KR102405961B1 - Method for analyzing information of patient identified by image, server thereof, and system thereof - Google Patents

Abstract

In one embodiment of the present invention, receiving an image from a nurse terminal, identifying a patient from information included in the received image, determining whether the identified patient is a patient for a chronic disease, and the identification If the patient is a patient for a chronic disease, analyzing the biosignal of the identified patient based on the first criterion, otherwise analyzing the biosignal of the identified patient based on the second criterion, and the first Disclosed is a method for analyzing information of a patient identified based on an image, comprising the step of storing a result analyzed according to one of a criterion and the second criterion.

Description

Method for analyzing information of patient identified by image, server thereof, and system thereof}

The present invention relates to a method for analyzing patient information, and more particularly, to a method for accurately analyzing patient information received in the form of an image, and a server and system for implementing the method.

Various bio-signals obtained from time to time from a patient admitted to a hospital are collected by a doctor or a nurse and used to diagnose the patient. Nurses frequently access patients' beds and manually record the patient's bio-signals output from the medical terminal or type them into the terminal to manage them, but this data management method only increases the nurse's workload excessively.

There is a need for an innovative method that enables efficient diagnosis for each patient by reflecting the unique characteristics of patients with chronic diseases while minimizing the unnecessary workload of nurses.

Republic of Korea Patent Publication No. 10-2006-0017491 (2006.02.23)

SUMMARY OF THE INVENTION An object of the present invention is to provide a method that enables a nurse to easily transmit and analyze biosignal information of a patient to a server.

A method according to an embodiment of the present invention for solving the technical problem, receiving an image from a nurse terminal, and identifying a patient from information included in the received image; determining whether the identified patient is a patient for a chronic disease; if the identified patient is a patient with a chronic disease, analyzing the biosignal of the identified patient based on a first criterion, otherwise analyzing the biosignal of the identified patient based on a second criterion; and storing a result analyzed according to one of the first criterion and the second criterion.

In the method, a result of analysis according to one of the first criterion and the second criterion may be transmitted to the nurse terminal, and the result may be controlled to be displayed on the nurse terminal.

In the method, the received image is at least two or more, and the information included in the received image includes personal information for identifying who the patient is and biosignal information displayed on the identified patient's medical terminal. can be

In the method, the received image is a first image and a second image, and the step of identifying the patient includes reading personal information from the first image to identify who the read patient is, and the biosignal The analyzing may include reading the identified biosignal of the patient from the second image and analyzing the read biosignal.

In the method, based on the analyzed result, result values corresponding to normal and abnormal may be output, and the output result may be controlled to be displayed on the nurse terminal.

In the method, the bio-signals are at least two kinds of bio-signals, and the analyzing of the bio-signals includes analyzing the two or more bio-signals for each bio-signal, and storing the results includes the analyzed bio-signals. For each biosignal, one of a first output corresponding to normal and a second output corresponding to abnormality may be divided and stored.

Server according to another embodiment of the present invention for solving the above technical problem, a communication unit for communicating with a nurse terminal; processing unit; and a database for storing data processed by the processing unit, wherein the processing unit receives an image from the nurse terminal, identifies a patient from information included in the received image, and the identified patient has a chronic disease to determine whether the patient is a patient, and if the identified patient is a patient for a chronic disease, analyzes the biosignal of the identified patient based on a first criterion, otherwise the identified patient based on a second criterion , and stores the analysis result according to one of the first criterion and the second criterion in the database.

A system according to another embodiment of the present invention for solving the above technical problem is an image-based patient information analysis system consisting of a nurse terminal and a server, wherein the nurse terminal includes a label including the patient's personal information and the patient Generates an image by photographing the display unit of the medical terminal connected to, the server receives the image from the nurse terminal, identifies the patient from the information included in the received image, The identified patient for chronic disease It is determined whether the patient is a patient, and if the identified patient is a patient for a chronic disease, the biosignal of the identified patient is analyzed based on the first criterion, otherwise the biosignal of the identified patient based on the second criterion The signal is analyzed, and the analysis result according to one of the first criterion and the second criterion is stored.

An embodiment of the present invention may provide a computer-readable recording medium storing a program for executing the method.

According to the present invention, it is possible to conveniently read the biosignals of patients suffering from chronic diseases, store them in the EMR server and manage them, so that the workload of doctors or nurses can be greatly reduced.

1 is a diagram schematically showing an entire system for implementing the present invention.
FIG. 2 is a block diagram illustrating an example of a server for implementing the system described in FIG. 1 .
3 is a flowchart illustrating an example of a method according to the present invention.
4 is a flowchart for explaining another example of the method according to the present invention.
7 is a diagram schematically showing an example of a result of the server analyzing the image received from the nurse terminal.
8 is a diagram schematically illustrating a process in which a nurse terminal captures a medical terminal and acquires an image.

Since the present invention can apply various transformations and can have various embodiments, specific embodiments are illustrated in the drawings and described in detail in the detailed description. Effects 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 drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various forms.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, and when described with reference to the drawings, the same or corresponding components are given the same reference numerals, and the overlapping description thereof will be omitted. .

In the following embodiments, terms such as first, second, etc. are used for the purpose of distinguishing one component from other components without limiting the meaning.

In the following examples, the singular expression includes the plural expression unless the context clearly dictates otherwise.

In the following embodiments, terms such as include or have means that the features or components described in the specification exist, and the possibility of adding one or more other features or components is not excluded in advance.

In cases where certain embodiments may be implemented differently, a specific process sequence may be performed differently from the described sequence. For example, two processes described in succession may be performed substantially simultaneously, or may be performed in an order opposite to the order described.

1 is a diagram schematically showing an entire system for implementing the present invention.

Referring to FIG. 1 , the system 1 according to the present invention has a structure in which a nurse terminal 110 , a medical terminal 130 , and a server 200 are connected through a communication network 150 .

In FIG. 1 , the nurse terminal 110 refers to a terminal used by nurses who care for patients in a hospital. The nurse terminal 110 refers to an electronic device equipped with a communication module capable of communicating with the server 200 .

The nurse terminal 110 includes an input device for receiving a nurse's input, an output device (display) for visually outputting an input of the nurse terminal 110 or a processing result of the terminal, and a communication module capable of communicating with an external device. Since it means a smart device, it is not limited in size or type as long as it includes only the above-described input device, output device and communication module. For example, although the nurse terminal 110 is shown in the form of a smartphone in FIG. 1 , the nurse terminal 110 may be a unique terminal custom-made according to the characteristics of each hospital's work.

The nurse terminal 110 may include a camera module 111 . In FIG. 1 , the camera module 111 is illustrated as being separated from the nurse terminal 110 , but this is for convenience of explanation, and the camera module 111 is physically or logically included in the nurse terminal 110 . can be implemented. Alternatively, the camera module 111 may be an independent module that can be connected to or disconnected from the nurse terminal 110 by wire or wirelessly.

Also, in FIG. 1 , the medical terminal 130 refers to a device that receives sensing results from various sensors attached to a patient's body and visually displays the received results. For example, the medical terminal 130 may visually output the patient's pulse, blood pressure, respiration rate, respiration frequency, SpO2 (oxygen saturation), and the like. When the nurse takes a picture of the display unit (display unit) of the medical terminal 130 with the camera module 111 provided in the nurse terminal 110 , the nurse terminal 110 displays the pulse rate of the patient displayed on the display unit of the medical terminal 130 . , blood pressure, respiration rate, respiration frequency, SpO2, etc. can be acquired as image information. The image acquired by the nurse terminal 110 is transmitted to the server 200 through the communication network 150 .

The server 200 analyzes the image received from the nurse terminal 110, stores the analysis result, or retransmits at least some of the analysis result to the nurse terminal 110, so that the nurse through the nurse terminal 110, the nurse terminal (110) allows to check the result of analyzing the acquired image. An integrated management program (integrated management app) is installed in the server 200 , and according to an embodiment, a part of the integrated management program is implemented in the form of a client driven by the nurse terminal 110 to the nurse terminal 110 . can be installed on

Since a unique session is established between the server 200 and the nurse terminal 110 , terminals other than the authenticated nurse terminal 110 cannot communicate with the server 200 . In addition, according to an embodiment, even if it is an authenticated nurse terminal 110 , when a person designated as a nurse who can use the nurse terminal 110 logs in to the nurse terminal 110 through a legal procedure, However, a session may be established between the server 200 and the nurse terminal 110 .

The communication network 150 performs a function of connecting the nurse terminal 110 and the server 200, and may include various wired and wireless communication networks such as a data network, a mobile communication network, the Internet, and an intranet.

FIG. 2 is a block diagram illustrating an example of a server for implementing the system described in FIG. 1 .

Referring to FIG. 2 , it can be seen that the server 200 according to an embodiment of the present invention includes a database 210 , a communication unit 230 , a processing unit 250 , and an output unit 270 . The server 200 of FIG. 2 may be an Electronic Medical Record (EMR) server.

The server 200 according to an embodiment of the present invention may correspond to or include at least one or more processors. Accordingly, the server 200 and the communication unit 230 , the processing unit 250 , and the output unit 270 included in the server 200 are included in a hardware device such as a microprocessor or a general-purpose computer system. can be driven by

The name of each module included in the server 200 shown in FIG. 2 is arbitrarily named in order to intuitively explain the representative function performed by each module. When the server 200 is actually implemented, each module is A name different from the name described in 2 may be assigned.

In addition, the number of modules included in the server 200 of FIG. 2 may vary each time according to an embodiment. More specifically, the server 200 of FIG. 2 includes a total of three modules, but according to an embodiment, at least two or more modules are integrated into one module, or at least one or more modules are separated into two or more modules. It may be implemented in the form.

The database 210 stores various data necessary for the server 200 to operate. As an example, the database 210 stores an integrated management program for controlling the operation of the server 200 , and the database 210 receives and stores the data received by the communication unit 230 from the nurse terminal 110 . can

The communication unit 230 communicates with the nurse terminal 110 .

The processing unit 250 processes data received by the communication unit 230 and data to be transmitted by the communication unit 230 to the nurse terminal 110 .

As an embodiment, the processing unit 250 combines the data received by the communication unit 230 with information stored in the database 210 and processes the communication unit 230 and the output unit to implement the method according to the present invention. 270 may perform a function of issuing a command to operate properly.

The function performed by the processing unit 250 is not limited to a specific function, and although the processing unit 250 is illustrated as a single module in FIG. 2 , according to the process of the processing unit 250 , the processing unit 250 is configured as a plurality of modules. can be subdivided.

The output unit 270 receives a command from the processing unit 250 and performs a function of calculating and outputting various data.

2 is a diagram for generally explaining the functions of the database 210 , the communication unit 230 , the processing unit 250 , and the output unit 270 as detailed modules constituting the server 200 . The operating characteristics will be described later with reference to FIGS. 3 and 4 .

3 is a flowchart illustrating an example of a method according to the present invention.

FIG. 3 may be implemented by the server 200 described with reference to FIG. 2 , and will be described below with reference to FIGS. 1 and 2 .

First, when a nurse shoots the display unit of the medical terminal 130 with the camera module 111 of the nurse terminal 110, the nurse terminal 110 acquires an image including information about the patient's biosignals. In addition, the nurse terminal 110 may transmit the acquired image to the communication unit 230 of the server 200 according to the setting of the installed application or the input of the nurse, and the processing unit 250 may include the image included in the received image. The information identifies the patient (S310).

In step S310 , the nurse may photograph the label of the hospital bed being used by the patient with the camera module 111 of the nurse terminal 110 , and then photograph the display unit of the medical terminal 130 . The patient's personal information, such as the patient's management number, the patient's name, the patient's gender, the patient's age, etc., is recorded on the label on the bed, and the image for the label on the bed is processed by the processing unit 250 of the server 200 by the patient. Allows you to identify who you are.

The processing unit 250 may determine whether the patient primarily identified in step S310 is a patient suffering from a chronic disease (S320).

In general, sudden patients who have recently been hospitalized for various accidents or injuries or receive one-time treatment, and persistent patients who stay for a long time in the hospital for long-term treatment due to old age or long-term treatment visit the hospital. In addition, there are patients suffering from chronic diseases such as high blood pressure, hypotension, and arrhythmias as patients that can be included in both breakthrough patients and persistent patients. Considering this, it was designed to accurately analyze the patient's biosignals and improve the nurse's work convenience.

The processing unit 250 applies an optical character recognition (OCR) technique to the image received from the nurse terminal 110, extracts characters, and compares the extracted characters with information stored in the database 210, It may be determined that the identified patient is a patient suffering from a chronic disease.

The processing unit 250 determines whether the identified patient is a chronic disease patient (S330), and if the patient is a chronic disease patient, analyzes the biosignal of the identified patient based on the first criterion (S340).

Here, the first criterion refers to an analysis algorithm implemented inside the processing unit 250 in consideration of the unique characteristics of chronic disease patients. The first reference may be a basic protocol of a black box that, when a patient's bio-signal is input, analyzes the input bio-signal and outputs an analysis result. In addition, when the processing unit 250 includes a learning model for performing machine learning, the first criterion may be a value or a function set in order for the learning model to stop learning. For example, if the machine learning algorithm included in the learning model is implemented as an autoencoder that extends an artificial neural network (ANN), the first criterion is a loss function that is internally set to stop the iterative learning of the autoencoder. (loss function). In addition to the above-described examples, the first standard refers to various standards set in the processing unit 250 in order to analyze a biosignal of a chronic disease patient, and is distinguished from a second standard to be described later.

On the other hand, if the patient is not a chronic disease patient in step S330, the processing unit 250 analyzes the biosignal of the identified patient based on the second criterion (S350). The second criterion is an algorithm set inside the processing unit 250, similar to the first criterion, and refers to a criterion for analyzing a biosignal for a patient who can be discharged through a one-time treatment, not a chronic disease patient, but a sudden patient, It is different from the first criterion.

The processing unit 250 stores the result of the analysis based on the first criterion or the second criterion in steps S340 and S350 in the database 210 (S360). The stored patient information may be read limitedly by an administrator (doctor, nurse) who has access to the server 200 , and some of the stored patient information may be transmitted to the nurse terminal 110 .

As described in FIG. 3, the present invention analyzes the received image, extracts information for identifying a patient and information on a biosignal for diagnosing a patient's health condition, and provides information on the extracted biosignal By analyzing and storing according to the first criterion or the second criterion, it is possible to build a digital database for the patient's condition information. In particular, according to the present invention, if the patient is identified as a chronic disease patient after identifying the patient with the information included in the image, the biosignal is based on the first criterion designed for chronic disease patients, not the second standard, which is a general standard. By analyzing , an accurate analysis result can be obtained and stored in the server 200 .

For example, the processing unit 250 may classify a patient having a high body temperature by applying the second criterion if the patient having an average body temperature of 37.8 degrees is a normal patient, but if a patient suffering from chronic kidney disease, It can be classified as a patient with normal body temperature. This is the result of the processing unit 250 determining the patient suffering from chronic renal failure as a chronic disease patient, applying the first criterion and analyzing, in general, since the patient suffering from chronic renal failure takes a calcium blocker, a general person tend to maintain a high body temperature compared to

4 is a flowchart for explaining another example of the method according to the present invention.

4 is a flowchart for explaining the present invention described in FIG. 3 in more detail. Like FIG. 3 , it may be implemented by the server 200 described in FIG. 2 . Hereinafter, descriptions overlapping with those described in FIG. 3 will be omitted.

First, the communication unit 230 of the server 200 receives the first image and the second image from the nurse terminal 110, and the processing unit 250 transmits the information included in the first image received by the communication unit 230 to the patient. is identified (S410).

In step S410 , the first image may be an image of the patient's label photographed by the nurse terminal 110 , and the second image may be an image of the display unit of the medical terminal 130 photographed by the nurse terminal 110 . In FIG. 4 , the first image and the second image are limited, but depending on the embodiment, the number of images photographed by the nurse terminal 110 and transmitted to the server 200 may be more or less than two.

The processing unit 250 determines whether the identified patient is a patient suffering from a chronic disease (hereinafter, "chronic disease patient") (S420).

The processing unit 250 determines whether the identified patient is a chronic disease patient (S430), and if the identified patient is a chronic disease patient, analyzes the biosignal of the identified patient based on the first criterion (S440), According to the effect of the included chronic disease drug, the analysis result of the biosignal is corrected (S450).

If the identified patient is not a chronic disease patient, the processing unit 250 analyzes the identified patient's biosignal based on the second criterion (S460).

The processing unit 250 may store the result analyzed through one of steps S450 and S460 in the database 210 of the server 200 and transmit at least some of the information stored in the nurse terminal 110 (S470). ).

Hereinafter, a process in which the processing unit 250 analyzes the patient's biosignal according to the first criterion or the second criterion in steps S440 to S460 will be described in detail.

First, the image received from the nurse terminal 110 may include information on a plurality of bio-signals. For example, in the image received from the nurse terminal 110, at least two of biosignal information for the patient's systolic blood pressure value, diastolic blood pressure value, pulse, blood sugar, body temperature, hourly respiration rate, respiration frequency, and oxygen saturation (SpO2) More than one may be included.

The processing unit 250 may read the received image and, if the patient is a chronic disease patient, may analyze a plurality of biosignals included in the image according to the first criterion for each biosignal. For example, if the received image includes information on the patient's blood pressure and body temperature, the processing unit 250 applies an algorithm for analyzing blood pressure as the first reference and an algorithm for analyzing body temperature as the first reference, respectively. , it is possible to analyze the patient's biosignals.

Here, the first criterion depends on the chronic disease the patient suffers from. For example, if the chronic disease the patient is suffering from is chronic renal failure, the first criterion is a criterion set in consideration of the general characteristics of the chronic renal failure patient. If the chronic disease the patient is suffering from is hypertension, the first criterion is the It is a standard set in consideration of general characteristics. Since the first criterion is a criterion set in consideration of the characteristics of the chronic disease, by the analysis performed in step S440, the value of the biosignal, which can be generally diagnosed as abnormal, may also be diagnosed as normal when the chronic disease is considered.

As an extended embodiment of step S440, the processing unit 250 may correct the analysis result of the biosignal according to the effect of the chronic disease drug included in the first criterion (S450), and the correction of step S450 is the reliability of the analysis result can be further improved.

chronic disease drug environmental factors Related factors Explanation chronic renal failure ACE inhibitors X Blood pressure Orthostatic hypotension possible X pulse tachycardia or bradycardia beta sympathetic blockers X blood sugar Hypoglycemia not observed calcium channel blockers,
alpha 1 receptor blockers X temperature elevated body temperature X Blood pressure cause hypotension X pulse tachycardia Alpha 2 antagonists X temperature elevated body temperature X pulse bradycardia X Blood pressure Orthostatic hypotension possible

Table 1 is a table exemplarily listing one element constituting the first criterion of the processing unit 250 . Hereinafter, with reference to Table 1, the operating principle of the processing unit 250 will be described.

The processing unit 250 primarily analyzes the biosignal information based on the first criterion corresponding to chronic renal failure, and then determines whether the patient's biosignal is normal or abnormal in a state in which suffering from chronic renal failure is considered. can do. In addition, the processing unit 250 secondarily refers to the database 210 or through the nurse's input input to the nurse terminal 110, by identifying which drugs are administered to the patient in Table 1, Depending on the effect, the analysis result of the biosignal may be corrected. For example, the processing unit 250 determines that the body temperature of the patient A is higher than that of a normal person and is higher than that of a general chronic renal failure patient, so that the patient A has a history of administering a calcium channel blocker that raises the body temperature. The body temperature determined to be abnormal can be corrected to normal.

As another example, if the body temperature of chronic renal failure patient B is higher than that of other patients, and patient B has not received any of the alpha 1 receptor blockers, calcium channel blockers, and alpha 2 antagonists that cause body temperature rise, the processing unit 250 is Patient B can be judged abnormal.

chronic disease drug environmental factors Related factors Explanation asthma salbutamol
(bronchial tubes for asthma
expander) X pulse tachycardia Blood pressure high blood pressure propranolol,
β-adrenergic blocker
(blood pressure medication) Taking oral medications for asthma with a previous diagnosis of hypertension Breath bronchospasm,
cause tachypnea oxygen saturation Decreased oxygen saturation theophylline,
aminophylline
(bronchodilators) X pulse tachycardia Blood pressure lowered blood pressure Breath cause tachypnea X night time oxygen saturation Decreased oxygen saturation

Table 2 is a table exemplarily listing another element constituting the first criterion of the processing unit 250 . Hereinafter, with reference to Table 1, the operating principle of the processing unit 250 will be described. Comparing Table 2 with Table 1, it can be seen that a parameter called an environmental factor is further added. Specifically, in the case of asthma, it is described in Table 2 that environmental factors act like drugs, and as the oxygen saturation of asthma patients decreases during the night time, asthma tends to worsen. The processing unit 250, through the first criterion, after first analyzing the biosignal, secondarily grasps what the drug (or environmental factor) administered to the patient is, and provides related elements and explanations of the administered drug. Referring to, it is possible to correct the analysis result of the biosignal, and finally determine whether the biosignal of the patient is normal or abnormal based on the corrected result.

The processing unit 250 may physically or logically include a learning model for accurately performing the above process.

Next, a description will be given of step S460.

When it is determined that the patient is not a chronic disease patient, the processing unit 250 may analyze the patient's biosignal based on the second criterion (S460).

Since the patient is not a chronic disease patient in step S460, the second standard, which is a general patient biosignal analysis method, may be applied.

The second criterion may be a criterion for body temperature, blood pressure, pulse, respiration, and oxygen saturation described in Tables 1 and 2.

Since a person's body temperature changes depending on gender, age, stress, surrounding environment, and biological rhythm for 24 hours, the processing unit 250 may determine whether the patient's body temperature is normal by referring to the data on the change in body temperature. Data on changes in body temperature may be data stored in the database 210 in the form of a table. For example, data that a newborn baby has a body temperature of 36.5 to 37.5 degrees and an elderly person 70 years or older has a body temperature of 35.6 to 37.2 degrees may be reference data.

In addition, since a person's blood pressure varies depending on gender, age, food intake, weight, etc., the processing unit 250 may determine whether the patient's blood pressure is normal by referring to the blood pressure data. Data on blood pressure, like body temperature, may be data stored in the database 210 in the form of a table.

In addition, since a person's pulse changes according to an increase in body temperature, an underlying disease, age, etc., the processing unit 250 may determine whether the patient's pulse is normal by referring to the pulse data. Data on the pulse may also be data stored in the database 210 in the form of a table, like body temperature.

In addition, since the respiration of a person varies depending on the tendency of the body temperature to rise and the degree to which the body temperature exceeds the normal range, the processing unit 250 may determine whether the respiration of the patient is normal with reference to the respiration data. Data on respiration, like body temperature, may be data stored in the database 210 in the form of a table.

In addition, since the oxygen saturation of a person is 90 to 100%, the processing unit 250 may determine whether the oxygen saturation of the patient is normal based on the reference range.

As described above, various criteria for the processing unit 250 to determine whether the biosignal is normal or abnormal may all correspond to the second criterion.

The processing unit 250 stores and manages the results of the analysis in steps S440 to S460 in the database 210 of the server 200, and at the same time transmits at least some of the information stored in the nurse terminal 110 (S470) , it is possible to induce the nurse to check the information output to the nurse terminal 110 and give an instruction to the patient to pay attention to a specific action.

As described above, the first criterion is not only a criterion that reflects the unique characteristics of a chronic disease itself, but also a criterion for judging the patient's normal state by considering the effect of the drug and whether the drugs are actually administered to the patient, and the second criterion The standard refers to a standard for objectively analyzing a patient's biosignal regardless of the disease the patient is suffering from. The present invention is an invention specialized for patients with chronic diseases as described above, and enables information that accurately reflects the patient's condition to be stored in the EMR server.

5 is a diagram schematically illustrating a process in which a nurse-only app installed in a nurse terminal recognizes a nurse's face.

The nurse executes the nurse-only application (nurse-only app) installed in the nurse terminal, and may input the nurse's face as authentication information in order to log in to the nurse-only app.

As shown in FIG. 5 , when an input image of a nurse is captured and collected by a camera module of the nurse terminal, the nurse-only app detects the nurse's face from the input nurse's image and , identifies major parts such as eyes, nose, and mouth from the detected face, and performs deep learning based on the information on the identified major parts to determine which of the nurses stored in the EMR server. Can you tell if you are a nurse? According to an embodiment, the process shown in FIG. 5 may be performed not only in the nurse terminal, but also in the EMR server.

6 is a diagram schematically illustrating a process of determining the nurse's information stored in the server from the detected nurse's face.

The app or EMR server installed in the nurse terminal converts the feature information of the nurse's face extracted from the nurse image into a feature vector, and a vector cluster located at the nearest distance to the transformed specific vector. ), it is possible to identify who the nurse is trying to log in to the dedicated app of the nurse terminal.

7 is a diagram schematically illustrating an example of a result of the server analyzing the image received from the nurse terminal.

In FIG. 7 , the first area 710 is an area including personal information of the identified patient when the processing unit 250 reads the first image to identify the patient.

In FIG. 7 , the second area 730 is an area in which the processing unit 250 reads the second image, classifies the patient's biosignals by signal, and includes diagnostic results obtained by analyzing each signal. According to the second area 730 of FIG. 7 , when the “nurse swimming” observed the patient's blood pressure at 3 pm, 108/55 corresponding to the abnormal blood pressure was observed as well as the oxygen saturation (SpO2) at that time. ) was also observed to be abnormal.

8 is a diagram schematically illustrating a process in which a nurse terminal captures a medical terminal and acquires an image.

FIG. 8A schematically shows a state in which a nurse activates the camera module 111 of the nurse terminal 110 to photograph the display unit of the medical terminal 130 . The camera module 111 focuses on the display unit of the medical terminal 130 , and when the nurse applies a shutter input, a second image including information on the patient's biosignal may be generated. In FIG. 8 , a drawing of the patient's label to generate a first image including the patient's personal information was omitted.

FIG. 8B is a schematic diagram showing that, when the nurse terminal 110 transmits the second image to the server 200 , the analysis result data received from the server 200 is output on the screen of the nurse terminal 110 . indicates. Referring to (B) of Figure 8, the name of the nurse logged into the application of the nurse terminal 110 is "Na Young-eun", the 35-year-old female patient has abnormal blood pressure, and oxygen saturation and pulse are normal. Able to know. The nurse may explain medical guidelines to the patient based on the contents output to the nurse terminal 110 or may inquire about a medical opinion from a doctor in charge of the patient. In addition, the nurse may control so that the captured image is finally stored in the server 200 by applying an input to the “save” button in FIG. 8B .

The embodiment according to the present invention described above may be implemented in the form of a computer program that can be executed through various components on a computer, and such a computer program may be recorded in a computer-readable medium. In this case, the medium includes a hard disk, a magnetic medium such as a floppy disk and a magnetic tape, an optical recording medium such as CD-ROM and DVD, a magneto-optical medium such as a floppy disk, and a ROM , RAM, flash memory, and the like, and hardware devices specially configured to store and execute program instructions.

Meanwhile, the computer program may be specially designed and configured for the present invention, or may be known and used by those skilled in the computer software field. Examples of the computer program may include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like.

The specific implementations described in the present invention are only examples, and do not limit the scope of the present invention in any way. For brevity of the specification, descriptions of conventional electronic components, control systems, software, and other functional aspects of the systems may be omitted. In addition, the connection or connection members of lines between the components shown in the drawings illustratively represent functional connections and/or physical or circuit connections, and in an actual device, various functional connections, physical connections that are replaceable or additional may be referred to as connections, or circuit connections. In addition, unless there is a specific reference such as “essential” or “importantly”, it may not be a necessary component for the application of the present invention.

In the specification of the present invention (especially in the claims), the use of the term “above” and similar referential terms may correspond to both the singular and the plural. In addition, when a range is described in the present invention, each individual value constituting the range is described in the detailed description of the invention as including the invention to which individual values belonging to the range are applied (unless there is a description to the contrary). same as Finally, the steps constituting the method according to the present invention may be performed in an appropriate order unless the order is explicitly stated or there is no description to the contrary. The present invention is not necessarily limited to the order in which the steps are described. The use of all examples or exemplary terms (eg, etc.) in the present invention is merely for the purpose of describing the present invention in detail, and the scope of the present invention is limited by the examples or exemplary terms unless limited by the claims. it's not going to be In addition, those skilled in the art will recognize that various modifications, combinations, and changes can be made in accordance with design conditions and factors within the scope of the appended claims or their equivalents.

110: nurse terminal
111: camera module
130: medical terminal
150: communication network
200: server
210: database
230: communication department
250: processing unit
270: output unit

Claims (5)

As a method for analyzing information of a patient identified based on an image, implemented by a server including a database, a communication unit, a processing unit and an output unit,
receiving, by the communication unit, an image from a nurse terminal, and identifying, by the processing unit, a patient from information included in the received image;
determining, by the processing unit, whether the identified patient is a patient for a chronic disease;
The processing unit, if the identified patient is a patient for a chronic disease, analyzes the biosignal of the identified patient based on a first criterion, and otherwise analyzes the biosignal of the identified patient based on a second criterion to do; and
and storing, by the processing unit, a result analyzed according to one of the first criterion and the second criterion in the database,
The first criterion is
Including the patient's physical effects that vary depending on the drugs used for each chronic disease,
The step of analyzing the biosignal,
When the type of chronic disease of the identified patient is identified, according to the physical effect included in the first criterion, the image-based identification method of analyzing the patient's information for correcting the result of analyzing the identified patient's biosignal . According to claim 1,
The communication unit transmits a result analyzed according to one of the first criterion and the second criterion to the nurse terminal, and controls the result to be displayed on the nurse terminal, an image-based identification method for analyzing patient information . According to claim 1,
The received image is at least two or more, and the information included in the received image is personal information for identifying who the patient is and biosignal information displayed on the identified patient's medical terminal, based on an image. Methods of analyzing information from identified patients. According to claim 1,
The received image is a first image and a second image,
Identifying the patient comprises:
Reading personal information from the first image, identifying who the read patient is,
The step of analyzing the biosignal,
A method for analyzing information of an identified patient based on an image, wherein the biosignal of the identified patient is read from the second image and the read biosignal is analyzed. According to claim 1,
The output unit outputs, based on the analyzed result, result values corresponding to normal and abnormal;
A method for analyzing information of a patient identified based on an image, wherein the processing unit controls the output result to be displayed on the nurse terminal.

Images