KR20200059373A - Prognosis management system based on measuring patient biometric data terminal and cloud server - Google Patents

Abstract

The present invention relates to a system which may measure biometric data including blood pressure or blood sugar levels of patients having body states of high sudden exacerbation risk such as chronic disease in real-time and analyze and recognize a dangerous situation in real-time by a prognosis analysis server to previously warn patients or medical staffs when the dangerous situation occurs. A prognosis management system comprises: a patient terminal and a medical staff terminal for measuring biometric data on a monitoring target patient to transmit the measured biometric data to a server; and a prognosis analysis server to analyze received biometric data when the prognosis analysis server receives the biometric data from the patient terminal. When danger with respect to a body state of the monitoring target patient is predicted as the analysis result, the prognosis analysis server transmits alarm to warn the predicted danger to the patient terminal or the medical staff terminal.

Description

Prognosis management system using mobile terminal and cloud server to measure patient's biometric data {PROGNOSIS MANAGEMENT SYSTEM BASED ON MEASURING PATIENT BIOMETRIC DATA TERMINAL AND CLOUD SERVER}

The present invention is a system for analyzing, predicting, and managing a patient's prognosis, and more specifically, measuring a patient's biological data such as blood pressure or blood sugar level using a mobile terminal, and using the cloud server to analyze the prognosis based on artificial intelligence. It relates to a system that manages.

As the transmission and reception of information through the Internet, such as the Internet, is free, new types of treatment methods such as telemedicine are introduced, and telemedicine can be conducted by doctors using telemedicine equipment for medical examination, devotion, and trial By doing so, it is possible to grasp the patient's physical condition and transmit the test results to the patient online. In cases where periodic and continuous medical services are needed, such as in a poor environment where medical services are not available, or in elderly people with limited mobility, such as Silver Town, which is composed of such elderly people, if telemedicine is used, the patient can be treated without space and time restrictions. It can have the advantage of being able to receive it.

In addition, in the case of diabetes, heart disease, or patients after cancer surgery, which require continuous patient management in addition to these cases, the discomfort that patients have to periodically go to the hospital through remote medical treatment can be resolved and life outside the patient's treatment It has the advantage of being able to easily check the patient's health status throughout.

Particularly, in the case of a chronic patient such as a diabetic patient, a sudden deterioration of physical condition such as hypoglycemic shock may occur. The deterioration of the physical condition can be sufficiently predicted when the patient's real-time biometric data is continuously analyzed. If these risks can be predicted, the patient can not only prescribe himself to the emergency before a risk situation occurs, but also be able to prepare for the risk by asking for help from nearby people or medical personnel in advance.

Accordingly, there is a need to study a system capable of measuring and analyzing real-time biometric data for patients with chronic diseases, and in advance to warn patients or medical staff about the risk of physical condition in advance.

The present invention aims to solve the above and other problems. Another object is to provide a system capable of predicting and preventing sudden physical risk to a chronic patient through real-time bio data measurement.

The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems that are not mentioned will be clearly understood by those skilled in the art from the following description. Will be able to.

According to an aspect of the present invention to achieve the above or other object, the patient terminal for measuring the biological data for the patient to be monitored, and transmitting the measured biological data to the server; Medical staff terminal; And when receiving the biometric data from the patient terminal, including a prognostic analysis server for analyzing the received biometric data, the prognostic analysis server, if the risk is predicted in the body condition of the patient to be monitored as a result of the analysis, the patient It provides a prognosis management system, characterized in that for transmitting a notification alerting the terminal or the medical staff of the predicted risk.

The biometric data measured by the patient terminal is time-series data measured in real time.

The biometric data may include at least one of blood glucose level, blood pressure, and weight of the patient to be monitored.

In this case, the prognostic analysis server may store the past measurement data of the patient to be monitored in a database, and analyze the prognosis by comparing the past measurement data and the received biometric data.

In addition, the prognostic analysis server may use a long-term short-term memory (LSTM) cyclic neural network in analyzing the prognosis.

In analyzing the prognosis, the prognosis analysis server may calculate a risk level of the physical condition as a risky score, and provide the calculated risk score to the patient terminal or the medical staff terminal.

At this time, the medical staff terminal may sort a plurality of patients to be monitored based on the provided Riskie score based on the provided Riskie score, and preferentially examine patients with a high Riskie score.

The prognosis management server may classify or predict a disease for the patient to be monitored by analyzing the bio data.

When explaining the effect of the prognosis management system according to the present invention as follows.

According to at least one of the embodiments of the present invention, there is an advantage of predicting and preventing a sudden physical risk of a chronic patient, such as a diabetic patient, in advance.

In addition, according to at least one of the embodiments of the present invention, there is an advantage that it is possible to easily and simply escape the obesity by systematically managing obesity, etc., on a daily basis.

Further scope of applicability of the present invention will become apparent from the following detailed description. However, various changes and modifications within the spirit and scope of the present invention may be clearly understood by those skilled in the art, and thus, it should be understood that specific embodiments such as detailed description and preferred embodiments of the present invention are given as examples only.

1 is a diagram illustrating a configuration diagram of a prognosis management system 1000 according to an embodiment of the present invention.
FIG. 2 is a block diagram of a patient terminal 100-1, a prognostic analysis server 100-2, and a medical staff terminal 100-3 according to an embodiment of the present invention.
3 is a flowchart illustrating a system control method according to an embodiment of the present invention.
FIG. 4 is a flowchart illustrating a first example of step S303 in which the prognostic analysis server 100-2 analyzes biological data according to an embodiment of the present invention.
FIG. 5 is a flowchart illustrating a second example of step S303 in which the prognostic prediction server 100-2 analyzes biological data according to an embodiment of the present invention.
6 is a table for explaining biological data analysis using body weight according to an embodiment of the present invention.

Hereinafter, exemplary embodiments disclosed herein will be described in detail with reference to the accompanying drawings, but the same or similar elements are assigned the same reference numbers regardless of the reference numerals, and overlapping descriptions thereof will be omitted. The suffixes "modules" and "parts" for components used in the following description are given or mixed only considering the ease of writing the specification, and do not have meanings or roles distinguished from each other in themselves. In addition, in describing the embodiments disclosed in this specification, detailed descriptions of related known technologies are omitted when it is determined that the gist of the embodiments disclosed in this specification may be obscured. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in the present specification, and the technical spirit disclosed in the specification is not limited by the accompanying drawings, and all modifications included in the spirit and technical scope of the present invention , It should be understood to include equivalents or substitutes.

Terms including ordinal numbers such as first and second may be used to describe various components, but the components are not limited by the terms. The terms are used only for the purpose of distinguishing one component from other components.

When an element is said to be "connected" or "connected" to another component, it is understood that other components may be directly connected to or connected to the other component, but there may be other components in between. It should be. On the other hand, when a component is said to be "directly connected" or "directly connected" to another component, it should be understood that no other component exists in the middle.

Singular expressions include plural expressions unless the context clearly indicates otherwise.

In this application, terms such as "comprises" or "have" are intended to indicate the presence of features, numbers, steps, actions, components, parts or combinations thereof described in the specification, but one or more other features. It should be understood that the existence or addition possibilities of fields or numbers, steps, operations, components, parts or combinations thereof are not excluded in advance.

1 is a diagram illustrating a configuration diagram of a prognosis management system 1000 according to an embodiment of the present invention.

According to the illustrated drawings, the prognosis management system 1000 may include a patient terminal 100-1, a prognosis analysis server 100-2, and a medical staff terminal 100-3. According to the illustrated example, the patient terminal 100-1 is illustrated as a mobile terminal, and the medical staff terminal 100-3 is illustrated as a fixed terminal, but the type of the terminal will not be limited.

The patient terminal 100-1, the prognostic analysis server 100-2, and the medical staff terminal 100-3 may be connected through a wired or wireless network.

The patient terminal 100-1 may be a terminal carried by a patient to be monitored, such as a chronic patient. For example, such a terminal may be a device such as a smartphone. That is, for the operation of the system, the device is not separately installed to the patient, but may be operated as a device that can be used routinely, such as a smartphone.

The prognostic analysis server 100-2 may analyze the physical condition of the patient to be monitored based on data transmitted from the patient terminal 100-1. In particular, the prognosis management server may classify or predict a disease for the patient to be monitored by analyzing the biological data using a long-term short-term memory (LSTM) circulatory neural network.

The medical staff terminal 100-3 may provide the medical staff with measurement data on the patient to be monitored or an analysis result by the prognostic analysis server 100-2.

FIG. 2 is a block diagram of a patient terminal 100-1, a prognostic analysis server 100-2, and a medical staff terminal 100-3 according to an embodiment of the present invention. In FIG. 2, the patient terminal 100-1, the prognostic analysis server 100-2, and the medical staff terminal 100-3 are collectively referred to as the terminal 100, and will be described in one block diagram.

The terminal 100 may include a wireless communication unit 110, a sensing unit 140, an output unit 150, a memory 170, a control unit 180, and a power supply unit 190. The components illustrated in FIG. 2 are not essential to the implementation of the terminal 100, and thus the terminal 100 described herein may have more or fewer components than those listed above.

More specifically, the wireless communication unit 110 among the components, the wireless communication between the terminal 100 and the wireless communication system, between the terminal 100 and another terminal 100, or between the terminal 100 and an external server It may include one or more modules to enable. Further, the wireless communication unit 110 may include one or more modules connecting the terminal 100 to one or more networks.

The wireless communication unit 110 may include at least one of a mobile communication module 112, a wireless Internet module 113, and a short-range communication module 114.

The wireless Internet module 113 refers to a module for wireless Internet access, and may be built in or external to the terminal 100. The wireless Internet module 113 is configured to transmit and receive wireless signals in a communication network according to wireless Internet technologies.

The mobile communication module 112 includes technology standards or communication methods for mobile communication (eg, Global System for Mobile Communication (GSM), Code Division Multi Access (CDMA), Code Division Multi Access 2000 (CDMA2000), EV -Enhanced Voice-Data Optimized or Enhanced Voice-Data Only (DO), Wideband CDMA (WCDMA), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), LTE-A (Long Term Evolution-Advanced) transmits and receives wireless signals to and from at least one of a base station, an external terminal, and a server on a mobile communication network constructed according to (Long Term Evolution-Advanced).

Wireless Internet technologies include, for example, WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Wi-Fi (Wireless Fidelity) Direct, DLNA (Digital Living Network Alliance), WiBro (Wireless Broadband), WiMAX (World) Interoperability for Microwave Access (HSDPA), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), Long Term Evolution-Advanced (LTE-A), and the wireless Internet module ( 113) transmits and receives data according to at least one wireless Internet technology in a range including the Internet technology not listed above.

In view of the wireless Internet access through WiBro, HSDPA, HSUPA, GSM, CDMA, WCDMA, LTE, LTE-A, etc., through the mobile communication network, the wireless Internet module 113 that performs wireless Internet access through the mobile communication network ) May be understood as a type of the mobile communication module 112.

The short-range communication module 114 is for short-range communication, Bluetooth ™, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, NFC (Near Field Communication), by using at least one of Wi-Fi (Wireless-Fidelity), Wi-Fi Direct, Wireless USB (Wireless Universal Serial Bus) technology, it can support short-range communication. The short-range communication module 114 is between the terminal 100 and the wireless communication system, between the terminal 100 and another terminal 100, or between the terminal 100 and another terminal through wireless area networks. (100, or an external server) can support wireless communication between the network is located. The short-range wireless communication network may be wireless personal area networks.

The sensing unit 140 may include one or more sensors for sensing at least one of information in the terminal 100, surrounding environment information surrounding the terminal 100, and user information. For example, the sensing unit 140 according to an embodiment of the present invention may further include a sensor for measuring biological data of a patient to be monitored. Biometric data is data on various biological signals obtained from a target human body, and may include, for example, blood pressure, blood sugar or body weight. Meanwhile, the terminal 100 disclosed in this specification may combine and use information sensed by at least two or more of these sensors.

The output unit 150 is for generating output related to time, and may include a display unit. The display unit may form a mutual layer structure with the touch sensor or may be integrally formed, thereby realizing a touch screen. The touch screen may function as a user input unit that provides an input interface between the terminal 100 and the user, and at the same time, provide an output interface between the terminal 100 and the user.

Also, the memory 170 stores data supporting various functions of the terminal 100. The memory 170 may store a number of application programs or applications running in the terminal 100 and data and commands for the operation of the terminal 100. At least some of these applications can be downloaded from external servers via wireless communication. In addition, at least some of these application programs may exist on the terminal 100 from the time of shipment for the basic functions of the terminal 100 (for example, an incoming call, a calling function, a message reception, and a calling function). Meanwhile, the application program may be stored in the memory 170 and installed on the terminal 100 to be driven by the controller 180 to perform an operation (or function) of the terminal 100.

In particular, the memory 170 according to an embodiment of the present invention may include a database that systematically stores a large amount of data. Furthermore, such a database stores biometric data, which will be described later, in a big data format, and utilizes it for prognosis prediction through machine learning or deep learning.

In addition to the operations related to the application program, the controller 180 generally controls the overall operation of the terminal 100. The controller 180 may provide or process appropriate information or functions to the user by processing signals, data, information, etc. input or output through the above-described components or by driving an application program stored in the memory 170.

In addition, the controller 180 may control at least some of the components discussed with reference to FIG. 2 to drive the application program stored in the memory 170. Further, the controller 180 may operate by combining at least two or more of the components included in the terminal 100 to drive the application program.

Under the control of the controller 180, the power supply unit 190 receives external power and internal power to supply power to each component included in the terminal 100. The power supply unit 190 includes a battery, and the battery may be a built-in battery or a replaceable battery.

At least some of the components may operate in cooperation with each other to implement the operation, control, or control method of the terminal 100 according to various embodiments described below. Also, the operation, control, or control method of the terminal 100 may be implemented on the terminal 100 by driving at least one application program stored in the memory 170.

3 is a flowchart illustrating a system control method according to an embodiment of the present invention.

In S301-1, the patient terminal 100-1 may measure biometric data from the patient to be monitored and transmit the measured biometric data to the prognostic analysis server 100-2 (step S302).

Here, the biometric data measured by the patient terminal 100-1 may be time-series data measured in real time. In addition, the biological data may include at least one of blood glucose level, blood pressure, and weight of the patient to be monitored.

In S302-2, the patient terminal 100-1 may receive user data from a user and similarly transmit it to the prognostic analysis server 100-2.

Here, the user data refers to various information that may affect changes in the user's biological data, such as information about a user's lifestyle or information on food ingested.

The prognostic analysis server 100-2 analyzes the current physical condition of the patient to be monitored (step S303) based on the received biometric data or user data.

Particularly, in the present invention, biometric data measured from a large number of patients are continuously converted into big data, stored in a database, and compared with the data stored in the database and the biometric data measured in real time. Prognosis is predicted and suggested to prevent dangerous conditions.

In addition, in one embodiment of the present invention, in analyzing the prognosis, the prognostic analysis server may use a long-short term memory (LSTM) cyclic neural network suitable for analysis of signals measured in time series. have.

The method of analyzing in step S303 is described with reference to FIGS. 4 and 5.

4 is a flowchart illustrating a first example of a step S303 in which the prognostic analysis server 100-2 analyzes biological data according to an embodiment of the present invention.

In the first example, a blood glucose level measured from a patient to be monitored is received (step S401), and analysis is performed.

In step S402, the prognostic analysis server 100-2 performs analysis using the past blood glucose change value stored in the database. Particularly, the database may include data measured from the patient to be monitored as well as data measured from other people.

The prognostic analysis server 100-2 analyzes the prognosis of the patient to be monitored using the past blood glucose level change numerical analysis (step S403). Based on the analyzed prognosis, it is determined whether the patient's current state is dangerous (step S404), and if it is not dangerous, a general analysis result is returned to the patient terminal 100-1 or the medical staff terminal 100-3 (S404). And, if it is dangerous, it may be possible to reply (step S405) the analysis result including the warning.

In FIG. 4, an analysis based on blood sugar has been described, but an analysis based on blood pressure may also be possible as described below.

FIG. 5 is a flowchart illustrating a second example of step S303 in which the prognostic prediction server 100-2 analyzes biological data according to an embodiment of the present invention.

In the second example, blood pressure values (SBP, DBP, etc.) measured from a patient to be monitored are received (step S501), and analysis is performed. What is systolic blood pressure (SBP), systolic blood pressure. Blood pressure in a contracted state of the heart, which means the highest blood pressure, and diastolic blood pressure (DBP) is diastolic blood pressure. The blood pressure when the heart expands, the lowest blood pressure.

In step S502, the prognostic analysis server 100-2 performs an analysis using the past blood pressure change value stored in the database. Particularly, the database may include data measured from the patient to be monitored as well as data measured from other people.

The prognosis analysis server 100-2 analyzes the prognosis of the patient currently monitored using the past blood pressure change numerical analysis (step S503). Based on the analyzed prognosis, it is determined whether the patient's current state is dangerous (step S504), and if it is not dangerous, a general analysis result is returned to the patient terminal 100-1 or the medical staff terminal 100-3 (S504). And, if it is dangerous, it will be possible to reply (step S505) the analysis results including the warning.

Returning to FIG. 3 again, the prognostic analysis server 100-2 delivers the analyzed results to the patient terminal 100-1 as described above (S304-1) or delivers it to the medical staff terminal 100-3 (S304). -2).

The patient terminal 100-1 may output the analysis result for the patient based on the analysis result received in step S304-1 (S305-1). Similarly, the medical staff terminal 100-3 may output the analysis result for the patient based on the analysis result received in step S304-2 (S305-2).

On the other hand, the prognostic analysis server 100-2 may not only output a warning, but may quantify the degree of risk of a patient with a score and deliver the numerical value to the terminals 100-1 and 100-2. will be. This is because it is possible to grasp the degree of risk, and especially when the medical staff judges, it is possible to quickly determine who among the many patients needs the most urgent action.

Therefore, the prognostic analysis server 100-2 calculates a risk score, which quantifies a patient's risk, based on the biometric data received in step S302, and then the patient terminal 100-1 or It can be delivered to the medical staff terminal 100-3.

Upon receiving this, the medical staff terminal 100-3 outputs the analysis result (S305-2), and can sort the risks using a plurality of received Riskey scores and preferentially treat emergency patients. will be.

6 is a table for explaining biological data analysis using body weight according to an embodiment of the present invention.

According to the illustrated drawings, the body mass index (BMI) is measured based on the patient's weight measurement data, and the patient's body is measured based on the measured BMI as 'UNDER WEIGHT', 'NORMAL', 'OVER WEIGHT' And 'OBESE'. This classification is only an example, and the present invention will not be limited to specific classification items.

Depending on each classification, different advice phrases could be printed on the patient. In particular, in the present invention, it is proposed to apply the method of calculating 'Normal weight' differently according to the classification (additional formula) and to calculate according to the method and include it in the advice phrase to the user.

In the example of FIG. 6, the Riskey score may be calculated using BMI by Equation 1 below.

The calculated Riskie score is transmitted to the medical staff terminal 100-3 or the patient terminal 100-1 as described above, so that it is possible to perform guidance on the current dangerous state.

The embodiment of the prognosis management system according to the present invention has been described above, but this is described as at least one embodiment, whereby the technical spirit of the present invention and its configuration and operation are not limited. The scope of the idea is not limited / limited by the drawings or the description referring to the drawings. In addition, the concepts and embodiments of the invention presented in the present invention may be used by a person having ordinary knowledge in the technical field to which the present invention pertains as a basis for modifying or designing with other structures in order to perform the same purpose of the present invention. , The equivalent structure modified or modified by a person having ordinary knowledge in the technical field to which the present invention pertains is bound by the technical scope of the present invention described in the claims, and does not depart from the spirit or scope of the invention described in the claims. Various changes, substitutions, and changes are possible within the limits.

Claims (8)

A patient terminal for measuring biometric data for a patient to be monitored and transmitting the measured biometric data to a server;
Medical staff terminal; And
When receiving the biometric data from the patient terminal, including a prognostic analysis server for analyzing the received biometric data,
The prognostic analysis server, characterized in that when the result of the analysis, the risk to the body condition of the patient to be monitored is predicted, sending a notification warning the predicted risk to the patient terminal or the medical staff terminal,
Prognosis management system. According to claim 1,
Biometric data measured in the patient terminal is characterized in that the time-series data measured in real time,
Prognosis management system. The method of claim 2, wherein the biometric data,
Characterized in that it comprises at least one of the blood glucose, blood pressure and weight of the patient to be monitored,
Prognosis management system. According to claim 1, wherein the prognostic analysis server,
The past measurement data of the patient to be monitored is stored in a database,
Characterized in that, by analyzing the prognosis by comparing the past measurement data and the received biometric data,
Prognosis management system. According to claim 4, The prognosis analysis server in analyzing the prognosis,
Characterized in that using a long-term memory (LSTM: Long-Short term Memory) cyclic neural network,
Prognosis management system. The method of claim 5, wherein the prognosis analysis server calculates a risk level of the physical condition in analyzing the prognosis as a risky score,
Characterized in that, providing the calculated risk score to the patient terminal or the medical staff terminal,
Prognosis management system. The method of claim 6, wherein the medical staff terminal,
On the basis of the provided Risky score, a plurality of patients to be monitored can be sorted based on the provided Risky score, characterized in that it is possible to preferentially examine patients with a high Risky score,
Prognosis management system. According to claim 1,
The prognosis management server, characterized in that to classify or predict the disease for the patient to be monitored by analyzing the biological data,
Prognosis management system.

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