement, the left-hand electrode 202 is an electrode for measuring an ECG LA (Left Ankle) signal or aVl signal. The right-hand electrode 203 is an electrode for measuring an ECG RA (Right Ankle) signal or aVr signal.

In order to obtain a 6-lead ECG signal waveform, a left foot electrode 204 is required in addition to the left hand electrode 202 and the right hand electrode 203 . The left foot electrode 204 is an electrode for measuring an ECG LF (Left Foot) signal or aVf (5d) signal. The three-lead electrocardiogram is obtained from the signal waveforms measured through the three electrodes 202, 203, and 204 connected to the user's hands and left feet, as shown in Fig. 6, I(6a), II(6b), III(6c). ), aVF(6d), aVL(6e), and aVR(6f) waveform data including 6-lead ECG waveform data can be output. A pulse may be measured by analyzing an electrocardiogram waveform or by analyzing a pulse wave signal from the PPG sensor 206 .

The right foot electrode 205 may be applied to set body impedance or a reference level, but may be omitted.

At least one of the left foot electrode 204 and the right foot electrode 205 may be disposed on a foot pad or an ankle clip illustrated in FIGS. 2A to 3 .

In the case of Lead I ECG signals, various types of heart-related diseases cannot be accurately measured. In the case of a 6-lead signal, heart disease may be subdivided and classified. Therefore, the 6-lead signal during reading by a specialist enables a more accurate diagnosis of heart disease compared to the Lead I electrocardiogram signal.

The sensors 206 to 209 may include a PPG sensor 206 , a respiration rate sensor 207 , a body temperature sensor 208 , and a camera sensor 209 and a blood pressure monitor. Additional sensors may be added according to measurement values required for diagnosis.

The PPG sensor 206 measures a user's pulse wave signal and oxygen saturation by using an LED (Light Emitting Diode). The PPG sensor 206 may be disposed on the surface of the ECG electrodes 202 to 204 in a structure that is not electrically connected to the ECG electrodes 202 to 204 . Either one of the user's hands and both feet can be in contact with the LED and the light-receiving part of the PPG sensor together with the ECG electrode at the same time.

The LED and the light receiving unit of the PPG sensor 206 are positioned opposite to the tip of the finger when the palm of the hand is placed on any one of the ECG electrodes 202 and 203 of both hands so that the blood pressure and the pulse wave signal can be simultaneously sensed at the same time as the ECG measurement. can be placed. The PPG sensor 206 may be disposed in a groove on the ECG electrode surface to block noise due to ambient light.

In the case of blood pressure, systolic and diastolic blood pressure can be measured using the pulse wave signal output from the PPG sensor 206 and the ECG signal measured from the ECG electrodes 202 to 205. It is possible to obtain blood pressure information by interworking. The external cuff type blood pressure monitor may be connected to the biometric data measurement system 1000 through the blood pressure monitor port 210 .

The respiration rate sensor 207 measures the respiration rate through the amount of change in body impedance that changes during inhalation and exhalation from the electrocardiogram electrode. The body temperature sensor 208 measures the user's skin temperature using an infrared (infrared ray) sensor. The camera sensor 209 outputs an image captured by the user. An image captured by the camera sensor 209 may be used to guide the correct position and posture distance for biometric data measurement along with user recognition.

The sensor control unit 200 converts the signals received from the electrodes 202 to 205 and the output signals of the sensors 205 to 209 into sensor values of digital signals that can be processed by the central control unit 100 to convert the central control unit 100 ) is sent to In addition, blood pressure is read from the cuff-type blood pressure monitor through the blood pressure monitor port 210 or a blood pressure value measured through Bluetooth Low Energy (BLE) in the wireless communication module 300 is read. The sensor control unit 200 includes an ECG Analog Front End (ECG AFE) 201 . The ECG AFE 201 amplifies the analog signal (electrocardiogram measurement signal) received from the electrodes 202 to 205 and converts it into a digital signal after removing noise. The digital signal output from the sensor controller 200 includes electrocardiogram measurement data, oxygen saturation measurement value, and four vital sign measurement values (blood pressure, pulse, respiration rate, and body temperature).

The central control unit 100 controls all components constituting the biometric data measurement system 1000 . The central control unit 100 communicates the user's basic information (gender, age, weight, height, phone number, etc.) received through the user interface unit 101 and the biometric data received from the sensor control unit 200 to the communication unit 300, 400) to the reading system. The biometric data output from the central control unit 100 includes electrocardiogram data, oxygen saturation measured values, and four vital sign measured values (blood pressure, pulse, respiration rate, and body temperature).

The central control unit 100 receives the reading result from the reading system through the communication units 300 and 400 and sends the reading result together with the electrocardiogram, coral saturation, and vital sign measurement values to the data output unit of the user interface unit 101 . to provide. The central control unit 100 may include a processor for controlling signal processing and input/output, and a memory.

The user interface unit 101 is connected to the central control unit 100 . The user interface unit 101 includes a user data input unit and a data output unit.

The user data input unit receives basic information (gender, age, weight, height, phone number, etc.) and user commands from the user. The user data input unit may include at least one of a voice input unit using a keypad, a touch pad, a mouse, and a microphone, and a gesture input unit using the camera sensor 209 .

The data output unit provides the user's own biometric data, the reading result derived by the reading system 3000, and the like to the user. The data output unit may include a display implemented as a liquid crystal display (LCD), an organic light-emitting diode display (OLED) display, or the like. Also, the data output unit may further include a printer.

The communication units 300 and 400 may include a wireless communication module 300 and a wired communication module 400 . The wireless communication module 300 may transmit the biometric data received from the central control unit 100 to the reading system 3000 via the gateway 2000 through a wireless communication interface, for example, Bluetooth™. The module 400 may transmit the biometric data received from the central control unit 100 to the reading system through a wired communication network such as Ethernet. That is, the electrocardiogram data, oxygen saturation measurement value, and four vital sign measurement values are transmitted to the reading system through a wired/wireless communication network, and the reading result is received from the reading system and provided to the central control unit 100 .

The power supply unit 500 generates power necessary for driving the measurement system using a battery, a battery charging circuit, a DC adapter, and the like.

The reading system 3000 is connected to the biometric data measurement system 1000 through a wired/wireless communication network. The reading system transmits the biometric data measurement value input from the biometric data measurement system 1000 through a wired/wireless communication network, and predicts the disease and reads the severity using the artificial intelligence-based biometric data reading algorithm 7200 . The reading system is connected to the mobile terminal of the user or medical staff and the hospital information system (hereinafter referred to as "") through a wired/wireless communication network, and is also connected to various external organizations and ambulances through a wired/wireless communication network. do. The reading system may transmit the biometric data reading result, the disease prediction result, and the severity reading result derived by the artificial intelligence-based biodata reading algorithm 7200 to the measurement system. Various external organizations and ambulances such as hospitals, public health centers, screening clinics, banks, public places, companies, etc. can interwork with the HIS 4000 to inquire the disease prediction results and severity reading results derived from the reading system in real time.

The reading system 3000 includes a server 3100 , a database (DB) 3200 , and an AI server 3300 . The reading system 3000 is connected to the HIS 4000 via the Internet substrate cloud. The reading system 3000 may be included in the measurement system 1000 to operate as needed.

The gateway 2000 transmits the user's basic information and biometric data received from the biometric data measurement system 1000 to the server 3100 through the Internet-based cloud.

The server 3100 processes system login and member management using the basic information of the user received through the gateway 2000 and the member information stored in the database 3200 . The server 3100 receives the user's basic information and biometric data from the biometric data measurement system through the gateway 2000 . The server 3100 operates the artificial intelligence-based biometric data reading algorithm 7200 to receive a disease prediction result, an infectious disease prediction result, and a severity reading result. The disease prediction result and severity may be classified in the order of highest probability and provided to the user and the medical staff.

The server 3100 requests the WAS (Web Application Server) in charge of log-in, member management, and biometric data measurement record processing, and artificial intelligence-based biometric data reading algorithm operation, and receives the reading result data obtained as a result of the driving of the algorithm. It can be divided into BAS (Biometric Data & information of medical treatment Analysis Server).

The database 3200 stores various biometric data and medical treatment information along with the user's basic information for AI-based learning. The server 3100 stores the user's basic information, various biometric data, and medical treatment information collected from a hospital or other external institution in the database DB. The learning data 7100 stored in the database 3200 is periodically updated and the accuracy of disease prediction and infectious disease risk prediction and severity reading is improved through the advancement of the artificial intelligence-based biometric data reading algorithm 7200 .

The AI server 3300 drives the artificial intelligence-based biometric data reading algorithm 7200 that is periodically learned using the learning data 7100 to read the reading result, disease prediction result, infectious disease prediction result, and severity of each of the biometric data. To derive the results.

The biometric data received from the server 3100 records the user's basic information, biometric data, and biometric data reading result in the EMR system through interworking with the HIS 4000 . The HIS 4000 is interlocked with the HIS 4000 of other hospitals through the Internet, and interlocked with other external organizations and ambulances.

The reading result derived from the AI server 3300 includes a disease prediction result derived by the artificial intelligence-based biometric data reading algorithm 7200, an infectious disease risk prediction result, and a severity reading result. The server 3100 transmits the reading result to the measurement system so that the user can check the measurement value together with his or her own biometric data, and also monitors the user's mobile terminal and the medical staff so that the medical staff can monitor the user's reading result in real time. It can be transmitted to the system ( 4100 in FIG. 8 ). The medical staff's monitor system may include a stationary monitor system, a portable mobile terminal, and the like.

The server 3100 may transmit an alarm signal together with the reading result to the medical staff's monitor system when the risk of an infectious disease is detected or the severity of the reading result of the user (patient, general public) is high. The alarm signal may be displayed as a preset alarm message or image on the screen, and may be output as a preset sound signal through a speaker of the monitor system.

As shown in FIG. 4 , the artificial intelligence-based biometric data reading algorithm 7200 includes electrocardiogram data, oxygen saturation measurement values, and vital signs measurement values (blood pressure, pulse, respiration rate, body temperature), and the user's medical information, location Using information, etc. to read heart disease, predict the risk of infectious diseases such as COVID-19 or MERS, and read the severity.

The learning data 7100 includes basic demographic information such as age and gender, four vital signs, electrocardiogram, oxygen saturation, diagnosis/treatment result information, and hospital room information collected from hospitals or other external organizations such as the National Health Insurance Corporation. It is big data including various patient data such as emergency room patient data, intensive care patient data, surgical patient data, outpatient data, and electrocardiogram disease data, as well as electrocardiogram reading result data of specialists, severity diagnosis result data, infectious disease data, and vital sign reading result. The artificial intelligence-based biometric data reading algorithm learns the learning data 7100 based on deep learning to increase the accuracy of reading biometric data, predicting heart disease, predicting risk of infectious disease, and reading severity. The training data 7100 may be stored and updated in the database 3200 .

The artificial intelligence-based biometric data reading algorithm 7200 includes a heart disease reading model, an infectious disease risk prediction model, and a severity judgment model as shown in FIG. 4 .

The heart disease reading model includes a time series reading unit and an image reading unit. The time series reader extracts the characteristic values of the waveform based on the ECG data in the training data and predicts heart disease based on this. The image reader converts the ECG data in the learning data into an image and predicts heart disease with an AI-based algorithm that is learned according to the classification by heart disease. The heart disease reading model integrates the time series reading result and the image reading result to select a disease with a higher probability of similarity.

The infectious disease risk prediction model includes the ECG reading result and predicted disease derived from the heart disease reading model, oxygen saturation value, vital sign value, user's basic information (gender, age, weight, etc.), and the user's medical record, hospital room information ( or location information) based on deep learning to determine the risk of infectious diseases such as COVID-19 and MERS in consideration of changes in the time and location trend of biometric data measurements.

As shown in FIGS. 4 and 5, the severity reading model is a disease prediction derived from the heart disease reading model, current and past measurements of oxygen saturation values and vital sign values (blood pressure, pulse rate, respiration rate, and body temperature), users The severity of the basic information (gender, age, weight, etc.) and the user's medical record information is read using the deep learning-based learning results of several stages.

Severity can be divided into 5 stages. For example, the severity is a level of resuscitation requiring urgent measures such as CPR (Level1), an emergency level lower than the resuscitation level (Level1) (Level2), an emergency level lower than the emergency level (Level2) (Level3), an emergency level (Level3) Level 3) It can be divided into a lower semi-emergency stage (Level 4) and a non-emergency stage (Level 5) classified as a mild patient. The readout may include predicted disease and severity.

The medical staff's monitor system is connected to the reading system through a communication network. The monitor system may monitor the user's ECG reading result, oxygen saturation measurement result, vital sign measurement result, disease prediction result, infectious disease risk prediction result, suspicious prediction result, and severity reading result received from the reading system in real time. When a reading result is received from the reading system, the monitor system may classify treatment and treatment priorities according to severity and assign a ward. The medical staff's monitoring system outputs an alarm signal when a result of a deviation from the normal range of biometric data is received, an infectious disease risk prediction result is received, or a high-severity reading result is received, and the patient is assigned to the intensive care unit or emergency room, and emergency measures are taken by the medical staff. can be instructed. The mobile terminal of the medical staff may output an alarm signal together with the reading result when an infectious disease risk prediction result is received by a preset application or a high severity reading result is received.

The biometric data reading system 3000 of the present invention derives a reading result of biometric data, a disease prediction result, an infectious disease risk prediction result, and a severity reading result, and transmits these data to hospitals and other various external sources through the HIS 4000 . It can be provided to agencies and ambulances. The HIS 4000 includes a medical staff's monitor system ( 4100 in FIG. 8 ).

7 is a diagram showing an example of a method of interworking with multiple biometric information measurement results and reading results through the HIS interworking of each external organ in the biometric data reading system of the present invention.

Referring to FIG. 7 , hospitals have their own HIS 4000 .

The biometric data measurement system is implemented in various form factors as shown in FIGS. 7 to 10 , and may be installed in not only hospitals but also public health centers, clinics, ambulances, healthcare companies, banks/large corporations, and public institutions. Users can measure their own biometric data by using the biometric data measurement system in these institutions, check the measurement results directly on the display, and receive a reading result sheet in the form of an electronic file such as a PDF file, and print the reading result sheet through a printer. can In the case of a bank, a biometric data measurement system can be used as one of customer services. A company can utilize a biometric data measurement system for employee welfare.

2A to 3 are diagrams illustrating various form factors of the biometric data measurement system 1000 .

2A and 2B , the biometric data measuring system 1000 may be divided into a main body device 5000 , a display 102 , and a footrest 5100 .

The main body device 5000 includes two-handed ECG electrodes 202 and 203, sensors 206 to 209, a sensor control unit 200, a central control unit 100, a user data input unit of the user interface unit 101, and a communication unit ( 300, 400), and is fixed to the top plate of the desk or kiosk type structure. The main body device 5000 may further include external interface ports such as a port to which the cuff type blood pressure monitor 1100 is connected and a USB connection port.

The display 102 of the user interface 101 may include a camera module. In this case, the camera module is disposed on the top of the display 102 to face the head of the user sitting in the chair. The camera module includes a body temperature sensor 208 and a camera sensor 209 . The display 102 may be fixed to a display support vertically coupled to the desk top. The display 102 may transmit/receive signals to and from the main body through a cable or communication units 300 and 400 connected to a display port of the main body device.

The footrest 5100 may be fixed to the lower plate of the desk or the lower plate of the kiosk type structure. The footrest 5100 includes a left foot electrode 204 and a right foot electrode 205 , and is connected to the main body device 5000 through cables or communication units 300 and 400 connected to ports of the main body device 5000 .

Referring to FIG. 3 , the biometric data measuring system 1000 includes a main body device 6000 to which a display 102 is foldably coupled. The main body device 6000 may be implemented in the form of a notebook or laptop.

The main body device 6000 includes both hands ECG electrodes 202 and 203 , sensors 206 to 209 , a sensor control unit 200 , a central control unit 100 , a user interface unit 101 , and a communication unit 300 , 400 . includes

The display 102 is operably coupled to the main body device 6000 through a hinge. The main body device 6000 may further include external interface ports such as a port for ECG electrode connection, a port to which a cuff type blood pressure monitor 210 is connected, a USB connection port, and a port to which a printer is connected. have. The desk-type device 6000 having this structure has no restrictions on installation space and is easy to carry.

The main body device 6000 may provide a lead I electrocardiogram signal, oxygen saturation, and biometric data including four vital signs (blood pressure, pulse, respiration rate, and body temperature). By adding the left foot electrode 204 through the port of the main body device 6000, it is possible to provide ECG data even with a 6-lead ECG waveform.

When precise electrocardiogram measurement is required, a footrest 6010 or an ankle clip 6020 on which the electrodes 204 and 205 are disposed may be provided as an option.

The biometric data measuring system and reading system of the present invention can be constructed as a remote diagnosis system that requires non-face-to-face biometric data measurement and enables remote monitoring. For example, as shown in FIG. 8 , devices in which biometric data measurement systems 1000 capable of self-measurement of biometric data of hospital inpatients are implemented may be disposed at the entrance of the hospital.

The medical staff's monitor system 4100 is disposed in a separate space separated from the biometric data measuring systems 1000 with a partition therebetween, and the visitor's biometric data measurement value and whether the normal range is deviated, disease prediction result, infectious disease risk prediction Results and severity can be viewed in real time. In particular, the monitoring system 4100 determines that at least one of the deviation of the normal range of the electrocardiogram, the deviation of the oxygen saturation from the normal range, and the deviation of each of the vital sign indicators from the normal range, the result of predicting the risk of infectious disease, and the severity of the emergency stage or higher is a reading system When received from the , an alarm signal can be output to request an emergency response from the medical staff. The alarm signal may also be transmitted to the mobile terminal of the medical staff.

Since the contents of the specification described in the problems to be solved above, the means for solving the problems, and the effects do not specify the essential characteristics of the claims, the scope of the claims is not limited by the matters described in the contents of the specification.

Although the embodiments of the present invention have been described in more detail with reference to the accompanying drawings, the present invention is not necessarily limited to these embodiments, and various modifications may be made within the scope without departing from the technical spirit of the present invention. Therefore, the embodiments disclosed in the present invention are not intended to limit the technical spirit of the present invention, but to explain, and the scope of the technical spirit of the present invention is not limited by these embodiments. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. The protection scope of the present invention should be construed by the claims, and all technical ideas within the scope equivalent thereto should be construed as being included in the scope of the present invention.

100: central control unit 101: user interface unit
200: sensor control unit 201: ECG AFE
202: left-hand electrode 203: right-hand electrode
204: left foot electrode 205: right foot electrode
206: PPG sensor 207: respiration rate sensor
208: body temperature sensor 209: camera sensor
210: blood pressure monitor port 300: wireless communication module
400: wired communication module 500: power unit
2000: gateway 3000: reading system
3100: Server 3200: DB
3300: AI Server 4000: HIS
4100: monitor system 5000, 6000: main unit
5100, 6010: footrest 6020: ankle clip

Claims (8)

a measurement system in which a user measures his/her own biometric data; and
a reading system for generating a reading result by reading a disease prediction and an infectious disease risk prediction and severity based on the data received from the measurement system,
The measurement system is
electrodes and sensors including a left-hand electrode, a right-hand electrode, a PPG sensor, a respiration rate sensor, a body temperature sensor, a blood pressure and a camera sensor;
Signals received from the electrodes and sensors are amplified, noise is removed, and converted into digital signals to convert electrocardiogram data, oxygen saturation measurements, blood pressure, pulse, respiration rate, and body temperature, including vital sign measurements into digital signals. a sensor control unit that outputs;
a user data input unit for receiving basic information of a user including the user's gender, age, and hospital room information; a user interface unit including a data output unit for outputting a result;
a communication unit connected to the reading system through a wired/wireless communication network; and
Receive the electrocardiogram measurement data, the oxygen saturation measurement value, and the vital sign measurement value from the sensor control unit, and transmit the ECG measurement data oxygen saturation measurement value, and the vital sign measurement value together with the user's basic information to the communication unit a central control unit for transmitting to the reading system through the communication unit and providing the reading result from the reading system received through the communication unit to the data output unit;
The system for measuring and reading biometric data, wherein the severity is divided into at least two stages. The method of claim 1,
The sensor and electrode part,
Further comprising a left foot electrode and a right foot electrode,
The left foot electrode and the right foot electrode,
disposed on a footrest or ankle clip embedded in the measurement system or connected to a port of the measurement system;
Lead I (Lead I) ECG signal waveform is obtained from the left electrode and the right electrode,
A biometric data measuring and reading system in which the left foot electrode is connected to the measurement system to obtain a 6-lead electrocardiogram signal waveform from the left foot electrode, the left hand electrode, and the right hand electrode. The method of claim 1,
The reading system is
a database storing the learning data; and
A heart disease prediction result is generated based on the electrocardiogram measurement data using an artificial intelligence-based biometric data reading algorithm that has learned the learning data, and the heart disease prediction result, the oxygen saturation measurement value, the vital sign measurement value, and the Generates an infectious disease risk prediction result based on the user's basic information, and determines the severity based on the user's basic information and past medical records, the reading result of the electrocardiogram data, the oxygen saturation measurement value, and the vital sign measurement value a server that reads and produces a severity reading result;
The learning data includes basic demographic data including age and gender collected from a plurality of external institutions, vital sign data including blood pressure, pulse, respiration rate and body temperature, electrocardiogram data, oxygen saturation data, diagnosis result data, treatment result data , including emergency room patient data, critical care data, surgical patient data, outpatient data, and disease-specific data, including hospital room information, electrocardiogram reading data, severity diagnosis data, infectious disease data, and vital sign reading data; ,
The server is
An alarm signal is generated when the risk of an infectious disease is detected from the user's reading result or the severity is higher than a preset level,
The learning data is periodically updated biometric data measurement and reading system. 4. The method of claim 3,
Further comprising a monitor system connected to the reading system through a communication network,
The monitor system is
monitor the user's electrocardiogram reading result, the oxygen saturation measurement value, the vital sign measurement value, the heart disease prediction result, the infectious disease risk prediction result, and the severity reading result received from the reading system in real time,
When at least one of a deviation from the normal range of the electrocardiogram, a deviation from the normal range of the oxygen saturation, and a deviation from the normal range of each of the vital sign indicators, the infectious disease risk prediction result, and a severity higher than a preset level is received from the reading system A biometric data measurement and reading system for outputting the alarm signal. The method of claim 1,
The biometric data reading system,
a main body device including the left hand electrode, the right hand electrode, the PPG sensor, the respiration rate sensor, the body temperature sensor, the camera sensor, the sensor control unit, the user interface unit, and the central control unit;
and a display of the user interface unit operably coupled to the main body device to open and close the biometric data measurement and reading system. 6. The method of claim 5,
The system for measuring and reading biometric data further comprising a footrest including a left foot electrode and a right foot electrode, and providing a signal received from the left foot electrode and the right foot electrode to the main body device through the communication unit. The method of claim 1,
The biometric data reading system,
a main body fixed to the desk top including the left electrode, the right electrode, the PPG sensor, the respiration rate sensor, the sensor controller, the data input unit of the user interface unit, and the central control unit;
a display having a camera module disposed at an upper end and connected to the main body, the display being fixed to a display support vertically coupled to the desk top plate;
A footrest fixed to the lower plate of the desk is provided, including a left foot electrode and a right foot electrode,
The camera module includes the body temperature sensor and the camera sensor,
The display and the footrest are connected to the main body through a cable or the communication unit connected to the port of the main body to measure and read biometric data. The method of claim 1,
The biometric data reading system,
a main body including the left electrode, the right electrode, the PPG sensor, the respiration rate sensor, the sensor control unit, the user interface unit data input unit, and the central control unit;
a display having a camera module disposed on it and connected to the body;
A footrest including a left foot electrode and a right foot electrode,
The camera module includes the body temperature sensor and the camera sensor,
The body and the display are fixed to an upper portion of the kiosk-type structure, and the footrest is fixed to the lower portion of the kiosk-type structure to measure and read biometric data.

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