Information processing device and estimation method

Abstract

To estimate reduction in a subjective cognitive function that occurs in a prior stage of mild cognitive impairment by evaluating attention adjustment ability.SOLUTION: An information processing device for estimating reduction in a subjective cognitive function receives biological index data indicating biological information emitted by a measurement person being a measurement object for reduction in the subjective cognitive function and behavior index data indicating a content of a behavior performed by the measurement person, calculates feature amounts of multiple features from the biological index data, calculates feature amounts of multiple features from the behavior index data (S703), selects multiple features that are temporally synchronized and mutually correlated with each other from the multiple features of the biological index data and the multiple features of the behavior index data (S704), evaluates the attention adjustment ability of the measurement person by comparing the selected feature amounts of the multiple features with a prescribed determination criterion (S705), and estimates reduction in the subjective cognitive function on the basis of the evaluated attention adjustment ability.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present invention relates to an information processing device and an estimation method for estimating a subjective decline in cognitive function. [Background technology]

[0002] It is known that mild cognitive impairment (MCI), which is a precursor to dementia and manifests as outward signs of dementia, can occur.

[0003] Patent Document 1 discloses a technology for identifying signs of dementia, which discloses a "signs of dementia identification program for identifying signs of dementia in a subject, the program causing a computer to execute an information acquisition step of acquiring facial expression image information obtained by capturing an image of the subject's facial expression, and a discrimination step of referring to reference facial expression image information obtained by capturing an image of the subject's facial expression in the past and a degree of correlation of three or more levels with the discriminatory types of signs of dementia, and discriminating signs of dementia in the subject based on the facial expression image information acquired in the information acquisition step." [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2022-113072 A Summary of the Invention [Problem to be solved by the invention]

[0005] It is also known that subjective cognitive decline (SCD) occurs before the above-mentioned mild cognitive impairment (MCI), which is the external sign of dementia. There are concepts such as subjective cognitive decline, subjective memory disorder, and subjective memory anxiety for subjective cognitive decline, but only the person himself feels the change and the people around him do not notice it.

[0006] Subjective cognitive decline, subjective memory impairment, and subjective memory anxiety may or may not be noticed by the individual. In addition, when subjective cognitive decline occurs, a person may feel vague anxiety or depression, but it is difficult to recognize this as a sign of dementia. Therefore, even if subjective cognitive decline occurs, people rarely seek medical treatment at a medical institution. When such symptoms of subjective cognitive decline progress, it becomes necessary to treat it as mild cognitive impairment (MCI) or dementia.

[0007] One of the factors that makes it difficult to notice a subjective decline in cognitive function is the compensatory function of attention adjustment. Compensation means that when a certain function declines, another function takes its place and plays its role, and attention is the function that makes this adjustment. In situations where cognitive function declines, the ability to adjust attention comes into play, for example, to focus attention on one point, switch attention to necessary information, and distribute and organize attention, thereby compensating for the decline in cognitive function.

[0008] In other words, the ability to regulate attention is the basis of cognitive function, and it is believed that a decline in the ability to regulate attention leads to a decline in cognitive function. In the case of subjective cognitive decline (SCD), there is a possibility of a decline in metabolism in the posterior cingulate cortex, which has the function of matching external information with one's own memory, and it is suggested that the functions of "selection," which matches and judges memory, and "allocation," which divides attention for information processing, are particularly impaired.

[0009] Therefore, the present invention has been made in consideration of the above problems, and aims to estimate the subjective decline in cognitive function that occurs in the preliminary stage of mild cognitive impairment by evaluating the ability to regulate attention. [Means for solving the problem]

[0010] The information processing device of the present invention is an information processing device that estimates a subjective decline in cognitive function, and is equipped with a receiving unit that receives bioindicator data indicating bioinformation emitted by a subject who is the subject of measurement of subjective cognitive function decline, and behavioral index data indicating the content of the behavior performed by the subject, and a control unit including a processor and a memory, and the control unit calculates feature values ​​of a plurality of characteristics from the bioindicator data and calculates feature values ​​of a plurality of characteristics from the behavioral index data, selects a plurality of features that are synchronized in time and correlated with each other from the plurality of features of the bioindicator data and the plurality of features of the behavioral index data, evaluates the subject's ability to adjust attention by comparing the feature values ​​of the selected plurality of features with a predetermined judgment criterion, and estimates the subjective decline in cognitive function based on the evaluated attention adjustment ability.

[0011] The estimation method of the present invention is a method for estimating a subjective decline in cognitive function, and includes receiving bioindicator data indicating bioinformation emitted by a subject who is the subject of measurement of the subjective decline in cognitive function, and behavioral index data indicating the content of the behavior performed by the subject, calculating feature values ​​of a plurality of characteristics from the bioindicator data, and calculating feature values ​​of a plurality of characteristics from the behavioral index data, selecting a plurality of features that are synchronized in time and correlated with each other from the plurality of features of the bioindicator data and the plurality of features of the behavioral index data, evaluating the subject's ability to regulate attention by comparing the feature values ​​of the selected plurality of characteristics with a predetermined judgment criterion, and estimating the subjective decline in cognitive function based on the evaluated ability to regulate attention. Effect of the Invention

[0012] According to the present invention, by evaluating the ability to regulate attention, it is possible to estimate the subjective decline in cognitive function that occurs at an earlier stage of mild cognitive impairment. Other objects and novel features will become apparent from the description of this specification and the accompanying drawings. [Brief description of the drawings]

[0013] [Figure 1]FIG. 1 is a diagram showing an overall configuration of an information processing system 1 including an estimation device 2 that estimates a subjective decline in cognitive function. [Diagram 2] FIG. 2 is a hardware block diagram of the estimation device 2. [Diagram 3] 2 is a software block diagram of a control unit 20 of the estimation device 2. FIG. [Figure 4] FIG. 2 is a hardware block diagram of the information processing terminal 3. [Diagram 5] 13 shows a setting screen 50 that the SCD determination application 461 displays on the display device 43. FIG. [Figure 6] 1 is a flowchart for estimating subjective cognitive decline. [Figure 7] 11 is a flowchart showing details of a process for evaluating the ability to adjust attention. [Figure 8] FIG. 13 is a diagram showing discrimination criteria for discriminating the quality of measurement data. [Figure 9] FIG. 9 is a diagram showing a result 90 of a cross-correlation process of feature amounts of a plurality of features. [Figure 10A] FIG. 1 shows a number of selected features and the criteria 101 set for each feature. [Figure 10B] 1 is a diagram showing feature amounts 102 of each feature of measurement data of a healthy subject that are referred to when setting a judgment criterion. [Figure 11] 13 is a flowchart showing details of a process for evaluating circadian rhythm. [Figure 12] FIG. 2 is a diagram showing circadian rhythm data 269 and the score 120 set for each data. [Figure 13] 11 is a flowchart showing details of a process for estimating a subjective decline in cognitive function. [Figure 14A] FIG. 141 shows a table 141 correlating the total score for the ability to regulate attention, the total score for the circadian rhythm, and the degree of subjective signs of decline in cognitive function. [Figure 14B] FIG. 13 is a diagram showing a message table 142 that stores messages to be displayed as the degree of a sign of subjective decline in cognitive function. [Figure 15A]15 is a screen 1510 showing the estimated result of subjective cognitive decline. [Figure 15B] This is a screen 1520 showing the estimated results (graph) of subjective decline in cognitive function. [Figure 15C] This is a screen 1530 that suggests measures to improve subjective cognitive decline. [Figure 15D] 15 is a screen 1540 showing the progress of the estimation results of subjective cognitive function. [Figure 15E] This is a screen 1550 for setting up cooperation with other services. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] In the following embodiments, for convenience, when necessary, the embodiments will be divided into multiple sections or embodiments, but unless otherwise expressly stated, they are not unrelated to each other and one may be a partial or complete variation, detail, supplementary explanation, etc. of the other.

[0015] In addition, in the following embodiments, when referring to the number of elements (including the number, numerical values, amounts, ranges, etc.), unless specifically stated or clearly limited to a specific number in principle, the number is not limited to that specific number and may be more than or less than a specific number.

[0016] Furthermore, in the following embodiments, the components (including element steps, etc.) are not necessarily essential unless specifically stated otherwise or considered to be clearly essential in principle.

[0017] Similarly, in the following embodiments, when referring to the shapes, positional relationships, etc. of components, etc., unless otherwise specified or considered to be obviously different in principle, it includes those that are substantially similar or similar to the shapes, etc. The same applies to the above numerical values ​​and ranges.

[0018] In addition, in all the drawings for explaining the embodiments, the same members are generally given the same reference numerals, and repeated explanations thereof will be omitted.

[0019] (Information Processing System 1) Fig. 1 is a diagram showing the overall configuration of an information processing system 1 including an estimation device 2 that estimates a subjective decline in cognitive function. As shown in Fig. 1, the information processing system 1 includes an estimation device 2 (information processing device) that estimates a subjective decline in cognitive function (SCD), an information processing terminal 3 used by a subject who is the subject of measurement of the subjective decline in cognitive function, and a viewing device 4 for viewing various results calculated by the estimation device 2. The estimation device 2, the information processing terminal 3, and the viewing device 4 are connected to each other via a network 5 so as to be able to communicate with each other.

[0020] (Estimation device 2) FIG. 2 is a hardware block diagram of the estimation device 2. FIG. 3 is a software block diagram of the control unit 20 of the estimation device 2. The estimation device 2 will be described in detail with reference to FIG. 2 and FIG. 3. The estimation device 2 receives measurement data (bioindicator data, behavioral index data) measured by the information processing terminal 3, evaluates attention adjustment ability and circadian rhythm based on the received measurement data, and estimates a decline in subjective cognitive function. The estimation device 2 provides the evaluation result of the estimated decline in subjective cognitive function to the information processing terminal 3 or the viewing device 4, and displays it on the display unit of the information processing terminal 3 or the viewing device 4. The estimation device 2 may be a cloud server or an on-premise server in a medical facility.

[0021] First, the hardware configuration of the estimation device 2 will be described with reference to Fig. 2. As shown in Fig. 2, the estimation device 2 includes a control unit 20 having a processor 21 and a memory 22, an input device 23, an output device 24, a communication device 25, a storage device 26, and a bus 27. The processor 21 is a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), an ASIC, or the like. The memory 22 is a dynamic random access memory (DRAM), or the like, and is used as a working area for the processor 21. The input device 23 is a keyboard, a mouse, or the like, and the output device 24 is a display unit, or the like. The communication device 25 is a network interface controller (NIC) or the like that communicates with the network 5.

[0022] The communication device 25 (reception unit) receives bioindicator data 267 indicating bioinformation emitted by a subject experiencing a decline in cognitive function, behavioral index data 268 indicating the content of behavior performed by the subject, and circadian rhythm data 269 from the information processing terminal 3 via the network 5. Note that the estimation device 2 may receive the bioindicator data 267, the behavioral index data 268, and the circadian rhythm data 269 locally, without using the network 5.

[0023] The storage device 26 is a hard disk drive (HDD), a solid state drive (SSD), or a combination thereof, and stores various programs and various data. The storage device 26 stores an attention regulation ability evaluation program 261, a circadian rhythm evaluation program 262, and an SCD estimation program 263. The storage device 26 also stores an attention regulation ability evaluation DB 264, a circadian rhythm evaluation DB 265, and an SCD estimation DB 266. The processor 21 executes the attention regulation ability evaluation program 261, refers to the attention regulation ability evaluation DB 264, and evaluates the attention regulation ability. The processor 21 also executes the circadian rhythm evaluation program 262, refers to the circadian rhythm evaluation DB 265, and evaluates the circadian rhythm. The processor 21 also executes the SCD estimation program 263, refers to the SCD estimation DB 266, and estimates subjective cognitive decline (SCD).

[0024] The storage device 26 also stores biological index data 267 and behavior index data 268 received from the information processing terminal 3. The storage device 26 also stores data relating to sleep received from the information processing terminal 3 as circadian rhythm data 269.

[0025] The biometric data 267 is data indicating biometric information emitted by a subjective person who is experiencing cognitive decline, and is, for example, data related to a person's gaze, facial expression, voice, heart rate, sweating, breathing, etc. The data related to the gaze includes, for example, features such as gaze retention time, gaze switching frequency, blink amount, and gaze turning back frequency. The data related to the facial expression includes, for example, features such as the rate of change of facial muscles, the rate of change of the upper part of the face, the rate of change of the lower part of the face, the number of times the face is tilted, and the head retention time. The data related to the voice includes, for example, features such as the occurrence rate of a specific word, the response delay time, and the word identity rate. The data related to the heart rate includes features such as the heart rate, heart rate variability, and low frequency fluctuation component LF / high frequency fluctuation component HF corresponding to respiratory variability. The data related to sweating is, for example, data acquired by a wearable device worn by the person, and includes features such as mental sweating rate. The data related to breathing is, for example, data acquired by a wearable device worn by the person, and includes features such as respiratory stability rate.

[0026] The behavior index data 268 is data indicating the content of the behavior performed by the measurer, and is, for example, data related to the amount of operation by the person to operate an object, the amount of activity of the person, the range of movement of the person, etc. The data related to the amount of operation includes features such as the number of touch operations and the amount of movement of the touch operation on the information processing terminal 3 of an object (for example, a smartphone, an IoT home appliance, a TV remote control, etc.). The data related to the amount of activity of the person is data acquired by a smartphone or a wearable device, and includes features such as the number of steps, calories burned, walking style, stride length change rate, speed, and balance. The data related to the range of movement of the person is data acquired by a smartphone or a drive recorder, and includes features such as the movement distance, the number of repeated movements, and the residence time.

[0027] The circadian rhythm data 269 is information related to sleep declared by the subject, and includes, for example, the continuous sleep time declared by the subject and the degree of sleep satisfaction.

[0028] Next, the software configuration of the control unit 20 of the estimation device 2 will be described with reference to Fig. 3. As shown in Fig. 3, the control unit 20 of the estimation device 2 has an attention regulation ability evaluation unit 31 that evaluates the attention regulation ability, a circadian rhythm evaluation unit 32 that evaluates the circadian rhythm, an SCD estimation unit 33 that estimates subjective cognitive decline (SCD), and an output unit 34 that outputs various information.

[0029] The attention adjustment ability evaluation unit 31 includes: Calculating feature values ​​of a plurality of features (e.g., the above-mentioned gaze retention time, gaze switching frequency, blink amount, gaze turning back frequency, etc.) from the biometric data 267, and calculating feature values ​​of a plurality of features (the above-mentioned number of touch operations, touch operation movement amount, etc.) from the behavioral index data 268, selecting a plurality of features that are synchronized in time and correlated with each other from among a plurality of features of the biometric data 267 and a plurality of features of the behavioral index data 268; The feature quantities of the selected multiple features are compared with a predetermined criterion to evaluate the subject's ability to adjust attention.

[0030] The circadian rhythm evaluation section 32 uses the circadian rhythm data 269 to evaluate the circadian rhythm of the subject.

[0031] The SCD estimation unit 33 estimates a subjective decline in cognitive function of the subject based on the attention regulation ability evaluated by the attention regulation ability evaluation unit 31 and the circadian rhythm evaluated by the circadian rhythm evaluation unit 32 .

[0032] The output unit 34 outputs the estimation result of the subjective decline in cognitive function estimated by the SCD estimation unit 33, etc. The output estimation result is displayed, for example, on the display device 43 (see FIG. 4) of the information processing terminal 3 or on the display unit of the viewing device 4. The output unit 34 may also output a history of the estimation result of the subjective decline in cognitive function. The output unit 34 may also output improvement recommendation information for improving the subjective decline in cognitive function corresponding to the estimated subjective decline in cognitive function.

[0033] (Information processing terminal 3) Fig. 4 is a hardware block diagram of the information processing terminal 3. The information processing terminal 3 will be described in detail with reference to Fig. 4. The information processing terminal 3 is used to acquire bioindicator data 267 and behavioral index data 268, and to acquire circadian rhythm data 269. The information processing terminal 3 is a terminal device used by a person who measures a subjective decline in cognitive ability, and is, for example, a smartphone, a tablet, or a notebook PC.

[0034] 4, the information processing terminal 3 has a processor 41, a memory 42, a display device 43, a touch sensor 44, a communication device 45, a storage device 46, a camera 47, and a bus 48. The processor 41 is a CPU, a GPU, a DSP, an ASIC, or the like. The memory 42 is a DRAM or the like, and is used as a working area for the processor 41. The display device 43 displays various information, and the touch sensor 44 detects a touch operation on the display device 43 by a user of the information processing terminal 3. The communication device 45 is a NIC that communicates with the network 5, or the like.

[0035] The storage device 46 is a flash memory or the like, and stores various programs and various data. The storage device 46 stores an SCD determination application 461 for determining subjective cognitive decline (SCD). The SCD determination application 461 may be a Web application or a native application. Details of the SCD determination application 461 will be described later.

[0036] The camera 47 captures pictures and videos. The touch sensor 44 and the camera 47 are used to acquire measurement data (biometric indicator data 267, behavioral indicator data 268) for estimating subjective cognitive decline (SCD).

[0037] (Viewing device 4) The viewing device 4 is a device for viewing the subjective estimation result of the decline in cognitive function provided by the estimation device 2. The viewing device 4 is used for, for example, monitoring, follow-up, health care services, etc. by a distant family member, a family doctor, a pharmacist, or the like.

[0038] (Settings screen 50) 5 is a diagram showing a setting screen 50 that the SCD determination application 461 displays on the display device 43. When the SCD determination application 461 is executed in the information processing terminal 3, the setting screen 50 is displayed. This setting screen 50 may be a screen that the estimation device 2 displays on the web browser of the information processing terminal 3 as a web server. In the setting screen 50, various conditions for acquiring data for determining subjective cognitive decline (SCD) are set. The setting screen 50 has a setting unit 51 for setting measurement information, a setting unit 52 for setting basic information for evaluating the ability to regulate attention, a setting unit 53 for setting basic information for evaluating circadian rhythm, and a setting unit 54 for setting the contents of the result display.

[0039] The setting unit 51 has a measurement target setting unit 511 for setting the measurement target to "individual" or "interaction", a measurement time setting unit 512 for setting the measurement time, and a target device setting unit 513 for setting the target device. In the setting unit 51 in FIG. 5, the measurement target is "individual", the measurement time is "5 minutes", and the target device is "smartphone". In the measurement target setting unit 511, it is possible to set "individual" for the operator who operates the target device as the measurement target, and "interaction" for the interlocutor who makes a voice call or video call with the operator or the like as the measurement target. In addition, in the measurement time setting unit 512, it is possible to set an arbitrary time or a time selected from a plurality of times set in advance as the measurement time. In addition, in the target device setting unit 513, it is possible to select a device to be used for measuring the measurement data. The devices to be used for the measurement are, for example, a smartphone, a TV, a personal computer, a wearable device, an IoT home appliance, a security camera, and a drive recorder.

[0040] The setting unit 52 includes a biometric setting unit 521 for setting whether or not a biometric indicator is used to evaluate the ability to adjust attention, and a behavioral indicator setting unit 522 for setting whether or not a behavioral indicator is used to evaluate the ability to adjust attention. In the setting unit 52 of FIG. 5, it is set that a biometric indicator and a behavioral indicator are used. In addition, in the biometric setting unit 521, when a setting is made to use a biometric indicator, the specific contents of the biometric indicator can be specified. The specific contents of the biometric indicator are, for example, gaze, facial expression, voice, heart rate, sweating, and breathing. The gaze and facial expression data are acquired by a camera 47 mounted on the smartphone. In addition, the voice data is acquired by a microphone not shown. In addition, the heart rate, sweating, and breathing data are acquired by a sensor of the wearable device. In the behavioral indicator setting unit 522, when a setting is made to use a behavioral indicator, the specific contents of the behavioral indicator can be specified. The specific contents of the behavioral indicator are, for example, an operation amount, an activity amount, and a motion range amount. The operation amount is an operation amount of a target device (for example, a smartphone, an IoT home appliance, or a TV remote control). The amount of activity is the amount of activity of a user who uses a target device (e.g., a smartphone, a wearable device), such as the number of steps, calories burned, walking style, stride length change rate, speed, balance, etc. The amount of motion range is the motion range of a target person using, for example, a smartphone or a GPS of a drive recorder, or a security camera, such as a moving distance, a number of repeated movements, a staying time, etc.

[0041] The setting unit 53 sets the continuous sleep time and the sleep satisfaction level used for the evaluation of the circadian rhythm. In the example of FIG. 5, the continuous sleep time is set to "4 hours" and the sleep satisfaction level is set to "not very satisfied". The continuous sleep time can be set to any time or a time selected from a plurality of times set in advance. The sleep satisfaction level can be selected in a tab format from a plurality of options prepared in advance (for example, "not satisfied", "not very satisfied", "mostly satisfied", "quite satisfied", "very satisfied"). Also, the wearable device may be set to automatically input sleep information. The person measuring the continuous sleep time and the sleep satisfaction level are declared in the setting unit 53.

[0042] The setting unit 54 sets whether to display a screen 1510 (see FIG. 15A) showing the estimation result of the subjective cognitive function decline, whether to display a screen 1520 (see FIG. 15B) showing the estimation result (graph) of the subjective cognitive function decline, whether to display a screen 1530 (see FIG. 15C) proposing a remedy for improving the subjective cognitive function decline, whether to display a screen 1540 (see FIG. 15D) showing the transition of the estimation result of the subjective cognitive function, and whether to display a screen 1550 (see FIG. 15E) for setting cooperation with other services. Details of each screen will be described later.

[0043] The setting screen 50 also has a device selection button 55 for selecting an external device or external equipment into which the bioindicator data or behavior index data is to be imported. The setting screen 50 also has a measurement start button 56 for starting measurement of the measurement data, and a result display button 57 for displaying the screen set in the setting unit 54.

[0044] For example, when the measurement start button 56 is selected, a web browser that is normally used is started, and the operator (measurer) of the information processing terminal 3 performs search and browsing using the web browser. While the operator is performing search and browsing, bioindicator data and behavior index data are acquired by sensors (touch sensor 44 and camera 47) of the information processing terminal 3. Note that the software started by the measurement start button 56 does not have to be a web browser, and may be dedicated software for acquiring bioindicator data and behavior index data, or may be game software.

[0045] (Flowchart for estimating subjective cognitive decline) 6 is a flowchart for estimating a subjective decline in cognitive function. An overview of the process for estimating a subjective decline in cognitive function will be described with reference to FIG.

[0046] First, the estimation device 2 acquires various settings set on the setting screen 50 in Fig. 5 from the information processing terminal 3 (S601). When the measurement start button 56 in Fig. 5 is selected, the various settings set on the setting screen 50 are transmitted from the information processing terminal 3 to the estimation device 2. Then, the estimation device 2 acquires various settings from the information processing terminal 3. At this time, the estimation device 2 accepts the circadian rhythm data 269 (continuous sleep time, sleep satisfaction level) set in the setting section 53 of the setting screen 50.

[0047] Further, the estimation device 2 receives bioindicator data and behavior index data (S602). Note that, although an example in which the estimation device 2 acquires both the bioindicator data and the behavior index data has been described here, the estimation device 2 may acquire only either the bioindicator data or the behavior index data according to the contents set by the setting unit 52.

[0048] The estimation device 2 executes the attention regulation ability evaluation program 261 to execute a process of evaluating the attention regulation ability based on the biological index data 267, the behavior index data 268, and the attention regulation ability evaluation DB 264 (S603). The process of evaluating the attention regulation ability will be described later in detail.

[0049] The estimation device 2 executes the circadian rhythm evaluation program 262 to execute a process of evaluating the circadian rhythm (S604) based on the circadian rhythm data 269 (continuous sleep time, sleep satisfaction level) and the circadian rhythm evaluation DB 265. The details of the process of evaluating the circadian rhythm will be described later.

[0050] After executing S603 and S604, the estimation device 2 executes the SCD estimation program 263 to execute a process of estimating a subjective decline in cognitive function based on the evaluation result of the attention adjustment ability, the evaluation result of the circadian rhythm, and the SCD estimation DB 266 (S605). The process of estimating a subjective decline in cognitive function will be described later in detail.

[0051] Then, each result output by the estimation device 2 is displayed on the display unit of the estimation device 2, the display device 43 of the information processing terminal 3, or the display unit of the viewing device 4 (S606).

[0052] (Details of Attention Regulation Ability Evaluation Process (S603)) Fig. 7 is a flowchart showing details of the process of evaluating the ability to regulate attention. The process of evaluating the ability to regulate attention will be described in detail with reference to Fig. 7. Each step in Fig. 7 is executed by the processor 21 of the control unit 20 executing the attention regulation ability evaluation program 261.

[0053] The control unit 20 reads the measurement data (biometric index data 267, behavior index data 268) received in S602 (S701).

[0054] Next, the control unit 20 determines whether the read measurement data is of a quality that can be used to evaluate the attention adjustment ability (S702). Fig. 8 is a diagram showing a discrimination criterion for discriminating the quality of the measurement data. This discrimination criterion 80 is stored, for example, in the attention adjustment ability evaluation DB 264. The estimation device 2 discriminates the quality of the biological index data and the behavior index data according to the discrimination criterion shown in Fig. 8.

[0055] For example, the control unit 20 determines the quality of the bioindicator data 267 based on the fact that three or more one-minute average data are measured when the measurement time is five minutes. The measurement time of "five minutes" is the measurement time set in the measurement time setting unit 512 of the setting screen 50. The average data may be average data for a period other than one minute, and the number of measurements may be four or more, or two or less. In addition, the times for calculating multiple average data may or may not overlap.

[0056] Similarly to the bioindicator data 267, the control unit 20 determines, as one of the quality criteria for the behavior index data 268, that three or more one-minute average data are measured when the measurement time is five minutes. The average data may be average data for a period other than one minute, and the number of measurements may be four or more, or two or less. The time for calculating a plurality of average data may or may not overlap. Furthermore, the control unit 20 determines, as another discrimination criterion, that the time difference between the bioindicator data 267 and the behavior index data 268 is within 30 seconds. The time difference of "30 seconds" may be less than 30 seconds, or may be greater than 30 seconds.

[0057] In addition, if it is not possible to obtain bioindicator data 267 or behavioral indicator data 268 that satisfies the discrimination criteria 80 in FIG. 8, a message indicating that the bioindicator data 267 or behavioral indicator data 268 could not be obtained (an alert may be issued) may be displayed on the setting screen 50 in FIG. 5.

[0058] Returning to FIG. 7, the control unit 20 executes a process of calculating the feature amount of the biometric data 267 of quality that satisfies the discrimination criterion 80 and the feature amount of the behavioral index data 268 of quality that satisfies the discrimination criterion 80 (S703). For example, when the biometric data 267 is gaze data, the feature amount is a dwell time, a frequency of switching gaze, an amount of blinking, and a frequency of turning back gaze. When the biometric data 267 is facial expression data, the feature amount is a facial muscle change rate, an upper face change rate, a lower face change rate, a number of face inclinations, and a head dwell time. When the behavioral index data 268 is operation amount data, the feature amount is a number of operation repetitions, an amount of operation movement, and the like. The control unit 20 calculates the feature amount of each feature of the acquired biometric data 267 and calculates the feature amount of each feature of the acquired behavioral index data 268.

[0059] Next, the control unit 20 selects a plurality of features that are synchronized in time and correlated with each other from among the plurality of features of the biometric data 267 and the plurality of features of the behavioral index data 268 (S704). Specifically, the control unit 20 performs cross-correlation processing of the feature amounts of the plurality of features. The cross-correlation processing is a process of calculating the correlation when the time axis of one of the two time series data is shifted, and in this embodiment, a cross-correlation coefficient of 1 to 10 is calculated. It is assumed that a feature with a high cross-correlation coefficient is a feature that is synchronized in time and highly correlated with each other, and a feature with a low cross-correlation coefficient is a feature that is not synchronized in time and has a low correlation with each other. FIG. 9 is a diagram showing a result 90 (cross-correlation coefficient) of the cross-correlation processing of the feature amounts of the plurality of features. In the result 90 of the cross-correlation processing of FIG. 9, the cross-correlation coefficients are indicated by 1 to 10. The control unit 20 selects features that are equal to or greater than a preset threshold (for example, threshold=6) as features that are synchronized in time and correlated with each other according to the result 90 of the cross-correlation processing of FIG. 9. It is to be noted that this threshold can be changed.

[0060] For example, when the threshold value is 6, the dwell time of the bioindicator data 267 is synchronized in time with and correlated with the gaze switching frequency, blink amount, and gaze turning back frequency of the bioindicator data, and the operation repetition count and operation movement amount of the behavior index data. In this embodiment, a description will be given assuming that a plurality of features (dwell time, gaze switching frequency, blink amount, and gaze turning back frequency) of the bioindicator data 267 and a plurality of features (operation repetition count and operation movement amount) of the behavior index data 268 are synchronized in time with and correlated with each other.

[0061] Next, the control unit 20 evaluates the attention adjustment ability of the measurer by comparing the selected multiple feature amounts with a predetermined judgment criterion (S705). FIG. 10A is a diagram showing the selected multiple features and the judgment criterion 101 set for each feature. For example, this judgment criterion 101 is stored in the attention adjustment ability evaluation DB 264. In the example of FIG. 10A, a judgment criterion for the number of touch operations (e.g., 40 times or more) and a judgment criterion for the amount of touch operation movement (e.g., 5000 pixels or more) which are characteristics of the behavior index data 268 are set. In addition, in the example of FIG. 10A, a judgment criterion for the retention time (e.g., 40 seconds or more), a judgment criterion for the frequency of switching the line of sight (e.g., 20 times or more), a judgment criterion for the amount of blinks (e.g., less than 20 times), and a judgment criterion for the frequency of turning back the line of sight (e.g., 10 times or more) which are characteristics of the biometric data 267 are set.

[0062] 10A, the features of the biometric data 267 are classified into the elements of attention regulation ability, selection, shifting, concentration, or distribution, and scores are set according to the classified elements. The scores are set so that the sum is 10, and for example, a higher score is set for selection and distribution, which are elements that are largely attributable to attention regulation ability, than for other elements (shifting and concentration).

[0063] Fig. 10B is a diagram showing feature amounts 102 of the respective features of the measurement data of healthy subjects that are referred to when setting the judgment criteria 101. The specific contents are as shown in Fig. 10B.

[0064] The control unit 20 compares each of the feature amounts of the multiple features selected in S704 with the criteria set for each feature, and calculates the total score of the scores set for the features that exceed the criteria. For example, if the feature amount of the dwell time of the measurement data exceeds the criteria, the feature amount of the gaze switching frequency exceeds the criteria, and the feature amounts of the other features do not exceed the criteria, the control unit 20 calculates a total score of "6" by adding up the score "4" set for the dwell time and the score "2" set for the gaze switching frequency. Then, the control unit 20 evaluates the user's ability to adjust attention according to the calculated total score (S705).

[0065] In the example of FIG. 10A, a score is set for the characteristic of the bioindicator data 267, but a score may be set for both the characteristic of the bioindicator data 267 and the characteristic of the behavior index data 268.

[0066] (Details of circadian rhythm evaluation process (S604)) Fig. 11 is a flowchart showing details of the process for evaluating circadian rhythm. The process for evaluating circadian rhythm will be described in detail with reference to Fig. 11. Each step of Fig. 11 is performed by the processor 21 of the control unit 20 executing the circadian rhythm evaluation program 262.

[0067] The control unit 20 reads the circadian rhythm data 269 (continuous sleep time, sleep satisfaction level) received in S601 (S1101).

[0068] Then, the control unit 20 evaluates the circadian rhythm according to the total score for the read circadian rhythm data 269 (S1102). FIG. 12 is a diagram showing the circadian rhythm data 269 and the score 120 set for each data. The score 120 is stored, for example, in the circadian rhythm evaluation DB 265. The score 120 in FIG. 12 is set according to the length of continuous sleep time and the degree of sleep satisfaction. Therefore, as in the example of FIG. 5, when the continuous sleep time is "4 hours" and the sleep satisfaction level is "not very satisfied", the control unit 20 calculates a total score of "8" by adding up the score "4" for the continuous sleep time and the score "4" for the sleep satisfaction level. Then, the control unit 20 evaluates the circadian rhythm of the person to be measured according to the calculated total score.

[0069] (Details of the process of estimating subjective cognitive decline (S605)) Fig. 13 is a flowchart showing details of the process of estimating the decline in subjective cognitive function. The process of estimating the decline in subjective cognitive function will be described in detail with reference to Fig. 13. In this embodiment, the decline in subjective cognitive function is estimated based on the total score related to the attention adjustment ability and the total score related to the circadian rhythm. Each step of Fig. 13 is executed by the processor 21 of the control unit 20 executing the SCD estimation program 263.

[0070] The control unit 20 inputs the total score related to the attention adjustment ability calculated in S705 (S1301).

[0071] Furthermore, the control unit 20 inputs the total score related to the circadian rhythm calculated in S1102 (S1302).

[0072] Next, the control unit 20 estimates a subjective decline in cognitive function (S1303) based on the total score related to the ability to regulate attention, the total score related to the circadian rhythm, and the SCD estimation DB 266. As shown in Fig. 14A, the SCD estimation DB 266 stores a table 141 that associates the total score related to the ability to regulate attention, the total score related to the circadian rhythm, and the degree of a sign of a subjective decline in cognitive function. The control unit 20 estimates that if the total score for the ability to regulate attention is "1 to 5" and the total score for the circadian rhythm is "1 to 5", there are no signs of subjective decline in cognitive function; if the total score for the ability to regulate attention is "1 to 5" and the total score for the circadian rhythm is "6 to 10", there are almost no signs of subjective decline in cognitive function; if the total score for the ability to regulate attention is "6 to 10" and the total score for the circadian rhythm is "1 to 5", there are slight signs of subjective decline in cognitive function; and if the total score for the ability to regulate attention is "6 to 10" and the total score for the circadian rhythm is "6 to 10", there are signs of subjective decline in cognitive function.

[0073] 14B, the control unit 20 displays a message corresponding to the subjective symptom of decline in cognitive function on the display device 43 of the information processing terminal 3 or the display unit of the browsing device 4 (S1304). This message table 142 is stored in, for example, the SCD estimation DB 266. For example, when the total score for the ability to regulate attention is "1-5" and the total score for the circadian rhythm is "1-5", the control unit 20 displays "No problem with circadian rhythm and attention regulation ability", when the total score for the ability to regulate attention is "1-5" and the total score for the circadian rhythm is "6-10", displays "Need to review circadian rhythm", when the total score for the ability to regulate attention is "6-10" and the total score for the circadian rhythm is "1-5", displays "Need to check progress of attention regulation ability", and when the total score for the ability to regulate attention is "6-10" and the total score for the circadian rhythm is "6-10", displays "Signs of subjective cognitive decline". The contents of the message shown in FIG. 14B are not limited to these words.

[0074] (Various screens 1510~1550) The estimation device 2 displays various screens on the display device 43 of the information processing terminal 3 or the display unit of the viewing device 4 according to the content of the result display set in the setting unit 54 of the setting screen 50 in Fig. 5. As shown in Figs. 15A to 15E, the estimation device 2 is capable of displaying a screen 1510 showing an estimation result of a subjective decline in cognitive function, a screen 1520 showing an estimation result (graph) of the subjective decline in cognitive function, a screen 1530 proposing a remedy for improving the subjective decline in cognitive function, a screen 1540 showing a transition of the estimation result of the subjective cognitive function, and a screen 1550 for setting up collaboration with other services.

[0075] (Screen 1510 showing estimated subjective cognitive decline) A screen 1510 displaying the estimated result of the level of decline in subjective cognitive function shows a mark 1511 indicating the total score related to the ability to regulate attention on a score bar 1512, and a mark 1513 indicating the total score related to circadian rhythm on a score bar 1514. This screen 1510 also displays a message 1515 according to the signs of decline in subjective cognitive function. In the example of FIG. 15A, since the total score related to the ability to regulate attention is "6 to 10" and the total score related to circadian rhythm is "6 to 10", "signs of subjective decline in cognitive function present" (see FIG. 14B) is displayed.

[0076] (Screen 1520 showing the estimated result (graph) of the subjective decline in cognitive function) A screen 1520 showing the estimated result (graph) of the subjective decline in cognitive function displays a graph 1521 in which the vertical axis indicates the total score related to the ability to regulate attention, and the horizontal axis indicates the total score related to circadian rhythm. A plot 1522 defined by the total score related to the ability to regulate attention and the total score related to circadian rhythm is displayed on this graph 1521. In addition, this screen 1520 displays a message 1523 according to the symptom of the subjective decline in cognitive function. In the example of FIG. 15B, since the total score related to the ability to regulate attention is "6 to 10" and the total score related to circadian rhythm is "6 to 10", "there is a sign of subjective decline in cognitive function" (see FIG. 14B) is displayed.

[0077] (Screen 1530, proposing measures to improve subjective cognitive decline) The screen 1530 proposing improvement measures introduces various trainings as recommended services for improving attention adjustment ability, and various information such as videos as recommended services for improving circadian rhythm. For example, the screen 1530 introduces training related to selectivity when the feature value of the retention time, which is a feature of the biometric data, is equal to or exceeds a criterion, and introduces training related to distribution when the frequency of gaze turning is equal to or exceeds a criterion.

[0078] (Screen 1540 showing the progress of subjective cognitive function estimates) A screen 1540 showing the transition of the estimation result of the subjective cognitive function displays past estimation results 1542 (plots in the figure) together with the estimation date and time on a graph 1541 similar to the graph 1521 in FIG. 15B.

[0079] (Screen 1550 for setting up integration with other services) Screen 1550, for setting up linkage with other services, is a screen for linking data measured using well-known services such as sleep evaluation services, brain training services, and fitness services as data for determining the subjective level of decline in cognitive function.

[0080] (Method for estimating subjective cognitive decline) Next, a method for estimating a subjective decline in cognitive function will be described with reference to the above-mentioned flowcharts.

[0081] The estimation method for estimating subjective cognitive decline is as follows: Receiving biometric data 267 indicating biometric information emitted by a subject who is the subject of measurement of subjective cognitive function decline, and behavioral index data 268 indicating the content of behavior performed by the subject (S602); Calculating feature amounts of a plurality of features from the biometric data 267 and calculating feature amounts of a plurality of features from the behavioral index data 268 (S703); Selecting a plurality of features that are synchronized in time and correlated with each other from among the plurality of features of the biometric data 267 and the plurality of features of the behavioral index data 268 (S704); Evaluating the ability of the person to adjust attention by comparing the feature quantities of the selected plurality of features with a predetermined criterion (S705); and and estimating a subjective decline in cognitive function based on the assessed ability to regulate attention (S1303).

[0082] Moreover, the method for estimating a subjective decline in cognitive function includes outputting an estimation result of the subjective decline in cognitive function (S606, FIG. 15A, FIG. 15B).

[0083] The method for estimating a subjective decline in cognitive function also includes outputting a history of the estimation results of the subjective decline in cognitive function (S606, FIG. 15D).

[0084] In addition, the estimation method for estimating a subjective decline in cognitive function includes outputting improvement recommendation information for improving the subjective decline in cognitive function corresponding to the estimated subjective decline in cognitive function (S606, FIG. 15C).

[0085] The method for estimating a subjective decline in cognitive function further includes receiving circadian rhythm data 269 indicating the circadian rhythm of the subject (S1101), and evaluating the circadian rhythm of the subject (S1102) using the circadian rhythm data 269. Then, evaluating the subject's ability to regulate attention (S705) includes estimating a decline in the subjective cognitive function of the subject based on the evaluated ability to regulate attention and the evaluated circadian rhythm.

[0086] In addition, evaluating the subject's ability to regulate attention (S705) includes evaluating the subject's ability to regulate attention according to the total score set for one or more features selected by comparison with a predetermined judgment criterion (Figure 10A).

[0087] In addition, the method for estimating a subjective decline in cognitive function includes determining whether or not the bioindicator data 267 and the behavioral index data 268 are of a quality that can be used to evaluate the ability to regulate attention, on condition that the measurement time difference between the accepted bioindicator data 267 and the behavioral index data 268 is within a predetermined time, and that a plurality of average data for a predetermined time period are measured for each of the bioindicator data 267 and the behavioral index data 268 (S702).

[0088] (Effects of this embodiment) In this embodiment, from among the multiple features of the biometric data 267 and the multiple features of the behavioral index data 268, multiple features that are synchronized in time and correlated with each other are selected, and the feature amounts of the selected multiple features are compared with a predetermined judgment criterion 101 (see FIG. 10A), thereby making it possible to evaluate the attention adjustment ability of the person being measured. Then, based on this evaluated attention adjustment ability, it is possible to estimate a subjective decline in cognitive function. As a result, by using the attention adjustment ability, it is possible to objectively evaluate the signs of dementia without physical burden, and by supporting the improvement of the attention adjustment ability, it is possible to prevent dementia at an extremely early stage.

[0089] Moreover, in this embodiment, the estimation result of the subjective decline in cognitive function can be displayed on the display device 43 of the information processing terminal 3 or on the display unit of the viewing device 4 (FIGS. 15A and 15B). Moreover, in this embodiment, the history of the estimation result of the subjective decline in cognitive function can be displayed on the display device 43 of the information processing terminal 3 or on the display unit of the viewing device 4 (FIG. 15D). This makes it possible to grasp the improvement or worsening of the subjective decline in cognitive function.

[0090] Furthermore, in this embodiment, improvement recommendation information for improving the subjective decline in cognitive function corresponding to the estimated subjective decline in cognitive function can be displayed (FIG. 15C).

[0091] Furthermore, in this embodiment, the subjective decline in cognitive function of the subject can be estimated based not only on the assessed ability to regulate attention, but also on the assessed ability to regulate attention and the assessed circadian rhythm.

[0092] In addition, in this embodiment, by setting a score according to the element of the ability to regulate attention, namely, selection, shift, concentration, or distribution, it is possible to weight the element attributable to the ability to regulate attention, thereby making it possible to accurately evaluate the ability to regulate attention.

[0093] In this embodiment, it is determined whether the bioindicator data 267 and the behavior index data 268 are of a quality that can be used to evaluate the ability to adjust attention, under the condition that the difference in measurement time between the bioindicator data 267 and the behavior index data 268 is within a predetermined time, and that a plurality of average data are measured for a predetermined time within the measurement time for each of the bioindicator data 267 and the behavior index data 268. This makes it possible to accurately evaluate the ability to adjust attention using the high-quality bioindicator data 267 and the behavior index data 268.

[0094] <Modification> The present invention is not limited to the above-described embodiment, and includes various modified examples. For example, the above-described embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to those having all of the configurations described. In addition, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. In addition, it is possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

[0095] For example, each criterion (e.g., a retention time of 40 seconds or more) of the criterion 101 in Fig. 10A is merely an example, and each criterion may be changed according to the accumulation of measurement data. Also, the scores for classifying the degree of the subjective sign of cognitive decline in Fig. 14A are not limited to the scores 1 to 5 and 6 to 10 related to the ability to regulate attention and the scores 1 to 5 and 6 to 10 related to the circadian rhythm. The range of the score related to the ability to regulate attention may not be the same as the range of the score related to the circadian rhythm, and the number of the range of the score related to the ability to regulate attention and the range of the score related to the circadian rhythm may be one or three or more.

[0096] In addition, in the above-described embodiment, the evaluation results of the ability to regulate attention and the evaluation results of the circadian rhythm were used to estimate a subjective decline in cognitive function, but the evaluation results of the ability to regulate attention (without using the evaluation results of the circadian rhythm) may also be used to estimate a subjective decline in cognitive function. [Explanation of symbols]

[0097] 1: Information processing system 2: Estimation device (information processing device) 3: Information processing terminal 4: Viewing device 5: Network 20: Control unit 21: Processor 22: Memory 23: Input device 24: Output device 25:Communication equipment 26: Storage device 261: Attention Regulation Ability Assessment Program 262: Circadian Rhythm Evaluation Program 263: SCD Estimation Program 264: Attention Adjustment Ability Evaluation DB 265: Circadian rhythm evaluation database 266: SCD Estimation Database 267: Biometric data 268: Behavioral indicator data 269: Circadian rhythm data 31: Attention regulation ability evaluation section 32: Circadian rhythm evaluation section 33: SCD estimation part 34: Output section 41: Processor 42: Memory 43:Display device 44: Touch sensor 45:Communication equipment 46: Storage device 461: SCD diagnosis app

Claims

1. An information processing device for estimating a subjective decline in cognitive function, A receiving unit that receives biometric data indicating biometric information emitted by a subject who is a subject of measurement of a subjective decline in cognitive function, and behavioral index data indicating the content of a behavior performed by the subject; A control unit including a processor and a memory, The control unit is Calculating feature amounts of a plurality of characteristics from the biological index data, and calculating feature amounts of a plurality of characteristics from the behavior index data; selecting a plurality of features from among the plurality of features of the biometric data and the plurality of features of the behavioral index data, the plurality of features being synchronized in time with each other and correlated with each other; evaluating the person's ability to adjust attention by comparing the feature quantities of the selected plurality of features with a predetermined criterion; A subjective decline in cognitive function is estimated based on the assessed ability to regulate attention.

23. An information processing apparatus comprising:

2. The control unit is Outputting the subjective estimation result of the decline in cognitive function 2. The information processing apparatus according to claim 1,

3. The control unit is Outputting a history of the subjective cognitive decline estimation results 2. The information processing apparatus according to claim 1,

4. The control unit is Outputting improvement recommendation information for improving the subjective cognitive decline corresponding to the estimated result of the subjective cognitive decline.

2. The information processing apparatus according to claim 1,

5. The receiving unit receives circadian rhythm data indicating a circadian rhythm of the subject, The control unit evaluates the circadian rhythm of the subject using the circadian rhythm data, A subjective cognitive function decline of the subject is estimated based on the evaluated attention adjustment ability and the evaluated circadian rhythm.

2. The information processing apparatus according to claim 1,

6. The plurality of features of the biomarker data are classified into elements of attention adjustment ability, such as selection, shift, concentration, or distribution, and a score is set according to the classified elements; The control unit evaluates the ability of adjusting the attention of the subject according to a total score set for one or more features selected by comparison with the predetermined criterion.

2. The information processing apparatus according to claim 1,

7. The control unit determines whether the bioindicator data and the behavior index data are of a quality that can be used to evaluate an ability to adjust attention, on the condition that a measurement time difference between the bioindicator data and the behavior index data received by the receiving unit is within a predetermined time, and that average data for a predetermined time period is measured for each of the bioindicator data and the behavior index data.

2. The information processing apparatus according to claim 1,

8. The control unit issues an alert when the biological index data and the behavior index data do not satisfy the condition.

8. The information processing apparatus according to claim 7,

9. A method for estimating a subjective decline in cognitive function, comprising: receiving biometric data indicating biometric information emitted by a subject who is a subject of measurement of subjective cognitive decline, and behavioral index data indicating the content of behavior performed by the subject; calculating feature amounts of a plurality of characteristics from the biological index data, and calculating feature amounts of a plurality of characteristics from the behavior index data; selecting a plurality of features from among the plurality of features of the biometric data and the plurality of features of the behavioral index data, the plurality of features being synchronized in time with each other and correlated with each other; Evaluating the ability of the person to adjust attention by comparing the feature quantities of the selected plurality of features with a predetermined criterion; and and estimating a subjective decline in cognitive function based on the assessed ability to regulate attention. The estimation method according to claim 1,

10. and outputting the subjective estimation result of the decline in cognitive function. The method according to claim 9 .

11. and outputting a history of the subjective cognitive decline estimation result. The method according to claim 9 .

12. and outputting improvement recommendation information for improving the subjective cognitive function decline corresponding to the estimated result of the subjective cognitive function decline. The method according to claim 9 .

13. receiving circadian rhythm data indicative of the circadian rhythm of the subject; and The method further comprises: evaluating the circadian rhythm of the subject using the circadian rhythm data; Evaluating the subject's ability to regulate attention includes estimating a decline in the subjective cognitive function of the subject based on the evaluated ability to regulate attention and the evaluated circadian rhythm. The method according to claim 9 .

14. The plurality of features of the biomarker data are classified into elements of attention adjustment ability, such as selection, shift, concentration, or distribution, and a score is set according to the classified elements; Evaluating the ability of the subject to adjust attention includes evaluating the ability of the subject to adjust attention according to a total score set for one or more features selected by comparison with the predetermined criterion. The method according to claim 9 .

15. and determining whether or not the bioindicator data and the behavioral index data are of a quality that can be used to evaluate attention adjustment ability, on the condition that a measurement time difference between the accepted bioindicator data and the behavioral index data is within a predetermined time, and that average data for a predetermined time period is measured for each of the bioindicator data and the behavioral index data. The method according to claim 9 .

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