Brain function evaluation system, method, and program

Abstract

To evaluate a brain function, as the occasion demands, on the basis of information on the brain function, obtained from an examinee, and additional examinee information.SOLUTION: A brain function evaluation system includes receiving means that is configured to receive examinee information on a brain function, and processing means that is configured to calculate an evaluation result by evaluating a brain function based on the examinee information and additional examinee information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a brain function evaluation system, method, and program. [Background technology]

[0002] Conventionally, patients are asked to take a number of different tests regarding brain functions, including cognitive function, such as interviews and measurements of brain magnetic fields using a magnetoencephalograph, and doctors diagnose the state of the patient's brain function based on the results. After the doctor's diagnosis, when treatment begins, the patient regularly goes to the hospital for interviews and brain magnetic field measurements, and follows the doctor's treatment decisions regarding whether to continue or change the treatment. Recently, diagnostic support systems that assist doctors in making diagnoses have become popular, but the functions provided by such systems are limited to displaying measurement results on a screen in an easy-to-read format and creating reports.

[0003] Patent Document 1 discloses a report creation system that can display treatment and medication information and biological signals in chronological order in one report. Summary of the Invention [Problem to be solved by the invention]

[0004] However, there are multiple methods for measuring brain function, and conventional diagnostic support systems have the problem that they cannot add information obtained by measurement to evaluate brain function.

[0005] The present invention aims to provide a brain function evaluation system, method, and program that can evaluate brain function at any time based on information regarding brain function obtained from a subject and additional subject information. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the object, the brain function evaluation system of the present invention comprises an acceptance means for accepting subject information on brain function and additional subject information, and a processing means for outputting an evaluation result of evaluating brain function based on the subject information on brain function and the additional subject information, wherein the subject information on brain function is information for evaluating a brain function risk, a cognitive function risk, and a lifestyle-related risk, respectively, the acceptance means accepts first subject information corresponding to the subject information on brain function, and then accepts additional second subject information corresponding to the subject information on brain function from a medical professional terminal and a subject terminal, the processing means calculates a first evaluation result dependent on each evaluation result of the brain function risk, the cognitive function risk, and the lifestyle-related risk based on the first subject information, and calculates a second evaluation result by re-evaluating the brain function based on the first evaluation result and the second subject information, Furthermore, the evaluation result recalculated based on the additional subject information, Including the first evaluation result and the second evaluation result Chronological update of history and the history of updates to the time series after the addition The result is output as a report to the medical staff terminal or the subject terminal. Effect of the Invention

[0007] According to the present invention, it is possible to advantageously evaluate brain function at any time based on information relating to brain function obtained from a subject and additional subject information. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of an overall configuration of a brain function evaluation system according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of a Web server. [Diagram 3] FIG. 3 is a diagram illustrating an example of a hardware configuration of a client PC. [Figure 4] FIG. 4 is a diagram showing an example of a functional block configuration of the brain function evaluation system. [Diagram 5]FIG. 5 is a diagram showing an example of the entire sequence in the brain function evaluation system. [Figure 6] FIG. 6 is a diagram showing an example of a registration screen for magnetoencephalographic data displayed on the UI screen. [Figure 7] FIG. 7 is a diagram showing an example of an input screen for entering answers to questions in a medical interview. [Figure 8] FIG. 8 is a diagram showing an example of an input screen for inputting the result of the psychological test. [Figure 9] FIG. 9 is a diagram showing an example of a flow of determining a brain function risk by the brain function risk calculation unit. [Figure 10] FIG. 10 is a diagram showing an example of reference data (determination criteria) for determining a brain function risk. [Figure 11] FIG. 11 is a diagram showing an example of a flow of determining a cognitive function risk by the cognitive function risk calculation unit. [Figure 12] FIG. 12 is a diagram showing an example of reference data for determining the cognitive function risk. [Figure 13] FIG. 13 is a diagram showing an example of a flow of determining a lifestyle habit risk by the lifestyle habit risk calculation unit. [Figure 14] FIG. 14 is a diagram showing an example of reference data for determining lifestyle-related risks. [Figure 15] FIG. 15 is a diagram illustrating an example of a comprehensive evaluation flow by the comprehensive evaluation calculation unit. [Figure 16] FIG. 16 is a diagram showing an example of a flow of a subroutine of the overall evaluation flow. [Figure 17] FIG. 17 is a diagram showing an example of reference data used for risk classification for performing a comprehensive evaluation. [Figure 18] FIG. 18 is a diagram showing an example of a configuration of a report created by the report creating unit. [Figure 19] FIG. 19 is a diagram showing an example of comment data classified by overall evaluation used in a report. [Figure 20] FIG. 20 is a diagram showing an example of a display in which the transition of the overall evaluation is displayed in chronological order on the UI screen. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of a brain function evaluation system, method, and program will be described in detail with reference to the accompanying drawings.

[0010] (First embodiment) The brain function evaluation system according to the present embodiment provides a comprehensive evaluation function that comprehensively evaluates brain function based on data (subject information) on the brain function of the subject. As an example, the subject information is information that evaluates each of the brain function risk, cognitive function risk, and lifestyle risk, and a comprehensive evaluation function is provided that can calculate an evaluation result that comprehensively evaluates brain function from even one of these pieces of information. In addition, if there is additional subject information, such as the remaining unregistered subject information or updated information on already registered subject information, an evaluation result that comprehensively reevaluates brain function by reflecting the added or updated information is calculated, and the calculated evaluation result can be stored or output each time. Note that the timing of calculation of the reevaluated evaluation result is any time. For example, the reevaluation evaluation result is calculated at a specific opportunity, such as when the user operates a button that requests the calculation of the evaluation result. Hereinafter, the calculation of the evaluation result is described as "evaluating" for convenience. Here, the "brain function risk" is an index that classifies the risk of brain function decline with an index value (for example, A, B, C level) based on the subject's brain magnetism data and biosignals. "Cognitive function risk" is an index that classifies the risk of cognitive function with index values ​​(e.g., levels A, B, C) based on the results of psychological tests and interviews given to subjects. "Lifestyle risk" is an index that classifies the risk of diseases caused by lifestyle habits with index values ​​(e.g., levels A, B, C) based on the subject's self-reported lifestyle. The "brain function" referred to in comprehensive brain function evaluation differs from the "brain function" in "brain function risk," in that "brain function evaluation" refers to a new comprehensive evaluation of the brain classified from factors including each risk, and can be used as "brain function evaluation" in a "brain function check-up," for example.

[0011] (Overall system) Fig. 1 is a diagram showing an example of the overall configuration of a brain function evaluation system according to an embodiment. The brain function evaluation system 1 shown in Fig. 1 can be implemented, for example, in the form of a server-client system. As an example, a case where the system is implemented in a Web server system will be described below.

[0012] 1, the Web server 10 is an information processing device configured as a computer. The Web server 10 has a comprehensive evaluation means 100 for comprehensively evaluating the brain function of a patient.

[0013] The Web server 10 comprehensively evaluates the brain function of the patient based on the patient information received from the client PC and the portable terminal device 30, and transmits the evaluation result to the client PC and the portable terminal device 30. Specifically, the comprehensive evaluation means 100 of the Web server 10 is composed of a reception means 100a, a processing means 100b, and a storage means 100c. The reception means 100a receives various information. In this example, it receives patient information, which is subject information for determining risk related to brain function. The processing means 100b performs various processes based on the received information. In this example, it comprehensively evaluates brain function based on the patient information received by the reception means 100a, that is, calculates the evaluation result. The calculated result is stored in the storage means 100c as needed, or output to an external device that is a request source. In this configuration example, the storage means 100c is provided in the Web server 10, but the storage means 100c may be provided in an external storage or the like.

[0014] A client PC (Personal Computer) 20 and a portable terminal device 30 each access the Web server 10 via a network.

[0015] The client PC 20 is a terminal for medical staff in the hospital P1 (or in a medical examination center, etc.). In the example shown in FIG. 1, a PC connected to a measuring device such as a magnetoencephalograph 40 is shown, but the PC may be a PC in an examination room, etc., where data from the measuring device can be obtained. The client PC 20 is configured to be connectable to a first network N1, and transmits patient information to the Web server 10 via the first network N1. The first network N1 is a network such as a LAN or the Internet that connects the client PC 20 and the Web server 10.

[0016] The portable terminal device 30 is a portable terminal device such as a smartphone or a tablet terminal device. The portable terminal device 30 is configured to be connectable to a second network N2, and transmits patient information to the Web server 10 via the second network N2. The second network N2 is a network such as Wi-Fi (registered trademark), a public network, or the Internet that connects the portable terminal device 30 and the Web server 10.

[0017] The portable terminal device 30 corresponds to a "subject terminal." The portable terminal device 30 includes a widely used smartphone, and for example, an external staff member assisting the patient in treatment, a family member of the patient, or the patient himself / herself can use some or all of the functions of the Web server 10 from outside, such as at home or in a facility, via a public network if access to the Web server 10 is authenticated.

[0018] The Web server 10 may be implemented by one information processing device, or may be implemented by a combination of multiple information processing devices by distributing the functions. In addition, some or all of the functions of the comprehensive brain function evaluation means 100 may be provided by cloud. In addition, some of the functions provided in the Web server 10 (part of the comprehensive brain function evaluation function) may be provided on the client PC 20 or the mobile terminal device 30 side.

[0019] Furthermore, the medical staff terminal and the subject terminal are not limited to the client PC 20 and the portable terminal device 30. The device configuration and the number of the medical staff terminal and the subject terminal may be determined arbitrarily.

[0020] Fig. 2 is a diagram showing an example of a hardware configuration of the Web server 10. As shown in Fig. 2, the Web server 10 has a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, an auxiliary storage device 14, and a communication I / F 15. Each part is connected via a bus 16 or the like.

[0021] The CPU 11 is a central processing unit, and controls the entire Web server 10. The ROM 12 is a memory that stores fixed programs such as the BIOS. The RAM 13 is a memory that is used as a work area when the CPU 11 executes processing.

[0022] The auxiliary storage device 14 is a HDD, an SSD, etc. The auxiliary storage device 14 stores various programs and data of the Web server 10. The various programs include an OS of the Web server 10, a program for evaluating brain function, etc.

[0023] The communication I / F 15 is a network interface that communicates with the client PC 20 and the portable terminal device 30 .

[0024] The CPU 11 of the Web server 10 reads various programs M1 from the auxiliary storage device 14 into the RAM 13 and executes them, thereby realizing each means for comprehensively evaluating brain function (reception means 100a, processing means 100b, and storage means 100c) as functional units.

[0025] Fig. 3 is a diagram showing an example of a hardware configuration of the client PC 20. As shown in Fig. 3, the client PC 20 has a CPU 21, a ROM 22, a RAM 23, an auxiliary storage device 24, a display device 25, an input device 26, and a communication I / F 27. Each part is connected via a bus 28 or the like.

[0026] The CPU 21 is a central processing unit, and controls the entire client PC 20. The ROM 22 is a memory that stores fixed programs such as the BIOS. The RAM 23 is a memory that is used as a work area when the CPU 21 executes processing.

[0027] The auxiliary storage device 24 is a HDD, an SSD, etc. The auxiliary storage device 24 stores various programs and data of the client PC 20. The various programs include the OS of the client PC 20 and a program M2 such as a web viewer.

[0028] The display device 25 is an LCD (Liquid Crystal Display), an organic EL display, etc. The input device 26 is an input device such as a keyboard or a mouse. Note that a touch panel may be provided as the input device 26. The communication I / F 27 is a network interface for the first network N1.

[0029] The CPU 21 of the client PC 20 loads various programs M2 from the auxiliary storage device 24 into the RAM 23 and executes them to realize client functions (including a Web viewer) such as a UI unit and a communication unit that utilize the functions of the Web server 10.

[0030] The hardware configuration of the portable terminal device 30 can be implemented with the same computer configuration as the client PC 20. The communication I / F of the portable terminal device 30 becomes a network interface of the second network. The CPU of the portable terminal device 30 loads various programs from the auxiliary storage device into the RAM and executes them to function as a UI section and a communication section that utilize the functions of the Web server 10. Other than that, the description of the hardware configuration of the client PC 20 is repeated, so illustrations and descriptions are omitted.

[0031] 4 is a diagram showing an example of the functional block configuration of the brain function evaluation system 1. The Web server 10 shows details of functional units (acceptance means 100a, processing means 100b, and storage means 100c) that comprehensively evaluate brain functions. The Web server 10 has an interface controller 101, a brain magnetic field data storage unit 102, a calculation instruction unit 103, an input data storage unit 104, a report creation unit 105, a spectrum analysis unit 106, a brain function risk calculation unit 107, a cognitive function risk calculation unit 108, a lifestyle risk calculation unit 109, and a comprehensive evaluation calculation unit 110.

[0032] Here, the interface controller 101 corresponds to the receiving means 100a (see FIG. 1). The brain magnetic field data storage unit 102 and the input data storage unit 104 correspond to the storage means 100c (see FIG. 1). The interface controller 101, the calculation instruction unit 103, the report creation unit 105, the spectrum analysis unit 106, the brain function risk calculation unit 107, the cognitive function risk calculation unit 108, the lifestyle risk calculation unit 109, and the overall evaluation calculation unit 110 correspond to the processing means 100b (see FIG. 1).

[0033] The interface controller 101 controls the function of evaluating brain functions based on access from the client PC 20, the portable terminal device 30, etc. For example, the interface controller 101 accepts requests and received data from the client PC 20 or the portable terminal device 30, registers the received data from the client PC 20 or the portable terminal device 30, issues various execution instructions related to the evaluation of brain functions, and transmits screen information to the requesting client PC 20 or the portable terminal device 30.

[0034] The brain magnetic data storage unit 102 is a storage unit for the brain magnetic data D1 transmitted from the client PC 20. The brain magnetic data D1 is a file of brain magnetic data obtained by a magnetoencephalograph. This file may include biological signals such as heart rate and pulse rate.

[0035] The calculation instruction unit 103 instructs the calculation processing unit 200 to perform calculations.

[0036] The input data storage unit 104 is a storage unit for various data. For example, the input data storage unit 104 stores patient data, which is transmitted patient information. The patient data includes input data such as patient identification information D2 indicating the name, age, sex, etc. of the patient, the result of interviewing the patient (information obtained from the patient, etc.) D3, a psychological test (result of conducting a psychological test) for the patient D4, and the result of calculation performed by the calculation processing unit 200. The input data such as the patient identification information D2, the result of interviewing the patient D3, and the psychological test D4 for the patient are stored by accepting transmission of the input data from the client PC 20 or the portable terminal device 30. In addition, the input data storage unit 104 may store standard data (including judgment standard data) D0 in a modifiable manner. The standard data D0 differs for each of the brain function risk, the cognitive function risk, and the lifestyle habit risk, and is used by the calculation processing unit 200 in the judgment of each risk. If the data of the standard data D0 may be fixed, it may be provided on the calculation processing unit 200 side.

[0037] The report creation unit 105 creates a report for each patient based on various data of the patient stored in the input data storage unit 104. For example, if a patient registers a psychological test every day, a comprehensive evaluation result is created every day, and the report includes time-series information (such as a line graph) of the comprehensive evaluation result.

[0038] The calculation processing unit 200 has, as an example, a spectrum analysis unit 106, a brain function risk calculation unit 107, a cognitive function risk calculation unit 108, a lifestyle-related risk calculation unit 109, and an overall evaluation calculation unit 110. As the reference data D0, reference data corresponding to each of the brain function risk calculation unit 107, the cognitive function risk calculation unit 108, the lifestyle-related risk calculation unit 109, and the overall evaluation calculation unit 110 is prepared. In the following, as an example, the reference data D0 is stored in the input data storage unit 104.

[0039] When the interface controller 101 receives the brain magnetic data D1 from the client PC 20, the spectrum analysis unit 106 performs spectrum analysis of the brain magnetic data D1. For example, when the interface controller 101 receives the brain magnetic data D1 from the client PC 20, it stores the brain magnetic data D1 in the brain magnetic data storage unit 102 and instructs the calculation instruction unit 103 to perform spectrum analysis of the brain magnetic data D1. This causes the spectrum analysis unit 106 to perform spectrum analysis of the brain magnetic data D1. In the spectrum analysis, a power spectrum value for evaluating the risk of brain function decline from a biological signal or the like is calculated, and the analysis result is stored in the input data storage unit 104.

[0040] The cerebral function risk calculation unit 107 uses the patient data stored in the input data storage unit 104 to classify the cerebral function risk based on the reference data for the cerebral function risk, and stores the result in the input data storage unit 104.

[0041] The cognitive function risk calculation unit 108 uses the patient data stored in the input data storage unit 104 to classify the cognitive function risk based on the reference data for the cognitive function risk, and stores the result in the input data storage unit 104.

[0042] The lifestyle habit risk calculation unit 109 uses the patient data stored in the input data storage unit 104 to classify lifestyle habit risks based on reference data for lifestyle habit risks, and stores the results in the input data storage unit 104 .

[0043] The comprehensive evaluation calculation unit 110 executes a comprehensive evaluation flow to perform a comprehensive evaluation, and stores the comprehensive evaluation result in the input data storage unit 104. When a comprehensive evaluation of brain function is requested from the client PC 20 or the portable terminal device 30, for example, the comprehensive evaluation calculation unit 110 performs a comprehensive evaluation depending on the results (corresponding to "evaluation results" and hereinafter referred to as "judgment results") of the brain function risk calculation unit 107, the cognitive function risk calculation unit 108, and the lifestyle habit risk calculation unit 109, and stores the comprehensive evaluation result in the input data storage unit 104. Note that, as will be described later in detail, if some risks among the brain function risk, the cognitive function risk, and the lifestyle habit risk can be evaluated, a comprehensive evaluation flow is executed to perform a comprehensive evaluation. In the example shown in this embodiment, it is sufficient to obtain the results of at least two risks. Furthermore, if three results are collected, a more accurate comprehensive evaluation result can be obtained, which is even better.

[0044] The client PC 20 has a UI unit 201 such as a Web viewer and a communication unit 202. The UI unit 201 analyzes screen information transmitted from the interface controller 101 of the Web server 10 to the communication unit 202 to configure and display a UI screen. The UI unit 201 also transmits input data accepted on the UI screen, acquired brain magnetic data D1, and execution commands as request data from the communication unit 202 to the interface controller 101. For example, the UI unit 201 acquires brain magnetic data D1 measured by the magnetoencephalograph 40 (see FIG. 1) from a designated storage destination. If the client PC 20 is a device capable of controlling the magnetoencephalograph 40, the UI unit 201 may display an operation screen of the magnetoencephalograph 40, execute settings and measurements of the magnetoencephalograph 40, and acquire the brain magnetic data D1. The UI unit 201 also displays an input screen on the display device 25 (see FIG. 2) and accepts input of various data on the screen. For example, the UI unit 201 receives input of patient identification information D2, patient interview results D3, and psychological tests D4 for the patient from the input device 26 (see FIG. 2).

[0045] When the UI screen instructs the UI unit 201 to transmit data to the Web server 10, the UI unit 201 transmits request information to the Web server 10 via the communication unit 202. For example, when the UI screen instructs the UI unit 201 to transmit patient identification information, the UI unit 201 transmits request information indicating a registration request and patient identification information D2 to the Web server 10 via the communication unit 202. When the UI screen instructs the UI unit 201 to transmit brain magnetic data, the UI unit 201 transmits request information indicating a registration request and brain magnetic data D1 to the Web server 10 via the communication unit 202. When the UI screen instructs the UI unit 201 to transmit a medical interview result or a psychological test, the UI unit 201 transmits request information indicating a registration request and input data such as the medical interview result D3 and the psychological test D4 to the Web server 10 via the communication unit 202. When the UI screen instructs the UI unit 201 to transmit a comprehensive evaluation of brain function, the UI unit 201 transmits request information indicating an acquisition request to the Web server 10 via the communication unit 202.

[0046] Furthermore, the UI unit 201 may display a UI screen and register or update the reference data D0 in the Web server 10.

[0047] Like the client PC 20, the portable terminal device 30 also has a UI unit 301 and a communication unit 302. Since the portable terminal device 30 generally cannot acquire the brain magnetic field data D1, the UI unit 301 may be limited mainly to a function of registering the interview results D3 and the psychological test D4, updating the overall brain function evaluation, displaying the history, and the like.

[0048] (Sequence of the entire system) 5 is a diagram showing an example of the overall sequence in the brain function evaluation system 1. Although not specifically described below, it is assumed that the client PC 20 and the Web server 10 communicate with each other via a first network N1. It is also assumed that the mobile terminal device 30 and the Web server 10 communicate with each other via a second network N2.

[0049] First, a medical examiner in the hospital inputs patient identification information D2 of a patient who has visited the hospital on a UI screen acquired by the client PC 20 from the Web server 10, and transmits the input data to the Web server 10 (interface controller 101) (S1). Here, the medical examiner is assumed to be a doctor or medical professional who performs medical examinations on patients.

[0050] The interface controller 101 registers the patient identification information D2 transmitted from the client PC 20 in the input data storage unit 104 (S2). The registered patient identification information D2 is managed as information unique to the patient. The information unique to the patient is used, for example, by issuing a patient ID when the patient accepts for a medical examination. The patient ID can also be used later as authentication information. The interface controller 101 uses the information unique to the patient, and thereafter, if there is any data related to the patient, it stores the data in the input data storage unit 104 in association with the information unique to the patient. In other words, in the input data storage unit 104, data related to the patient is associated with the patient ID for each patient.

[0051] Once registration to the Web server 10 is complete, the examiner operates the UI screen to obtain the measurement data of the patient measured by the magnetoencephalograph (i.e., the magnetoencephalograph data D1) as a file from the storage location where the magnetoencephalograph saved the data, and saves the file of the magnetoencephalograph data D1 of the patient in the memory section of the client PC 20 (S3).

[0052] Next, the examiner operates the UI screen to transmit the patient's magnetic brain data D1 stored in the storage unit to the Web server 10 (interface controller 101) (S4). The interface controller 101 stores the patient's magnetic brain data D1 transmitted from the client PC 20 in the magnetic brain data storage unit 102 (S5), and further instructs the spectrum analysis unit 106 via the calculation instruction unit 103 to perform a spectrum analysis of the patient's magnetic brain data D1 (S6).

[0053] The spectrum analysis section 106 acquires the brain magnetic field data D1, performs a spectrum analysis on the brain magnetic field data D1 (S7), and stores the analysis results in the input data storage section 104 (S8).

[0054] After completing the registration in the Web server 10, the medical examiner operates the UI screen, inputs the results of the medical interview and the psychological test of the patient, and transmits the input data (the medical interview result D3 and the psychological test D4) to the Web server 10 (interface controller 101) (S9). If the medical interview or the psychological test has not been conducted, the medical interview result or the remaining psychological test may be input later and transmitted to the Web server 10.

[0055] The interface controller 101 registers the input data of the patient transmitted from the client PC 20 in the input data storage unit 104 in association with the patient ID of the patient (S10).

[0056] After this registration, the examiner operates the UI screen to request the Web server 10 (interface controller 101) to judge the brain health condition of the patient, that is, to make a comprehensive evaluation of brain function (S11).

[0057] When the interface controller 101 receives a request for determining the brain health condition of the patient from the client PC 20, it causes the computation instruction unit 103 to execute the process of determining the brain health condition of the patient (S12).

[0058] As a process of judging the brain health state, the calculation instruction unit 103 first instructs the brain function risk calculation unit 107 to calculate the brain function risk of the patient (S13). In response to this instruction, the brain function risk calculation unit 107 executes a brain function risk judgment flow (such as the judgment flow in FIG. 9 ) using the spectrum analysis result of the patient stored in the input data storage unit 104, and calculates the brain function risk of the patient.

[0059] When the brain function risk calculation unit 107 finishes the calculation, the calculation instruction unit 103 subsequently instructs the cognitive function risk calculation unit 108 to calculate the cognitive function risk of the patient (S14). In response to this instruction, the cognitive function risk calculation unit 108 executes a cognitive function risk judgment flow (such as the judgment flow in FIG. 11 ) using the psychological test results of the patient stored in the input data storage unit 104, and calculates the cognitive function risk of the patient.

[0060] When the cognitive function risk calculation unit 108 finishes the calculation, the calculation instruction unit 103 subsequently instructs the lifestyle risk calculation unit 109 to calculate the lifestyle risk of the patient (S15). In response to this instruction, the lifestyle risk calculation unit 109 executes a lifestyle risk judgment flow (such as the judgment flow in FIG. 13 ) using the interview results of the patient stored in the input data storage unit 104, and calculates the lifestyle risk of the patient.

[0061] When the lifestyle risk calculation unit 109 finishes the calculation, the calculation instruction unit 103 subsequently instructs the overall evaluation calculation unit 110 to judge the brain health state of the patient (S16). In response to this instruction, the overall evaluation calculation unit 110 executes an overall evaluation flow (such as the judgment flow in FIG. 15) using the obtained calculation results of the brain function risk, cognitive function risk, and lifestyle risk, and calculates an overall evaluation of the brain health state of the patient. The results calculated by each unit are stored in the input data storage unit 104, and the interface controller 101 notifies the client PC 20 of the end.

[0062] Next, the person in charge of the examination operates the UI screen to request the Web server 10 (interface controller 101) to create a report on the brain health condition of the patient (S17).

[0063] When the interface controller 101 receives a request for creating a report on the brain health condition of the patient from the client PC 20, it acquires the report on the brain health condition of the patient from the report creation unit 105 (S18). The report creation unit 105 creates a report file based on various data of the patient stored in the input data storage unit 104.

[0064] Then, the interface controller 101 transmits the report file of the patient to the client PC 20 (S19), and the contents of the report indicating the brain health condition of the patient are displayed on the UI screen of the client PC 20.

[0065] For example, if a psychological test is not conducted, the result of cognitive function risk cannot be obtained, and one piece of information will be missing. However, by executing the comprehensive assessment flow, the result of two risks will be evaluated based on the dependency between brain function risk and lifestyle risk, and the report file will be sent to the client PC 20.

[0066] The medical examiner outputs the report file and gives the contents of the report to the patient as an electronic file or on paper (S20). After that, the patient connects to the Web server 10 (interface controller 101) from his / her home or another facility using authentication information such as a patient ID on the portable terminal device 30. For example, the patient connects by performing authentication using login information (such as the patient ID) in the report file.

[0067] Then, in the mobile terminal device 30, the user operates the UI screen acquired from the Web server 10 to input new psychological test D4 for the patient, or re-input the answers to the interview D3 or psychological test D4, and transmits the input data (interview result D3 and psychological test D4) to the Web server 10 (interface controller 101) (S21). The interface controller 101 additionally registers the input data for the patient transmitted from the mobile terminal device 30 in the input data storage unit 104 in association with the patient ID of the patient (S22).

[0068] When the additional registration is performed, a comprehensive judgment process is performed similarly to the comprehensive judgment (S11 to S16) although not shown in the figure, and the report creation unit 105 creates a report including the updated comprehensive judgment result.

[0069] After that, the UI screen of the mobile terminal device 30 is further operated to request the Web server 10 (interface controller 101) to reacquire the report on the brain health condition of the patient (S23). In response to this request, the interface controller 101 acquires a report created based on the updated data from the report creation unit 105 and transmits it to the mobile terminal device 30 (S24). The contents of the report indicating the updated brain health condition are displayed on the UI screen of the mobile terminal device 30.

[0070] The data registered in the Web server 10 can be updated at any time from the client PC 20 and the portable terminal device 30. When update data is repeatedly transmitted from the client PC 20 or the portable terminal device 30, the report creation unit 105 creates a history of updates to the overall judgment at each transmitted date and time, and outputs the history in a report as information shown in chronological order, such as a graph.

[0071] The interface controller 101 may limit the information to be transmitted so that only information necessary for the patient or a person supporting the patient is displayed on the UI screen of the portable terminal device 30. For example, the UI screen of the portable terminal device 30 limits the information to be transmitted only to the functions of registering and updating input data such as medical interviews and psychological tests, and displaying reports.

[0072] (UI screen) Next, we will explain the UI screen. Here, we will show an example of a UI screen where various registration / input screens are displayed by switching between tabs.

[0073] Fig. 6 is a diagram showing an example of a registration screen for magnetoencephalography data displayed on a UI screen. In this example, the UI screen 1000 has a plurality of switching tabs T at the top, and by switching the display to an MEG tab T1 among the switching tabs T, a registration screen 1111 for magnetoencephalography data is displayed so that data can be entered, as shown in Fig. 6. The plurality of switching tabs T also include a basic information tab, a medical interview tab, a psychological test tab, an analysis result tab, a report tab, and the like. The basic information tab is provided on the UI screen of the client PC 20, and patient identification information D2 indicating the name, age, sex, and the like of a patient is entered by staff of a hospital or medical examination facility, and the like.

[0074] A registration screen 1111 shown in FIG. 6 includes a file selection box 1111A for the brain magnetic field data measured by the magnetoencephalograph 40 (see FIG. 1), a setting input box 1111B for adding information confirmed in the brain magnetic field data, and the like. This registration screen 1111 is provided on the UI screen of the client PC 20. A staff member of a hospital or medical examination facility selects a file of the brain magnetic field data of a patient in the file selection box 1111A of this registration screen 1111, sets information confirmed in the selected brain magnetic field data in the setting input box 1111B, and presses the save button 1111C. Pressing the save button 1111C causes the brain magnetic field data of the patient to be saved as a file from the magnetoencephalograph in the client PC 20. Pressing the analyze button 1111D causes the file of the brain magnetic field data D1 (including the set information) to be sent from the client PC 20 to the Web server 10 (interface controller 101).

[0075] FIG. 7 is a diagram showing an example of an input screen for questions and answers to a medical interview. This input screen 1121 is provided not only to the client PC 20 but also to the UI screen of the mobile terminal device 30, and is displayed so that input can be made by switching the display to the medical interview tab T2. The input screen 1121 of FIG. 7 shows an example of questions for a medical interview (example of medical interview 1). The questions include questions for grasping the patient's behavioral patterns, lifestyle, personality, and the like. The patient or the assistant staff inputs answers to each question 1121A by designating them in a selection field 1121B, and transmits the medical interview result D3 to the Web server 10 (interface controller 101) by pressing a save button, for example. This input screen 1121 is also acquired by the mobile terminal device 30 by accessing the Web server 10, so that the patient or the assistant staff can update the answers to the medical interview at any time on the UI screen of the mobile terminal device 30.

[0076] FIG. 8 is a diagram showing an example of an input screen for inputting the results of a psychological test. Like the input screen 1121 for answering a medical interview, this input screen 1131 is also provided on the UI screen of the portable terminal device 30 in addition to the client PC 20, and is displayed so that input can be made by switching the display to the psychological test tab T3. The input screen 1131 in FIG. 8 shows an example of items of a psychological test. Input items such as MMSE and FAB are included. In each item 1131A, a psychologist or an assistant staff member inputs an impression read from a patient by, for example, designating a rank, and transmits the input result (psychological test result D4) to the Web server 10 (interface controller 101) by, for example, pressing a save button 1131B. In addition, since the input screen 1131 can be acquired by accessing the Web server 10 from the portable terminal device 30, the results of the psychological test, such as the rank, can be updated at any time on the UI screen of the portable terminal device 30.

[0077] (Decision flow) FIG. 9 is a diagram showing an example of a flow of judging a brain function risk by the brain function risk calculation unit 107. FIG. 10 is a diagram showing an example of a criterion for judging a brain function risk. The flow of judging a brain function risk shown in FIG. 9 judges a brain function risk based on the criterion in FIG. 10. As an example of the criterion, a value (score) of the brain rhythm and the complexity of the electroencephalogram calculated by the spectrum analysis of the magnetoencephalogram data is used. Here, the brain rhythm is the mean frequency MF, and the complexity of the electroencephalogram is the spectrum entropy SE.

[0078] First, the brain function risk calculation unit 107 judges whether or not the spectrum analysis results (scores) of each of the analysis methods MF and SE have been obtained (S101), as shown in the contents of the input judgment (see FIG. 10). If the spectrum analysis results (scores) of each of the analysis methods MF and SE have not been obtained (S101: No), the brain function risk calculation unit 107 sets the brain function risk to "A (empty)".

[0079] When the spectral analysis results of each of the analysis methods MF and SE have been obtained (S101: Yes), the brain function risk calculation unit 107 determines whether the MF score satisfies the contents of the standard value determination (see FIG. 10) (S102).

[0080] If the MF score satisfies the content of the reference value judgment (see FIG. 10) (S102: Yes), the brain function risk calculation unit 107 judges whether the MF score further satisfies the content of the D judgment (see FIG. 10) (S103). If the MF score satisfies the content of the D judgment (see FIG. 10) (S103: Yes), the brain function risk calculation unit 107 sets the brain function risk to "D".

[0081] If the MF score does not satisfy the contents of the reference value judgment (see FIG. 10) (S102: No) or if the MF score does not satisfy the contents of the D judgment (see FIG. 10) (S103: No), the brain function risk calculation unit 107 judges whether the MF and SE scores satisfy the contents of the C judgment (see FIG. 10) (S104). If the MF and SE scores satisfy the contents of the C judgment (see FIG. 10) (S104: Yes), the brain function risk calculation unit 107 sets the brain function risk to "C".

[0082] If the scores of MF and SE do not satisfy the contents of the C judgment (see Figure 10) (S104: No), the brain function risk calculation unit 107 determines whether either MF or SE satisfies the contents of the B judgment (see Figure 10) (S105).

[0083] If either MF or SE satisfies the content of judgment B (see FIG. 10) (S105: Yes), the brain function risk calculation section 107 further performs MF / SE judgment (S106).

[0084] If the MF satisfies the contents of the MF / SE judgment (see FIG. 10) (S106: Yes), the brain function risk calculation unit 107 sets the brain function risk to "B type: 1." If the SE satisfies the contents of the MF / SE judgment (see FIG. 10) (S106: No), the brain function risk calculation unit 107 sets the brain function risk to "B type: 2."

[0085] If neither MF nor SE satisfies the content of the B judgment (see FIG. 10) (S105: No), the brain function risk calculation unit 107 determines the brain function risk to be "A".

[0086] In this way, even if no brain magnetic field data is available, the brain function risk is determined to be "A" for the sake of comprehensive assessment. However, since the assessment of brain function is a provisional assessment, it is accompanied by an empty identification.

[0087] Fig. 11 is a diagram showing an example of a flow of judging the cognitive function risk by the cognitive function risk calculation unit 108. Fig. 12 is a diagram showing an example of a criterion for judging the cognitive function risk. Two types of tests, MMSE (Mini Mental State Examination) and FAB (Frontal Assessment Battery), are performed as psychological tests, and each score is compared with the criterion for reference data.

[0088] First, the cognitive function risk calculation unit 108 performs an input judgment of the input data (S201), and if the input data does not satisfy the input judgment (see FIG. 12) (S201: No), it sets the cognitive function risk to "A (empty)".

[0089] If the input data satisfies the input judgment (see Figure 12) (S201: Yes), the cognitive function risk calculation unit 108 determines whether the MMSE satisfies the contents of the D judgment (see Figure 12) (S202), and if so (S202: Yes), it sets the cognitive function risk to "D".

[0090] If the MMSE does not satisfy the contents of a D assessment (see FIG. 12) (S202: No), the cognitive function risk calculation unit 108 determines whether the FAB or overall impression score satisfies the contents of a C assessment (see FIG. 12) (S203), and if they do (S203: Yes), it sets the cognitive function risk to "C".

[0091] If neither the FAB nor the overall impression score meets the content of the C assessment (see FIG. 12) (S203: No), the cognitive function risk calculation unit 108 determines whether the MMSE, FAB, or overall impression score meets the content of the B assessment (see FIG. 12) (S204).

[0092] If the content of the B judgment is met (S204: Yes), the cognitive function risk calculation unit 108 further judges whether the number of mild abnormalities meets the content of the mild abnormality number judgment (see FIG. 12) (S205), and if so (S205: Yes), the cognitive function risk is set to "B type: 1." On the other hand, if not so (S205: No), the cognitive function risk calculation unit 108 sets the cognitive function risk to "B type: 2."

[0093] Moreover, if the content of the B judgment is not satisfied (S204: No), the cognitive function risk calculation unit 108 determines the cognitive function risk to be "A".

[0094] In this way, even if the psychological test results are not available, the cognitive function risk is judged as "A" for the sake of comprehensive judgment. However, since the judgment of cognitive function is a provisional judgment, it is accompanied by an empty identification.

[0095] FIG. 13 is a diagram showing an example of a flow of determining lifestyle habit risk by the lifestyle habit risk calculation unit 109. FIG. 14 is a diagram showing an example of a determination criterion for determining lifestyle habit risk. The lifestyle habit risk is determined by the risk score shown in FIG. 14(a). The risk score is a score added based on a condition determined based on the result of the medical interview. FIG. 14(b) shows an example of a condition for adding the risk score. In FIG. 14(b), as an example, a score of 1 or more is set when the answer number of the question matches the condition. In the following, the lifestyle habit risk determination flow will be described in detail assuming that the risk score has already been calculated from the medical interview result by the lifestyle habit risk calculation unit 109.

[0096] First, the lifestyle risk calculation unit 109 performs an input judgment on answers to questions in a medical interview (S301), and if the answers do not satisfy the input judgment (see FIG. 14) (S301: No), the lifestyle risk is set to "A (empty)".

[0097] If the answer to the question satisfies the input judgment (see Figure 14) (S301: Yes), the lifestyle risk calculation unit 109 judges whether the risk score of the answer to the question satisfies the content of the D judgment (see Figure 14) (S302), and if so (S302: Yes), sets the lifestyle risk to "D".

[0098] If the risk score of the question answer does not satisfy the contents of the D judgment (see Figure 14) (S302: No), the lifestyle risk calculation unit 109 determines whether the risk score of the question answer satisfies the contents of the C judgment (see Figure 14) (S303), and if it does satisfy the contents (S303: Yes), it sets the lifestyle risk to "C".

[0099] If the risk score of the question answer does not satisfy the contents of the C judgment (see Figure 14) (S303: No), the lifestyle risk calculation unit 109 determines whether the risk score of the question answer satisfies the contents of the B judgment (see Figure 14) (S304), and if it does satisfy the contents (S304: Yes), it sets the lifestyle risk to "B".

[0100] If the risk score of the answer to the question does not satisfy the content of judgment B (see FIG. 14) (S304: No), the lifestyle risk calculation unit 109 determines the lifestyle risk to be "A".

[0101] In this way, even if the answers to the questions in the interview are not sufficient, the lifestyle risk is judged as "A" for the purpose of the overall judgment. However, since the lifestyle judgment is a provisional judgment, it is accompanied by an empty identification.

[0102] Fig. 15 is a diagram showing an example of a comprehensive evaluation flow by the comprehensive evaluation calculation unit 110. The comprehensive evaluation calculation unit 110 uses the judgment results obtained by the flows shown in Fig. 9, Fig. 11, and Fig. 13, that is, the judgment results of the brain function risk, the cognitive function risk, and the lifestyle habit risk (a set of these will be referred to as a "judgment result set" below), and makes a comprehensive judgment according to the comprehensive evaluation flow of Fig. 15 which specifies their interdependencies.

[0103] Fig. 16 is a diagram showing an example of a flow of a subroutine of a comprehensive evaluation flow Fig. 17 is a diagram showing an example of a judgment criterion used for risk classification for performing a comprehensive evaluation.

[0104] The comprehensive judgment flow of Figures 15 and 16 will be described in detail. First, the comprehensive evaluation calculation unit 110 determines that the judgment result set satisfies the D judgment, that is, performs the D judgment process of Figure 16 (S401), and if it satisfies (S401: Yes), the comprehensive judgment is "D". In the example of the D judgment process of Figure 16, if the cognitive function risk is "D", it becomes "Yes", and otherwise it becomes "No".

[0105] If the judgment result set does not satisfy the D judgment (S401: No), the comprehensive evaluation calculation unit 110 performs the C judgment process in Fig. 16 (S402) if the judgment result set satisfies the C judgment, that is, if the condition for C judgment is satisfied (S402: Yes in Fig. 15), it performs a C classification judgment (S403). In the example of the C judgment process in Fig. 16, it is satisfied when the cognitive function risk is "C" and when the cognitive function risk is not "C" but is "B" and the brain function risk is "C" or "D", and is not satisfied in other cases.

[0106] The C classification judgment is based on the value (C1 or C2) extracted from the C classification in the risk classification table (see FIG. 17) for the setting of the comprehensive evaluation item corresponding to the combination of judgment results in the judgment result set.

[0107] If the judgment result set does not satisfy the C judgment (S402: No in FIG. 15), the comprehensive evaluation calculation unit 110 judges whether the judgment result set satisfies the B judgment, that is, whether it is judged as a B judgment in the B judgment process in FIG. 16 (S404), and if it satisfies the B judgment (S404: Yes in FIG. 15), it performs a B classification judgment (S405). In the example of the B judgment process in FIG. 16, the process proceeds to the B classification when the cognitive function risk is other than "A" and the brain function risk is other than "B". Alternatively, the process proceeds to the B classification when the cognitive function risk is other than "A" and the brain function risk is "B" but the lifestyle habit risk is other than "A". The process proceeds to the A classification (S406 in FIG. 15) when the cognitive function risk is other than "A" and the brain function risk is "B" but the lifestyle habit risk is "A". In addition, in the case of a combination of cognitive function risk "A" and brain function risk other than "A" and brain function risk other than "B", processing proceeds to classification B (S405 in FIG. 15). In the case of a combination of cognitive function risk "A" and brain function risk also "A", processing proceeds to classification A (S406 in FIG. 15). In the case of a combination of cognitive function risk "A" and brain function risk other than "A" and brain function risk "B", processing proceeds to classification A (S406 in FIG. 15).

[0108] The B classification judgment is based on the value (B1, B2, or B3) extracted from the B classification in the risk classification table (see Figure 17) for the setting of the comprehensive evaluation item corresponding to the combination of judgment results in the judgment result set.

[0109] If the judgment result set does not satisfy the B judgment (S404: No), the comprehensive evaluation calculation unit 110 performs an A classification judgment (S406). The A classification judgment is performed by extracting a value (A1, A2, A3, or A4) from the table of risk classifications (see FIG. 17) for the setting of the comprehensive evaluation item corresponding to the combination of judgment results of the judgment result set from the A classification as the judgment result.

[0110] (Report creation)

[0111] Fig. 18 is a diagram showing an example of the structure of a report created by report creation unit 105. Fig. 19 is a diagram showing an example of comment data classified by overall evaluation used in a report.

[0112] The report shown in Fig. 18 is acquired by, for example, selecting a report tab from among the multiple switching tabs T shown in Fig. 6. A report 1200 in Fig. 18 includes a patient basic information section 1201, an overall evaluation section 1202, a lifestyle habit evaluation section 1203, a brain function evaluation section 1204, and a cognitive ability evaluation section 1205. Information is set in each section based on the patient data stored in the input data storage section.

[0113] For example, in the overall evaluation column 1202, the overall evaluation determined by the overall evaluation determination flow (setting "B2" as an example) and the comment of the overall evaluation "B2" included in the comment data of FIG. 19 are set.

[0114] Furthermore, in a lifestyle habit evaluation column 1203, the judgment result judged in the lifestyle habit risk judgment flow (as an example, "B" is set) and patient data related to lifestyle habit are set.

[0115] Moreover, in the brain function evaluation column 1204, the result of the determination made in the brain function risk determination flow (set to "A" as an example) and the respective levels of MF and SE are set with star marks.

[0116] Further, in the cognitive ability assessment field 1205, the result of the assessment made in the cognitive function risk assessment flow (for example, "B" is set) and the respective values ​​of MMSE and FAB are set with star marks.

[0117] Figure 20 is a diagram showing an example of a UI screen that displays the transition of the overall evaluation over time. The overall evaluation changes as the medical interview, psychological test, and MEG data are updated. The overall evaluation also changes when insufficient data is added or when the scores of the medical interview or psychological test change as a result of treatment. For example, if the scores of the medical interview or psychological test improve as a result of treatment, the overall evaluation also changes in the direction of improvement.

[0118] When the medical interview, psychological test, or MEG data is updated (including the case where the medical interview, psychological test, or MEG data is input for the first time later), the Web server 10 generates an update history by saving the current overall evaluation in addition to the previous overall evaluation. For example, even if there is insufficient data, a comprehensive evaluation is performed, and if the missing data is added, a more accurate overall evaluation is saved in chronological order. Also, as shown in FIG. 20, the overall evaluation (white plot) calculated each time the medical interview or psychological test is updated from home or the like between the previous visit (colored plot) and the current visit (colored plot) is added, making it possible to analyze the effects of treatment performed at home or the like in more detail.

[0119] The program executed by the computer of this embodiment may be provided by being pre-installed in a ROM. It may also be provided by being recorded in a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a digital versatile disk (DVD) in the form of an installable or executable file. It may also be configured to be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network.

[0120] As described above, in this embodiment, the brain health state is judged using at least a part (one, two or three) of "brain function risk," "cognitive function risk," and "lifestyle risk," and information leading to lifestyle improvement and behavioral change is reported to the doctor and patient as a report on the current state. If the results of even one of the three risks can be calculated, the current brain health state can be calculated using a certain algorithm and provided to the doctor and patient as a report, thereby increasing the opportunity for the patient to change their behavior.

[0121] Furthermore, by executing various judgment flows, the dependencies of each risk are defined, allowing a comprehensive judgment of brain function to be made. For those cases where no data is available from the MEG data, interview, or psychological test and a risk judgment cannot be made, a provisional "A" judgment can be made and a comprehensive judgment can be made. For those cases where no data is available, the remaining risks will be judged by inputting the data later, and a comprehensive judgment will be made again. Furthermore, if the MEG data, interview, or psychological test data is updated, a comprehensive judgment will be made again based on the latest data.

[0122] Therefore, brain function can be evaluated comprehensively based on data on the subject's brain function (subject information) even if only a portion (for example, two) of the brain function risk, cognitive function risk, and lifestyle risk. Therefore, even if it is not possible to perform all the necessary measurements in the hospital due to the patient's physical condition, by referring to this comprehensive evaluation information, it is possible to immediately start appropriate treatment.

[0123] In addition, it is possible to evaluate brain function at any time based on the information on brain function obtained from the patient. By taking psychological tests at any time while undergoing treatment at home, etc., the patient can confirm the objective results of the treatment effect with the brain function evaluation system. Therefore, even when the patient himself thinks that the treatment is ineffective, the objective results from the brain function evaluation system will motivate the patient and enable him or her to continue the treatment.

[0124] In addition, if there is recent information on a certain element conducted outside the hospital, such as at home or at an intervention facility, it can be added and updated to the past report, and the current "brain health status" can be updated. Subjects who receive updated information can be more motivated to change their behavior.

[0125] In addition, if treatment at home is not effective, patients and support staff will be able to make decisions from the comfort of their own home, such as going to the hospital earlier than planned or consulting with support staff to change the treatment.

[0126] In addition, since the effects of behavioral modification and lifestyle improvement can be confirmed without the need for outpatient examinations, improvement behavior can be continued with less economic and mental burden on the subject.

[0127] Although the embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. Each of these embodiments is included in the scope and gist of the invention, and is included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0128] 1. Brain function evaluation system 10 Web Server 20 Client PCs 30 Portable terminal device 40 Magnetoencephalography 100 Comprehensive Evaluation Instrument 100a Reception method 100b Processing means 100c storage means 101 Interface Controller 102 Magnetoencephalographic Data Storage Unit 103 Calculation instruction section 104 Input data storage unit 105 Report Writing Department 106 Spectral Analysis Unit 107 Brain Function Risk Calculation Department 108 Cognitive Function Risk Calculation Department 109 Lifestyle Risk Calculation Department 110 Comprehensive Evaluation Calculation Department 200 Processing section 201 UI section 202 Communications Department 301 UI section 302 Communications Department D0 Reference data (including judgment criteria data) D1 Magnetoencephalography data D2 Patient identification information D3 Interview results D4 Psychological Test N1 First Network N2 Second Network [Prior art documents] [Patent documents]

[0129] [Patent Document 1] Patent No. 6475132

Claims

1. A receiving means for receiving subject information regarding brain function and additional subject information; a processing means for outputting an evaluation result of the brain function based on the subject information on the brain function and the additional subject information; having The subject information on brain function is information for evaluating a brain function risk, a cognitive function risk, and a lifestyle risk, the receiving means receives, after receiving the first subject information corresponding to the subject information on the brain function, additional second subject information corresponding to the subject information on the brain function from the medical staff terminal and the subject terminal; The processing means includes: calculating a first evaluation result that depends on each of the evaluation results of the brain function risk, the cognitive function risk, and the lifestyle risk based on the first subject information, and calculating a second evaluation result by reevaluating the brain function based on the first evaluation result and the second subject information; Further, the evaluation result recalculated based on the additional subject information is added to a time-series update history including the first evaluation result and the second evaluation result, and the time-series update history after the addition is made into a report and output to the medical staff terminal or the subject terminal. Brain function evaluation system.

2. When there is a shortage of subject information data related to the brain function, the processing means determines the evaluation results of the brain function risk, the cognitive function risk, and the lifestyle habit risk that have a shortage of subject information data using a provisional setting, thereby calculating evaluation results that depend on each of the brain function risk, the cognitive function risk, and the lifestyle habit risk. The brain function evaluation system according to claim 1 .

3. the processing means sets a provisional judgment value for an evaluation result of a risk having insufficient data of the subject information among the brain function risk, the cognitive function risk, and the lifestyle habit risk, and calculates an evaluation result depending on each of the evaluation results of the brain function risk, the cognitive function risk, and the lifestyle habit risk. The brain function evaluation system according to claim 2 .

4. The time-series update history outputted as the report is a graph showing changes in the evaluation results. The brain function evaluation system according to claim 1 .

5. The additional subject information is information about a test performed at home or at an intervention facility. The brain function evaluation system according to claim 1 .

6. The input of the subject information and the output of the report are received via a UI screen. The brain function evaluation system according to claim 1 .

7. A method for outputting a brain function evaluation result by a computer, comprising: receiving subject information on brain function, the subject information being information for evaluating a brain function risk, a cognitive function risk, and a lifestyle risk; receiving, after receiving first subject information corresponding to the subject information on the brain function, additional second subject information corresponding to the subject information on the brain function from a medical staff terminal and a subject terminal; calculating a first evaluation result depending on each of the evaluation results of the brain function risk, the cognitive function risk, and the lifestyle habit risk based on the first subject information; calculating a second evaluation result by reevaluating the brain function based on the first evaluation result and the second subject information; outputting a time-series update history including the first evaluation result and the second evaluation result as a report to the medical staff terminal or the subject terminal; further comprising the step of accepting additional subject information; adding the evaluation result recalculated based on the additional subject information to a time-series update history including the first evaluation result and the second evaluation result, and outputting the time-series update history after the addition as a report to the medical staff terminal or the subject terminal; The method includes:

8. On the computer, receiving subject information on brain function, the subject information being information for evaluating a brain function risk, a cognitive function risk, and a lifestyle risk; receiving, after receiving first subject information corresponding to the subject information on the brain function, additional second subject information corresponding to the subject information on the brain function from a medical staff terminal and a subject terminal; calculating a first evaluation result depending on each of the evaluation results of the brain function risk, the cognitive function risk, and the lifestyle habit risk based on the first subject information; calculating a second evaluation result by reevaluating the brain function based on the first evaluation result and the second subject information; outputting a time-series update history including the first evaluation result and the second evaluation result as a report to the medical staff terminal or the subject terminal; further comprising the step of accepting additional subject information; adding the evaluation result recalculated based on the additional subject information to a time-series update history including the first evaluation result and the second evaluation result, and outputting the time-series update history after the addition as a report to the medical staff terminal or the subject terminal; A program for executing.

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