Dementia detection device, dementia detection method, and dementia detection program

Abstract

To provide a dementia diagnosis device that can accurately determine the likelihood of a subject developing dementia. [Solution] The dementia determination device 30 of the present invention includes: an acquisition unit that acquires information regarding the condition of a subject 50; an evaluation unit that quantitatively evaluates the cognitive function of the subject 50 over a unit period based on the information regarding the condition acquired by the acquisition unit; a storage unit that stores the evaluation results from the evaluation unit for multiple consecutive unit periods; and a determination unit that determines the possibility of the subject 50 developing dementia based on the evaluation results for multiple consecutive unit periods stored in the storage unit.

Description

Technical Field

[0001] The present invention relates to a dementia determination device, a dementia determination method, and a dementia determination program.

Background Art

[0002] With the advent of an aging society, the number of people suffering from dementia is also on the rise. Early detection and early treatment are important for dementia.

[0003] In this regard, Patent Document 1 below discloses a dementia determination device that determines whether there is a possibility of dementia in an operator of a household electrical appliance based on the operation history of the household electrical appliance. The dementia determination device of Patent Document 1 extracts incorrect operations from the operation history, and when the number of incorrect operations reaches a predetermined number, it determines that there is a possibility of dementia in the operator of the household electrical appliance. According to such a configuration, it becomes possible to receive early diagnosis and treatment of dementia in a hospital or the like.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] [ However, since the above-mentioned dementia determination device determines the possibility of dementia based on the number of incorrect operations, even when the operator's physical condition is temporarily poor and there is an incorrect operation due to this, it is determined that there is a possibility of dementia in the operator, which is not preferable. For this reason, it is desired to more accurately determine the possibility of developing dementia.

[0006] This invention has been made in view of the above-mentioned problems. Accordingly, the object of this invention is to provide a dementia diagnosis device, a dementia diagnosis method, and a dementia diagnosis program that can accurately determine the likelihood of a subject developing dementia. [Means for solving the problem]

[0007] The above objectives of the present invention are achieved by the following means.

[0008] (1) A dementia detection device comprising: an acquisition unit that acquires information about the condition of a subject; an evaluation unit that quantitatively evaluates the cognitive function of the subject over a unit period based on the information about the condition acquired by the acquisition unit; a storage unit that stores the evaluation results from the evaluation unit for a plurality of consecutive unit periods; and a determination unit that determines the possibility of the subject developing dementia based on the evaluation results for a plurality of consecutive unit periods stored in the storage unit.

[0009] (2) The dementia determination device according to (1) above, wherein the determination unit determines that there is a possibility of dementia developing in the subject if the unit period for which the evaluation result indicating the possibility of cognitive decline is obtained is a predetermined number of consecutive units, and determines that there is no possibility of dementia developing in the subject if the unit period for which the evaluation result indicating the possibility of cognitive decline is obtained is not a predetermined number of consecutive units.

[0010] (3) The dementia diagnosis device according to (1) or (2) above, wherein the information relating to the state includes one or more indicators from among indicators relating to behavior, indicators relating to sleep, and indicators relating to emotion.

[0011] (4) The dementia detection device described in (3) above, wherein the behavioral indicators, sleep indicators, and emotional indicators are calculated from the subject's imaging data, body movement data, and voice data, respectively.

[0012] (5) The dementia determination device according to (1) or (2) above, wherein the evaluation unit quantitatively evaluates the cognitive function of a subject for multiple subjects using a learning model that has learned the relationship between information about the subject's condition and a quantitative value of the subject's cognitive function.

[0013] (6) The dementia detection device according to (1) or (2) above, further comprising a notification unit that notifies the subject if the determination unit determines that the subject may be at risk of developing dementia.

[0014] (7) The dementia detection device according to (6) above, wherein the cognitive functions are classified into memory function, executive function, attention function, and language function, and the notification unit notifies of the possibility of dementia onset in association with at least one cognitive function selected from the memory function, executive function, attention function, and language function.

[0015] (8) The dementia diagnosis device described in (6) above, wherein the notification unit causes the terminal device's display unit to display text describing facts about the subject's condition, text warning of the possibility of cognitive decline, and text encouraging a medical examination or testing.

[0016] (9) A dementia determination method comprising: (a) obtaining information about the condition of a subject; (b) quantitatively evaluating the cognitive function of the subject over a unit period based on the information about the condition obtained in step (a); (c) storing the evaluation results from step (b) in a memory unit for a plurality of consecutive unit periods; and (d) determining the possibility of the subject developing dementia based on the evaluation results for a plurality of consecutive unit periods stored in the memory unit.

[0017] A dementia determination program that causes a computer to execute: a procedure (a) for acquiring information regarding the state of a subject; a procedure (b) for quantitatively evaluating the cognitive function of the subject in a unit period based on the information regarding the state acquired in the procedure (a); a procedure (c) for storing the evaluation results in the procedure (b) in a storage unit for a plurality of consecutive unit periods; and a procedure (d) for determining the likelihood of onset of dementia of the subject based on the evaluation results of the plurality of consecutive unit periods stored in the storage unit.

Advantages of the Invention

[0018] According to the present invention, the likelihood of onset of dementia of a subject can be accurately determined.

Brief Description of the Drawings

[0019] The advantages and features provided by one or more embodiments of the present invention will be more fully understood from the following detailed description and the accompanying drawings, which are for illustrative purposes only and are not intended to define the limitations of the present invention. [Figure 1] It is a diagram showing a schematic configuration of a dementia determination system. [Figure 2] It is a block diagram showing a schematic configuration of a detection device. [Figure 3] It is a block diagram showing a schematic configuration of a mobile terminal device. [Figure 4] It is a block diagram showing a schematic configuration of a server device. [Figure 5] It is a diagram showing the stored contents of the storage unit of a server device. [Figure 6] It is a diagram showing an example of an index related to behavior. [Figure 7] It is a diagram showing an example of an index related to sleep. [Figure 8] It is a diagram showing an example of an index related to emotion. [Figure 9] It is a flowchart showing the procedure of quantitative evaluation processing. [Figure 10] It is a diagram for explaining an example of a quantitative value of cognitive function. [Figure 11] This is a flowchart showing the procedure for determining whether dementia is present. [Figure 12] This is a diagram illustrating the process for determining dementia. [Figure 13] This figure shows an example of a notification screen. [Modes for carrying out the invention]

[0020] Embodiments of the present invention will be described below with reference to the drawings. However, the scope of the present invention is not limited to the disclosed embodiments.

[0021] Figure 1 is a diagram showing the schematic configuration of a dementia diagnosis system 1 to which a dementia diagnosis device according to one embodiment of the present invention is applied.

[0022] As shown in Figure 1, the dementia diagnosis system 1 comprises a detection device 10, a mobile terminal device 20, and a server device 30. The detection device 10, the mobile terminal device 20, and the server device 30 are configured to communicate with each other via a network 40.

[0023] The detection device 10 is installed in the room of the subject 50. The subject 50's room is either in a nursing home or hospital, or in the subject 50's home. The mobile terminal device 20 is used by staff working at the nursing home or hospital, or by the subject 50's family. The network 40 consists of the internet or an intranet.

[0024] <Detection device 10> Figure 2 is a block diagram showing the schematic configuration of the detection device 10. The detection device 10 is installed as a sensor box on the ceiling or upper part of the wall of the room where the subject 50 lives.

[0025] As shown in Figure 2, the detection device 10 comprises a control unit 11, a communication unit 12, a camera 13, a Doppler sensor 14, and a microphone 15, which are interconnected by a bus.

[0026] The control unit 11 is composed of a CPU (Central Processing Unit) and memory such as RAM (Random Access Memory) and ROM (Read Only Memory), and controls each of the above parts and performs various calculation processes according to the program.

[0027] The communication unit 12 is an interface for communicating with other devices, and various wired or wireless communication interfaces are used.

[0028] Camera 13 captures images of the subject 50 from the ceiling or upper part of the wall of the living room and outputs the image data of the subject 50.

[0029] The Doppler sensor 14 transmits and receives microwaves to the subject 50 to detect the subject 50's body movements (for example, breathing) and outputs the subject 50's body movement data.

[0030] The microphone 15 captures the sound from inside the room of the subject 50 and outputs the voice data of the subject 50.

[0031] <Mobile terminal device 20> Figure 3 is a block diagram showing the schematic configuration of a mobile terminal device 20. The mobile terminal device 20 is, for example, a smartphone or a tablet device.

[0032] As shown in Figure 3, the mobile terminal device 20 comprises a control unit 21, a storage unit 22, a communication unit 23, and an operation display unit 24, which are interconnected by a bus. Note that, to avoid repetition in the explanation, the parts of the mobile terminal device 20 that have the same functions as those of the detection device 10 will not be described.

[0033] The storage unit 22 consists of an SSD (Solid State Drive) and an HDD (Hard Disk Drive) and stores various programs and data.

[0034] The operation display unit 24 is, for example, a touch panel display that displays various information and accepts various inputs from the user.

[0035] <Server device 30> Figure 4 is a block diagram showing the schematic configuration of the server device 30. The server device 30 corresponds to the dementia diagnosis device of the present invention.

[0036] As shown in Figure 4, the server device 30 comprises a control unit 31, a storage unit 32, and a communication unit 33, which are interconnected by a bus. Note that the above-mentioned parts of the server device 30 have the same functions as the above-mentioned parts of the detection device 10 and the mobile terminal device 20, so their descriptions are omitted.

[0037] Figure 5 shows the contents of the storage unit 32 of the server device 30. As shown in Figure 5, the storage unit 32 of the server device 30 stores quantitative evaluation data 100 regarding the cognitive function of the subject 50. The quantitative evaluation data 100 is data that includes the results of a weekly quantitative evaluation of the cognitive function of the subject 50 for multiple weeks (for example, 4 weeks).

[0038] Furthermore, the storage unit 32 of the server device 30 stores programs corresponding to the acquisition unit 110, evaluation unit 120, determination unit 130, and notification unit 140. The acquisition unit 110 acquires information regarding the status of the subject 50. The evaluation unit 120 includes a learning model that has learned the relationship between information regarding the status of multiple subjects and quantitative values ​​of cognitive function, and quantitatively evaluates the cognitive function of the subject 50 on a weekly basis based on the information regarding the subject 50's status. The determination unit 130 determines the possibility of the subject 50 developing dementia based on the quantitative evaluation results for several consecutive weeks. If the determination unit 130 determines that the subject 50 may be at risk of developing dementia, the notification unit 140 notifies the mobile terminal device 20 accordingly. The functions of each of the above units are performed by the control unit 31 executing the corresponding programs.

[0039] Furthermore, the detection device 10, the mobile terminal device 20, and the server device 30 may have components other than those described above, and may not have some of the components described above.

[0040] In the dementia assessment system 1 configured as described above, the detection device 10 collects imaging data, movement data, and voice data of the subject 50 24 hours a day. Then, from the daily imaging data, movement data, and voice data, values ​​of various indicators, which are information about the subject 50's condition, are calculated on a daily basis, and based on the values ​​of each indicator over seven days, the cognitive function of the subject 50 is quantitatively evaluated on a weekly basis.

[0041] In addition, the dementia assessment system 1 performs a quantitative evaluation of the cognitive function of the subject 50 on a weekly basis, and the weekly quantitative evaluation results are stored in the storage unit 32 of the server device 30. If quantitative evaluation results indicating a possible decline in cognitive function are obtained for several consecutive weeks (for example, 4 weeks), it is determined that the subject 50 may be at risk of developing dementia, and this fact is notified to the mobile terminal device 20. The operation of the dementia assessment system 1 will be explained below with reference to Figures 6 to 13.

[0042] First, with reference to Figures 6 to 8, the indices used for the quantitative evaluation of the cognitive function of the 50 subjects will be described. In this embodiment, the cognitive function of the 50 subjects is quantitatively evaluated based on a total of 54 indices, including indicators related to behavior, sleep, and emotion.

[0043] Figure 6 shows an example of behavioral indicators. The behavioral indicators include 25 indicators. The values ​​of these indicators are calculated from imaging data obtained by imaging the subject 50 with the camera 13 of the detection device 10.

[0044] As shown in Figure 6, the behavioral indicators include indicators 1-6 for movement range, indicators 7-14 for repetitive behavior, indicator 15 for area exceeding the designated area, indicator 16 for movement speed, indicators 17-20 for stopping, indicators 21-24 for movement time and distance, and indicator 25 for unsteadiness.

[0045] The movement range indicators 1-6 include daytime movement range indicators 1-3 and nighttime movement range indicators 4-6, and are calculated based on the area of ​​the areas visited by the 50 subjects outside of bed. The repetitive behavior indicators 7-14 include daytime repetitive behavior indicators 7-10 and nighttime repetitive behavior indicators 11-14, and are calculated based on the number and duration of repetitive behaviors by the 50 subjects. The overhang area indicator 15 is calculated based on the overhang area from high-frequency routes outside of bed at night, and the movement speed indicator 16 is calculated based on the movement speed of the 50 subjects outside of bed at night. The stopping indicators 17-20 are calculated based on the time and number of times the subjects 50 stop outside of daily activities outside of bed, and the movement time / distance indicators 21-24 are calculated based on the stay time and distance traveled by the 50 subjects outside of bed. The unsteadiness indicator 25 is calculated based on the degree of unsteadiness of the trajectory of the 50 subjects outside of bed at night. Since the technique for calculating behavioral indicators from the subject's imaging data is a publicly known technique, a detailed explanation will be omitted.

[0046] Figure 7 shows an example of sleep-related indicators. The sleep-related indicators include nine indicators. The values ​​of these indicators are calculated from body movement data obtained by detecting the body movements of the subject 50 using the Doppler sensor 14 of the detection device 10.

[0047] As shown in Figure 7, the sleep indicators include indicators 1-5 for nighttime sleep duration and sleep rate, indicators 6-7 for nighttime daytime sleep ratio, and indicators 8-9 for nighttime sleep stability.

[0048] Indicators 1-5 for nighttime sleep duration and sleep rate are calculated based on the nighttime sleep duration and nighttime wake duration of 50 subjects. Indicators 6-7 for nighttime daytime sleep ratio are calculated based on the daytime sleep duration and nighttime sleep duration of 50 subjects. Indicators 8-9 for nighttime sleep stability are calculated based on the sleep pattern stability of 50 subjects from midnight to 5 AM. Note that the technology for calculating sleep-related indicators from subject movement data is a publicly known technology, so a detailed explanation is omitted.

[0049] Figure 8 shows an example of an index related to emotion. The index related to emotion includes 20 indicators. The values ​​of these indicators are calculated from audio data obtained by capturing sounds in the room using the microphone 15 of the detection device 10.

[0050] As shown in Figure 8, the emotional indicators include an energy indicator 1, a satisfaction indicator 2, agitation indicator 3, aggression indicator 4, stress indicator 5, uncertainty indicator 6, excitement indicator 7, concentration indicator 8, emotion and cognition indicator 9, and hesitation indicator 10. Furthermore, the emotional indicators include a brain power indicator 11, confusion indicator 12, focused thinking indicator 13, imaginative activity indicator 14, extreme emotion indicator 15, passion indicator 16, mood indicator 17, expectation indicator 18, dissatisfaction indicator 19, and confidence indicator 20. In this embodiment, values ​​from 0 to 10 are calculated on a daily basis from one day's worth of voice data of the subject 50. Note that the technology for analyzing the speaker's emotions from voice is a known technology, so a detailed explanation is omitted.

[0051] Next, referring to Figure 9, we will explain the quantitative evaluation process for quantitatively assessing the cognitive function of the 50 subjects on a weekly basis.

[0052] Figure 9 is a flowchart showing the procedure for quantitative evaluation processing performed by the server device 30. The processing shown in the flowchart in Figure 9 is executed by the control unit 31 according to the program stored in the storage unit 32 of the server device 30.

[0053] (Step S101) First, the server device 30 acquires information regarding the status of the subject 50. More specifically, the server device 30 obtains the weekly (unit period) value for each of the 54 indicators from the weekly data of the subject 50 collected by the detection device 10.

[0054] In this embodiment, the server device 30 calculates seven days' worth of daily values ​​for the 25 behavioral indicators (see Figure 6) from the imaging data of the subject 50 collected by the detection device 10 over one week. Then, the server device 30 obtains a weekly value by averaging the seven days' worth of values ​​for each of the 25 indicators.

[0055] Furthermore, the server device 30 calculates seven daily values ​​for the nine sleep-related indicators (see Figure 7) from the body movement data of the subjects 50 collected by the detection device 10 over one week. Then, the server device 30 obtains a weekly value by averaging the seven daily values ​​for each of the nine indicators.

[0056] Furthermore, the server device 30 calculates seven days' worth of daily values ​​for the 20 emotional indicators (see Figure 8) from the voice data of the subjects 50 collected by the detection device 10 over one week. Then, the server device 30 obtains a weekly value by averaging the seven days' worth of values ​​for each of the 20 indicators.

[0057] (Step S102) Next, the server device 30 quantitatively evaluates the cognitive function of the subject 50. More specifically, the server device 30 calculates a quantitative value of the cognitive function of the subject 50 from the values ​​of the 54 indicators obtained in the process of step S101.

[0058] Figure 10 illustrates an example of a quantitative value for cognitive function. In this embodiment, the score from the Mini-Mental State Examination (MMSE) is used as the quantitative value for cognitive function. As shown in Figure 10, the MMSE assessment items include 11 items: orientation to time, orientation to place, auditory-verbal memory, attention and calculation, recall, naming, repetition, comprehension, reading, writing, and drawing. Each item is assigned a score, and the score for each item is calculated as a quantitative value. A lower score indicates a potential decline in cognitive function.

[0059] In this embodiment, pairs of values ​​for 54 indicators and MMSE test results are prepared for multiple subjects. Cognitive function is quantitatively evaluated by a learning model (multimodal AI) that has been trained with each of the 54 indicator values ​​as an explanatory variable and each of the scores for the 11 items as an objective variable. Specifically, the values ​​of the 54 indicators for subject 50 obtained in step S101 are input into the learning model, and as a result, the scores for each of the 11 items are output from the learning model as quantitative values ​​of the cognitive function of subject 50.

[0060] (Step S103) Next, the server device 30 stores the evaluation results for the week and terminates the process. More specifically, the server device 30 stores the scores for each of the 11 items calculated in step S102 in the storage unit 32 and terminates the process.

[0061] As described above, according to the flowchart shown in Figure 9, the cognitive function of subject 50 is quantitatively evaluated on a weekly basis based on information regarding subject 50's condition, and the quantitative evaluation results are stored in the memory unit 32. Specifically, cognitive function is scored for 11 items of the MMSE based on the values ​​of 54 indicators related to subject 50's condition, and the score for each item is stored in the memory unit 32.

[0062] In addition, in the dementia diagnosis system 1 of this embodiment, the above quantitative evaluation process is performed weekly, and the quantitative evaluation results for the cognitive function of the subject 50 over several weeks are stored in the memory unit 32. Based on the quantitative evaluation results for several weeks, the possibility of the subject 50 developing dementia is determined. The operation of the server device 30 that determines the possibility of the subject 50 developing dementia will be described below with reference to Figures 11 to 13.

[0063] Figure 11 is a flowchart showing the procedure for dementia diagnosis processing performed by the server device 30. The processing shown in the flowchart in Figure 11 is executed by the control unit 31 according to the program stored in the storage unit 32 of the server device 30.

[0064] (Step S201) First, the server device 30 reads out quantitative evaluation data for one item. More specifically, the server device 30 reads out the scores for the most recent four weeks for one item from the scores for multiple weeks of the 11 items stored in the memory unit 32. For example, the server device 30 reads out four scores for the most recent four weeks for item 3, "Auditory and Speech Recall," from the memory unit 32. The maximum score for "Auditory and Speech Recall" is 3 points, and the score read out will be either 0, 1, 2, or 3 points.

[0065] (Step S202) Next, the server device 30 compares the quantitative values ​​with the judgment values. More specifically, the server device 30 compares the four scores from the most recent four weeks read in step S201 with the judgment values ​​from the previous week (the third week of the most recent four weeks). Here, the judgment values ​​are determined by the maximum score for each item; for example, in the case of "auditory language memory," the judgment value is usually "3."

[0066] (Step S203) Next, the server device 30 determines whether all quantitative values ​​are smaller than the judgment value. More specifically, the server device 30 determines whether all four scores for the most recent four weeks are smaller than the judgment value for the previous week (week 3).

[0067] If it is determined that all quantitative values ​​are smaller than the judgment value (step S203: NO), the server device 30 proceeds to step S205. On the other hand, if it is determined that all quantitative values ​​are smaller than the judgment value (step S203: YES), the server device 30 proceeds to step S204.

[0068] (Step S204) If all quantitative values ​​are determined to be smaller than the judgment value (step S203: YES), the server device 30 decreases the judgment value by "1" and proceeds to step S208. More specifically, the server device 30 changes the judgment value for the latest week (week 4) to a value that is "1" less than the judgment value for the previous week (week 3) and proceeds to step S208.

[0069] (Step S205) On the other hand, in the process of step S203, if it is not determined that all quantitative values ​​are smaller than the judgment value (step S203: NO), the server device 30 determines whether all quantitative values ​​are larger than the judgment value. More specifically, the server device 30 determines whether all four scores for the most recent four weeks are larger than the judgment value for the previous week.

[0070] If it is determined that all quantitative values ​​are not greater than the judgment value (step S205: NO), the server device 30 proceeds to step S207. On the other hand, if it is determined that all quantitative values ​​are greater than the judgment value (step S205: YES), the server device 30 proceeds to step S206.

[0071] (Step S206) If all quantitative values ​​are determined to be greater than the judgment value (step S205: YES), the server device 30 increases the judgment value by "1" and proceeds to step S208. More specifically, the server device 30 changes the judgment value for the latest week (week 4) to a value that is "1" higher than the judgment value for the previous week (week 3) and proceeds to step S208.

[0072] (Step S207) On the other hand, if none of the quantitative values ​​are determined to be greater than the judgment value (step S205: NO), the server device 30 maintains the judgment value as is and proceeds to the process in step S208. More specifically, the server device 30 maintains the judgment value for the latest week (week 4) at the same value as the judgment value for the previous week (week 3) and proceeds to the process in step S208.

[0073] (Step S208) Next, the server device 30 determines whether the evaluation has been completed for all 11 items. More specifically, the server device 30 determines whether the judgment values ​​for the most recent week (week 4) have been calculated for all 11 items of the MMSE.

[0074] If it is determined that the evaluation has not been completed for all 11 items (step S208: NO), the server device 30 returns to the process in step S201. As a result, the processes in steps S201 to S208 are repeated until a judgment value is calculated for all 11 items.

[0075] On the other hand, if it is determined that the evaluation of all 11 items has been completed (step S208: YES), the server device 30 proceeds to the process in step S209.

[0076] (Step S209) If it is determined that the evaluation has been completed for all 11 items (Step S208: YES), the server device 30 determines whether there are any items whose judgment value has decreased. More specifically, the server device 30 determines whether there are any items among the 11 MMSE items whose judgment value for the most recent week has decreased by "1" compared to the previous week.

[0077] If it is determined that there are no items whose judgment value has decreased (step S209: NO), the server device 30 terminates the process.

[0078] On the other hand, if it is determined that there are items whose judgment values ​​have decreased (step S209: YES), the server device 30 notifies the mobile terminal device 20 and terminates processing. More specifically, the server device 30 determines that the subject 50 may have developed dementia, notifies the mobile terminal device 20 of this fact, and terminates processing.

[0079] As described above, according to the flowchart shown in Figure 11, the possibility of dementia developing in subject 50 is determined based on the quantitative evaluation results of the subject's cognitive function over the past four weeks. Specifically, if the evaluation results indicate a possibility of cognitive decline for four consecutive weeks, it is determined that subject 50 has a possibility of developing dementia, and this is notified to the mobile terminal device 20. On the other hand, if the evaluation results do not indicate a possibility of cognitive decline for four consecutive weeks, it is determined that subject 50 does not have a possibility of developing dementia, and the process ends.

[0080] Figure 12 is a diagram illustrating the dementia assessment process. Figure 12 uses the example of item 3, "Auditory and Speech Recall," as the quantitative assessment item. "Auditory and Speech Recall" is scored out of 3 points, and if there is no abnormality in cognitive function, both the quantitative value and the assessment value will be "3." Figure 12 also shows the quantitative assessment results for 50 subjects over a 10-week period.

[0081] As shown in Figure 12, in the most recent four weeks (weeks 7 to 10), all four quantitative values ​​are lower than the judgment value of "3" in week 9. In this case, the judgment value for week 10 is changed to "2". As a result, the server device 30 determines that the subject 50 may be at risk of developing dementia and notifies the mobile terminal device 20 accordingly.

[0082] On the other hand, during the first four weeks (weeks 1 to 4), although the quantitative value of "2" in week 4 is lower than the judgment value of "3" in week 3, the quantitative values ​​for the remaining three weeks (weeks 1 to 3) are the same as the judgment value of "3" in week 3. In this case, the judgment value for week 4 is maintained at "3". As a result, the server device 30 determines that the change in the quantitative value is temporary and that there is no possibility of dementia developing in the subject 50, and terminates the process.

[0083] Similarly, in weeks 7, 8, and 9, there were no consecutive weeks during which the quantitative value was lower than the judgment value. Therefore, the change in the quantitative value was considered temporary, and it was determined that there was no possibility of dementia developing in subject 50.

[0084] With this configuration, the likelihood of dementia developing in each of the 50 subjects is determined based on the evaluation results of their cognitive function over multiple consecutive unit periods (for example, 4 weeks), thus allowing for an accurate determination of the likelihood of dementia developing in each subject.

[0085] Finally, referring to Figure 13, we will explain the notification screen that informs the 50 subjects that they may be at risk of developing dementia.

[0086] Figure 13 shows an example of a notification screen 200. The notification screen 200 is displayed, for example, on the operation display unit 24 of the mobile terminal device 20.

[0087] As shown in Figure 13, the notification screen 200 includes a graph display unit 210, an evaluation result display unit 220, and a text display unit 230.

[0088] The graph display unit 210 displays a graph showing the time-dependent changes in the values ​​of indicators that indicate a decline in cognitive function, selected from the multiple indicators mentioned above. For example, the graph display unit 210 displays a graph of the indicator for standing still, which increases with a decline in cognitive function, and a graph of the indicator for continuous nighttime sleep duration, which decreases with a decline in cognitive function.

[0089] The evaluation result display unit 220 displays the evaluation results of the cognitive function of the subject 50, associating them with memory function, executive function, attention function, and language function. In this embodiment, the 11 items of the MMSE are classified into memory function, executive function, attention function, and language function, and the evaluation results are displayed. For example, item 5, "Recall," and item 7, "Repetition," are classified into memory function, so if the scores for these items are low, the evaluation result display unit 220 displays an evaluation result indicating that memory function is impaired. In contrast to this embodiment, in addition to the above four functions, the evaluation results of visuospatial cognitive function may also be displayed as part of the cognitive function evaluation results.

[0090] The text display unit 230 displays text describing facts about the subject 50's condition, text reminding the subject of the possibility of cognitive decline, and text encouraging a diagnosis or examination (cognitive function test) to confirm the onset of dementia. The content of the text describing facts about the subject 50's condition may correspond to the content displayed on the graph display unit 210.

[0091] With this configuration, users of the mobile terminal device 20 (staff at the care facility or family members of the subject 50) can quickly identify if the subject 50 is at risk of developing dementia. In addition, users of the mobile terminal device 20 can also identify the type of cognitive function (for example, memory function) that may be affected by the development of dementia.

[0092] The present invention is not limited to the embodiments described above, and can be modified in various ways within the scope of the claims.

[0093] For example, in the embodiment described above, the cognitive function of the subject was quantitatively evaluated based on three types of indicators: behavioral indicators, sleep indicators, and emotional indicators. However, the information on the subject's state used for quantitative evaluation of their cognitive function is not limited to these three types of indicators. For example, cognitive function may be quantitatively evaluated using one or two indicators selected from the three types. Alternatively, cognitive function may be quantitatively evaluated using one or more indicators selected from 25 behavioral indicators. Or, other information different from the indicators described above may be used. Furthermore, the items used for quantitative evaluation of cognitive function are not limited to the 11 items of the MMSE, and various parameters may be used.

[0094] Furthermore, in the embodiments described above, the example given was that the server device 30 quantitatively evaluates the cognitive function of the subject on a weekly basis. However, the unit period for quantitatively evaluating cognitive function is not limited to one week; for example, quantitative evaluation may be performed on a 3-day or 10-day basis. Also, the period (number of consecutive unit periods) for determining whether there is a possibility of dementia onset is not limited to four weeks. If quantitative evaluation is performed on a 3-day basis, for example, if evaluation results indicating a possibility of cognitive decline are obtained for 15 consecutive days (5 unit periods), the subject 50 will be determined to have a possibility of developing dementia.

[0095] Furthermore, in the embodiments described above, the case in which the server device 30 quantitatively evaluates the cognitive function of a subject using a learning model was used as an example. However, the method for quantitatively evaluating the cognitive function of a subject is not limited to the method using a learning model, and various evaluation methods can be used.

[0096] In the embodiments described above, the functions of each device may be implemented by other devices. For example, each function of the server device 30 may be implemented by the detection device 10, or by other server devices. For example, the detection device 10 may calculate the values ​​of each indicator from various data of the subject.

[0097] The means and methods for performing various processing in the dementia diagnosis device according to the above embodiment can be implemented by either a dedicated hardware circuit or a programmed computer. The program may be provided, for example, on a computer-readable recording medium such as a USB (Universal Serial Bus) memory or a DVD (Digital Versatile Disc)-ROM, or it may be provided online via a network such as the Internet. In this case, the program recorded on the computer-readable recording medium is usually transferred to and stored in a storage unit such as an HDD. Furthermore, the program may be provided as a standalone application software, or it may be incorporated into the software of the dementia diagnosis device as a function of the device.

[0098] While embodiments of the present invention have been described and illustrated in detail, the disclosed embodiments are for illustrative purposes only and are not limiting. The scope of the present invention should be interpreted in accordance with the language of the appended claims. [Explanation of Symbols]

[0099] 1. Dementia diagnosis system, 10 detection devices, 11,21,31 Control Unit, 12, 23, 33 Communications Department, 13 cameras, 14 Doppler sensors, 15 microphones, 20 Mobile terminal devices, 22,32 memory section, 24 Operation display section, 30 server devices, 40 networks, 50 target individuals.

Claims

1. An acquisition unit that acquires information about the subject's condition, An evaluation unit quantitatively evaluates the cognitive function of the subject over a unit period based on the information regarding the state acquired by the acquisition unit, A storage unit that stores the evaluation results from the evaluation unit for multiple consecutive unit periods, A determination unit that determines the likelihood of the subject developing dementia based on the evaluation results for a plurality of consecutive unit periods stored in the memory unit, A dementia diagnosis device having the following features.

2. The dementia determination device according to claim 1, wherein the determination unit determines that there is a possibility of dementia developing in the subject if the unit period for which the evaluation result indicating the possibility of cognitive decline was obtained is a predetermined number of consecutive periods, and determines that there is no possibility of dementia developing in the subject if the unit period for which the evaluation result indicating the possibility of cognitive decline was obtained is not a predetermined number of consecutive periods.

3. The dementia determination device according to claim 1 or 2, wherein the information relating to the state includes one or more indicators from among indicators relating to behavior, indicators relating to sleep, and indicators relating to emotion.

4. The dementia detection device according to claim 3, wherein the behavioral indicator, the sleep indicator, and the emotional indicator are calculated from the subject's imaging data, body movement data, and voice data, respectively.

5. The dementia determination device according to claim 1 or 2, wherein the evaluation unit quantitatively evaluates the cognitive function of a subject for a plurality of subjects using a learning model that has learned the relationship between information about the subject's condition and a quantitative value of the subject's cognitive function.

6. The dementia detection device according to claim 1 or 2, further comprising a notification unit that notifies the subject if the determination unit determines that the subject may be at risk of developing dementia.

7. The aforementioned cognitive functions are classified into memory function, executive function, attention function, and language function. The dementia determination device according to claim 6, wherein the notification unit notifies of the possibility of developing dementia in association with at least one cognitive function selected from the memory function, the executive function, the attention function, and the language function.

8. The dementia diagnosis device according to claim 6, wherein the notification unit causes the terminal device's display unit to display text describing facts about the subject's condition, text warning of the possibility of cognitive decline, and text encouraging a medical examination or testing.

9. Step (a) to obtain information about the subject's condition, Step (b) is to quantitatively evaluate the cognitive function of the subject over a unit period based on the information regarding the state obtained in step (a), Step (c) involves storing the evaluation results from step (b) in a storage unit for a plurality of consecutive unit periods, (d) A step of determining the possibility of the subject developing dementia based on the evaluation results for a plurality of consecutive unit periods stored in the memory unit, A method for determining dementia that includes [specific characteristics / features].

10. Procedure (a) for obtaining information about the subject's condition, A procedure (b) to quantitatively evaluate the cognitive function of the subject over a unit period based on the information regarding the state obtained in the procedure (a) above, The procedure (c) involves storing the evaluation results from the above procedure (b) in the storage unit for multiple consecutive unit periods, A procedure (d) for determining the likelihood of the subject developing dementia based on the evaluation results for a plurality of consecutive unit periods stored in the memory unit, A dementia diagnosis program that is executed by a computer.

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