Cognitive function estimation device, cognitive function estimation method, cognitive function estimation terminal, cognitive function estimation system device, program, and recording medium

Abstract

To provide a recognition function estimation device capable of simply estimating a recognition function with a low burden on an inspection object person.SOLUTION: A recognition function estimation device comprises a foot pressure information acquisition unit, an estimation parameter calculation unit, a determination unit, and an output unit. The foot pressure information acquisition unit acquires a subject's foot pressure information. The estimation parameter calculation unit calculates a recognition function estimation parameter on the basis of the foot pressure information. The determination unit determines the presence / absence of the subject's recognition functional disorder on the basis of at least one of the foot pressure information and the foot pressure information. The output unit outputs a result of the determination.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a cognitive function estimation device, a cognitive function estimation method, a cognitive function estimation terminal, a cognitive function estimation system device, a program, and a recording medium. [Background technology]

[0002] The number of dementia patients is increasing year by year. On the other hand, it is known that if appropriate treatment is given at the mild cognitive impairment (MCI) stage, 44% of dementia patients will recover to normal (Non-Patent Document 1). For this reason, there is a need for a means of early detection of dementia patients, and dementia tests such as the Hasegawa Dementia Scale-Revised (HDS-R) are known as screening tests for dementia patients (Non-Patent Document 2). [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Brodaty, H., Heffernan, M., Kochan, NA, Draper, B., Trollor, JN, Reppermund, S., ... & Sachdev, PS, “Mild cognitive impairment in a community sample: the Sydney Memory and Aging Study”, Alzheimer's & dementia, Vol. 9, No. 3 (2013), pp. 310-317 [Non-patent document 2] Shinji Kato, "Development of the Revised Hasegawa Dementia Scale (HDS-R)," Journal of Geriatric Psychiatry, Vol. 2, (1991), pp. 1339-1347. Summary of the Invention [Problem to be solved by the invention]

[0004] The dementia test requires test subjects, most of whom are elderly, to undergo the test voluntarily at a hospital, which creates the problem of poor continuity of the test. For this reason, there is a need for a method for estimating cognitive function that places less burden on test subjects and can be performed on a daily basis.

[0005] Therefore, an object of the present invention is to provide a cognitive function estimation device that can easily estimate cognitive function with less burden on the test subject. [Means for solving the problem]

[0006] In order to achieve the above object, the cognitive function estimation device of the present invention (hereinafter also referred to as "estimation device") includes: The device includes a foot pressure information acquisition unit, an estimation parameter calculation unit, a determination unit, and an output unit, the foot pressure information acquisition unit acquires foot pressure information of the subject; the estimation parameter calculation unit calculates a cognitive function estimation parameter based on the foot pressure information; the determination unit determines whether or not the subject has a cognitive dysfunction based on at least one of the foot pressure information and the cognitive function estimation parameter; The output unit is a device that outputs the determination result.

[0007] The cognitive function estimation method of the present invention (hereinafter also referred to as the "estimation method") includes: The method includes a foot pressure information acquisition step, an estimation parameter calculation step, a determination step, and an output step, the foot pressure information acquiring step acquires foot pressure information of the subject; the estimation parameter calculation step calculates a cognitive function estimation parameter based on the foot pressure information; the determining step determines whether or not the subject has cognitive dysfunction based on at least one of the foot pressure information and the cognitive function estimation parameter; The output step is a method for outputting the determination result.

[0008] The program of the present invention is a program for estimating cognitive function of a subject, causing a computer to execute a foot pressure information acquisition procedure, an estimation parameter calculation procedure, a determination procedure, and an output procedure; the step of acquiring foot pressure information includes acquiring foot pressure information of the subject; the estimation parameter calculation step calculates a cognitive function estimation parameter based on the foot pressure information; the determination step determines whether or not the subject has cognitive dysfunction based on at least one of the foot pressure information and the cognitive function estimation parameter; The output step outputs the determination result.

[0009] A computer-readable recording medium of the present invention records the program of the present invention.

[0010] The cognitive function estimation terminal (hereinafter also referred to as "estimation terminal") of the present invention includes a foot pressure measurement unit and a communication unit, the foot pressure measuring unit is capable of measuring the foot pressure of the subject as the foot pressure information; The communication unit is capable of communicating with the cognitive function estimation device of the present invention and is capable of transmitting the foot pressure information to the cognitive function estimation device.

[0011] The cognitive function estimation system device of the present invention (hereinafter also referred to as the "estimation system" or "estimation system device") comprises the cognitive function estimation terminal of the present invention and the cognitive function estimation device of the present invention, and the cognitive function estimation terminal and the cognitive function estimation device are capable of communicating with each other. [Effects of the Invention]

[0012] According to the present invention, it is possible to provide a cognitive function estimation device that can easily estimate the cognitive function of a test subject. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of a cognitive function estimation system apparatus including a cognitive function estimation apparatus and a cognitive function estimation terminal according to the first embodiment. [Figure 2]FIG. 2 is a block diagram illustrating an example of a hardware configuration of the cognitive function estimation apparatus according to the first embodiment. [Figure 3] FIG. 3 is a block diagram illustrating an example of a hardware configuration of the cognitive function estimation terminal according to the first embodiment. [Figure 4] FIG. 4 is a schematic diagram showing an example of foot pressure measurement points of a subject in the cognitive function estimation terminal of the first embodiment. [Figure 5] FIG. 5 is a flowchart illustrating an example of processing in the cognitive function estimation device of the first embodiment. [Figure 6] FIG. 6 is a block diagram illustrating an example of the configuration of a cognitive function estimation device according to the second embodiment. [Figure 7] FIG. 7 is a flowchart illustrating an example of processing in the cognitive function estimation device of the second embodiment. [Figure 8] FIG. 8 is a photograph illustrating the method for measuring the foot pressure of the subject in Examples 1 and 2. [Figure 9] FIG. 9 is a graph showing the relationship between the HDS-R scores of subjects estimated by the estimation method of the present invention and the measured HDS-R scores of each subject in Example 1. [Figure 10] FIG. 10 is a graph showing the results of error analysis of the estimation results obtained by the estimation method of the present invention in Example 1. [Figure 11] FIG. 11 is a graph showing the relationship between the HDS-R scores of subjects estimated by the estimation method of the present invention and the measured HDS-R scores of each subject in Example 2. [Figure 12] FIG. 12 is a graph showing the results of error analysis of the estimation results obtained by the estimation method of the present invention in Example 2. DETAILED DESCRIPTION OF THE INVENTION

[0014] In the cognitive function estimation device of the present invention, for example, the estimation parameter calculation unit calculates, as the cognitive function estimation parameter, at least one of ground contact time difference information and ground contact ratio information based on the foot pressure information; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The determination unit may be configured to determine whether or not the subject has cognitive dysfunction based on at least two selected from the group consisting of the foot pressure information, the ground contact time difference information, and the ground contact ratio information.

[0015] In the cognitive function estimation device of the present invention, for example, the determination unit may determine whether or not the subject has cognitive dysfunction based on the following formula (1).

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[0016] The cognitive function estimation device of the present invention further includes, for example, a cognitive function estimation unit, the estimation parameter calculation unit calculates, as the cognitive function estimation parameter, at least one piece of information selected from the group consisting of ground contact time difference information, ground contact ratio information, and foot pressure center trajectory information, based on the foot pressure information; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The information on the trajectory length of the foot pressure center is information on the length connecting points indicating the foot pressure center from the time when the foot of the subject contacts the ground until the foot is completely released from the ground, the cognitive function estimation unit estimates a cognitive function level of the subject determined to have a cognitive impairment based on at least two selected from the group consisting of the foot pressure information, the ground contact time difference information, the ground contact ratio information, and the foot pressure center trajectory information; The output unit may output at least one of the determination result and the cognitive function level.

[0017] In the cognitive function estimation device of the present invention, for example, the cognitive function estimation unit may estimate the cognitive function level of the subject based on the following formula (2).

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[0018] In the cognitive function estimation device of the present invention, for example, the cognitive function estimation unit may estimate the cognitive function level of the subject based on the following formula (3).

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[0019] In the cognitive function estimation method of the present invention, for example, the estimation parameter calculation step calculates, as the cognitive function estimation parameter, at least one of ground contact time difference information and ground contact ratio information based on the foot pressure information; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The determination step may be performed in a manner that determines whether or not the subject has cognitive dysfunction based on at least two selected from the group consisting of the foot pressure information, the ground contact time difference information, and the ground contact ratio information.

[0020] In the cognitive function estimation method of the present invention, for example, the determination step may be performed by determining whether or not the subject has cognitive dysfunction based on the following formula (1):

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[0021] The cognitive function estimation method of the present invention further includes, for example, a cognitive function estimation step: the estimation parameter calculation step calculates, as the cognitive function estimation parameter, at least one piece of information selected from the group consisting of contact time difference information, contact rate information, and foot pressure center trajectory information, based on the foot pressure information; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The information on the trajectory length of the foot pressure center is information on the length connecting points indicating the foot pressure center from the time when the foot of the subject contacts the ground until the foot is completely released from the ground, the cognitive function estimating step estimates a cognitive function level of the subject determined to have a cognitive impairment based on at least two selected from the group consisting of the foot pressure information, the contact time difference information, the contact rate information, and the foot pressure center trajectory information; The output step may be configured to output at least one of the determination result and the cognitive function level.

[0022] In the cognitive function estimation method of the present invention, for example, the cognitive function estimation step may be performed by estimating the cognitive function level of the subject based on the following formula (2).

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[0023] In the cognitive function estimation method of the present invention, for example, the cognitive function estimation step may be performed by estimating the cognitive function level of the subject based on the following formula (3).

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[0024] In the program of the present invention, for example, the estimation parameter calculation step calculates, as the cognitive function estimation parameter, at least one of contact time difference information and contact ratio information based on the foot pressure information; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The determination procedure may be in the form of determining whether or not the subject has cognitive dysfunction based on at least two selected from the group consisting of the foot pressure information, the ground contact time difference information, and the ground contact ratio information.

[0025] In the program of the present invention, for example, the determination step may be an embodiment in which the presence or absence of cognitive impairment in the subject is determined based on the following formula (1):

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[0026] The program of the present invention further causes the computer to execute a cognitive function estimation procedure, for example: the estimation parameter calculation step calculates, as the cognitive function estimation parameter, at least one piece of information selected from the group consisting of ground contact time difference information, ground contact ratio information, and foot pressure center trajectory information, based on the foot pressure information; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The information on the trajectory length of the foot pressure center is information on the length connecting points indicating the foot pressure center from the time when the foot of the subject contacts the ground until the foot is completely released from the ground, the cognitive function estimation step estimates a cognitive function level of a subject determined to have a cognitive impairment based on at least two information selected from the group consisting of the foot pressure information, the ground contact time difference information, the ground contact ratio information, and the foot pressure center trajectory information; The output step may be an embodiment in which at least one of the determination result and the cognitive function level is output.

[0027] In the program of the present invention, for example, the cognitive function estimation step may estimate the cognitive function level of the subject based on the following formula (2).

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[0028] In the program of the present invention, for example, the cognitive function estimation step may estimate the cognitive function level of the subject based on the following formula (3).

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[0029] Next, embodiments of the present invention will be described with reference to the drawings. The present invention is not limited to the following embodiments. In the following drawings, the same parts are denoted by the same reference numerals. Furthermore, the descriptions of the embodiments can be mutually incorporated unless otherwise specified, and the configurations of the embodiments can be combined unless otherwise specified.

[0030] In the present invention, a "subject" refers to a person whose cognitive function is estimated using the cognitive function estimation device of the present invention, and is also referred to as a test subject. The "subject" may be, for example, a person with cognitive impairment, a person without cognitive impairment (a healthy person), or a person whose cognitive impairment is unknown.

[0031] In the present invention, "cognitive dysfunction" refers to a state in which cognitive function is acquiredly impaired, and may be, for example, mild cognitive impairment (MCI), dementia, or severe dementia. The cause of the cognitive dysfunction is not particularly limited, and specific examples include those derived from diseases such as schizophrenia, dementia with Lewy bodies, frontotemporal dementia, Alzheimer's dementia, and vascular dementia such as cerebral infarction, cerebral hemorrhage, and subarachnoid hemorrhage, or those derived from external factors such as alcoholic dementia.

[0032] [Embodiment 1] This embodiment is an example of a cognitive function estimation system including an example of a cognitive function estimation device and a cognitive function estimation terminal of the present invention. FIG. 1 is a block diagram showing the configuration of an example of an estimation system device 100 including an example of an estimation device 1 and an estimation terminal 2 of this embodiment. As shown in FIG. 1, the estimation system device 100 includes an estimation device 1 and an estimation terminal 2. Also, as shown in FIG. 1, the estimation device 1 includes a foot pressure information acquisition unit 11, an estimation parameter calculation unit 12, a determination unit 13, and an output unit 14. The estimation device 1 may also include, for example, a storage unit as an optional configuration. The estimation terminal 2 includes a foot pressure measurement unit 21 and a communication unit 22. As shown in FIG. 1, the estimation device 1 can be connected to the estimation terminal 2, for example, via a communication network 3. However, this is not limiting, and the connection between the estimation device 1 and the estimation terminal 2 may be, for example, a wired connection using a cable or a wireless connection via wireless communication. Although not shown, the estimation system device 100 may include, for example, multiple estimation terminals 2. Examples of the wireless connection include WiFi (Wireless Fidelity), Bluetooth (registered trademark), and LPWA (Low Power Wide Area). The wireless communication may be either a form in which each device communicates directly (Ad Hoc communication) or indirect communication via an access point. The estimation device 1 of this embodiment may be incorporated into a server as a system. The estimation device 1 of this embodiment may also be a personal computer (PC), tablet terminal, or the like, on which the program of the present invention is installed. Although not shown, the estimation device 1 may also be connected to an external terminal of a system administrator via a communication network 3, for example, and the system administrator may manage the estimation device 1 from the external terminal.

[0033] The communication network 3 is not particularly limited and may be a known network, for example, a wired or wireless network. Examples of the communication network 3 include the Internet, the World Wide Web (WWW), a telephone line, a Local Area Network (LAN), Wireless Fidelity (WiFi), and Low Power Wide Area (LPWA).

[0034] The estimation terminal 2 is not particularly limited as long as it can measure the foot pressure of the subject using, for example, a foot pressure measuring unit 21 and transmit the measured foot pressure information of the subject to the estimation device 1 using a communication unit 22. The estimation terminal 2 may be, for example, a portable type in which the foot pressure measuring unit 21 is provided under the insole of the shoe worn by the subject, or a fixed type in which the foot pressure measuring unit 21 is provided on the floor on which the subject walks. A known foot pressure meter can be used as the estimation terminal 2 in the estimation system device 100; for example, see the description in Japanese Patent Application Laid-Open No. 2014-45885. Alternatively, the estimation terminal 2 may be a commercially available foot pressure monitor (foot pressure meter). Specific examples of commercially available foot pressure meters include insole-type foot pressure meters such as the PiT (registered trademark) foot pressure monitoring insole manufactured by Leaf Corporation, the Waltwin plantar pressure sensor for rehabilitation manufactured by Paramount Bed Co., Ltd., the F-Scan II foot pressure distribution measurement system manufactured by Nitta Corporation, and the Pedar insole-type foot pressure distribution measurement system manufactured by Novel GmbH (Germany); and sheet-type foot pressure meters such as the WalkWay NM-1000 sheet-type lower limb weight meter manufactured by Anima Corporation and the footscan plantar pressure distribution measurement system manufactured by Rsscan GmbH (Belgium).

[0035] 2 shows an example block diagram of the hardware configuration of the estimation device 1. The estimation device 1 includes, for example, a CPU (central processing unit) 101, a memory 102, a bus 103, a storage device 104, an input device 106, a display 107, and a communication device 108. Each component of the estimation device 1 is connected via the bus 103 by its respective interface (I / F).

[0036] The CPU 101 cooperates with other components via, for example, a controller (system controller, I / O controller, etc.) and is responsible for overall control of the estimation device 1. In the estimation device 1, the CPU 101 executes, for example, the program 105 of the present invention and other programs, and also reads and writes various types of information. Specifically, for example, the CPU 101 functions as a foot pressure information acquisition unit 11, an estimation parameter calculation unit 12, a determination unit 13, and an output unit 14. The estimation device 1 includes a CPU as a computing device, but may also include other computing devices such as a GPU (Graphics Processing Unit) or an APU (Accelerated Processing Unit), or may include a combination of the CPU and these. In the estimation device 1, the CPU 101 functions as each unit other than the storage unit in embodiment 2, which will be described later.

[0037] The memory 102 includes, for example, a main memory. The main memory is also referred to as a primary storage device. When the CPU 101 performs processing, the memory 102 reads various operating programs, such as the program 105 of the present invention, stored in, for example, a storage device 104 (auxiliary storage device) described below. The CPU 101 then reads and decodes data from the memory 102 and executes the program. The main memory is, for example, a RAM (random access memory). The memory 102 further includes, for example, a ROM (read only memory).

[0038] The bus 103 can also be connected to, for example, external devices. Examples of the external devices include an external storage device (external database, etc.), a printer, etc. The estimation device 1 can be connected to a communication network 3 by, for example, a communication device 108 connected to the bus 103, and can also be connected to the external devices via the communication network 3. The estimation device 1 can also be connected to an estimation terminal 2 via the communication device 108 and the communication network 3.

[0039] The storage device 104 is also referred to as an auxiliary storage device, for example, in contrast to the main memory (primary storage device). As described above, the storage device 104 stores an operating program including the program 105 of the present invention. The storage device 104 includes, for example, a storage medium and a drive for reading and writing data from and to the storage medium. The storage medium is not particularly limited and may be internal or external, and examples include a hard disk (HD), a floppy disk (FD), a CD-ROM, a CD-R, a CD-RW, an MO, a DVD, a flash memory, and a memory card, and the drive is not particularly limited. The storage device 104 may be, for example, a hard disk drive (HDD) in which the storage medium and the drive are integrated. If the estimation device 1 includes, for example, a storage unit, the storage device 104 functions as the storage unit.

[0040] The estimation device 1 further includes, for example, an input device 106 and a display 107. Examples of the input device 106 include pointing devices such as a touch panel, track pad, and mouse; a keyboard; imaging means such as a camera and scanner; card readers such as an IC card reader and a magnetic card reader; and audio input means such as a microphone. Examples of the display 107 include display devices such as an LED display and a liquid crystal display. In the first embodiment, the input device 106 and the display 107 are configured separately, but the input device 106 and the display 107 may also be configured as an integrated device, such as a touch panel display.

[0041] In the estimation device 1, the memory 102 and the storage device 104 can also store access information and log information from users, as well as information acquired from an external database (not shown).

[0042] Fig. 3 shows an example block diagram of the hardware configuration of the estimation terminal 2. As shown in Fig. 3, the estimation terminal 2 includes, for example, a CPU 201, a memory 202, a bus 203, a storage device 204, an input device 206, a communication device (communication unit) 22, a display 207, and a pressure measurement unit 21. Each unit of the estimation terminal 2 is connected via the bus 203 by its respective interface (I / F). The description of each unit of the estimation terminal 2 other than the pressure measurement unit 21 can be made using the description of each unit of the estimation device 1.

[0043] The pressure measurement unit 21 is a pressure sensor, and is preferably a foot pressure sensor capable of measuring foot pressure at multiple locations on the sole of the subject. Specific examples of the multiple locations will be described with reference to FIG. 4. FIG. 4 is a schematic diagram showing an example of foot pressure measurement locations on the sole of the subject. As shown in FIG. 4, the pressure measurement unit 21 of the estimation terminal 2 is preferably capable of measuring, for example, the thumb finger 211A, the ball of a thumb 211B, the middle forefoot 211C, and the hypothenar 211D of the subject's forefoot, and the heel 211E, the outside heel 211F, and the arch 211G of the subject's hindfoot. The pressure measurement unit 21 is preferably capable of measuring foot pressure on each of the subject's left and right feet, but is not limited thereto and may be capable of measuring foot pressure on either the left or right foot.

[0044] Next, the cognitive function estimation method of this embodiment will be described with reference to the flowchart of Fig. 5. The estimation method of this embodiment can be implemented, for example, using an estimation system device 100 including the estimation device 1 and estimation terminal 2 of this embodiment. Note that the estimation method of this embodiment is not limited to use with the estimation system device 100.

[0045] First, prior to processing by the estimation device 1, the pressure measurement unit 21 of the estimation terminal 2 measures foot pressure information of the subject. The foot pressure refers to the pressure when the sole of the subject's foot touches the ground. The pressure measurement unit 21 of the estimation terminal 2 measures, for example, foot pressures of the thumb 211A, the ball of a thumb 211B, the middle forefoot 211C, the hypothenar 211D, and the heel 211E, outside the heel 211F, and arch 211G of the subject's hindfoot while the subject is walking. The foot pressure information may be, for example, a value obtained by dividing the measurement value by the pressure measurement unit 21 by the subject's body weight. Dividing the measurement value by the subject's body weight is preferable because it can, for example, suppress the influence of the subject's body weight. Furthermore, because foot pressure changes over time as the subject walks, the peak pressure from the moment each measurement site touches the ground until it leaves the ground can be used as the foot pressure information for each site. The estimation terminal 2 may, for example, determine the total foot pressure on the subject's big toe, the ball of the foot, the center of the forefoot, and the ball of the little toe as the foot pressure of the subject's forefoot, and the total foot pressure on the subject's heel and lateral heel as the foot pressure of the subject's rearfoot. The foot pressure may be measured, for example, on the subject's first step, i.e., the first time, or may be measured over multiple steps (two or more). In the latter case, the foot pressure of each site may be determined as the average of multiple measurements, or the minimum or maximum value of multiple measurements, although the maximum value is preferably used. A specific method for measuring foot pressure using the pressure measurement unit 21 of the estimation terminal 2 can be, for example, the measurement method described in the Examples below. The estimation terminal 2 then transmits the measured foot pressure information to the estimation device 1 via the communication network 3 using the communication unit 22. However, the present invention is not limited to this, and for example, the estimation terminal 2 may transmit the measured foot pressure information to a database outside the system. In this case, the database stores, for example, the transmitted foot pressure information of the subject.

[0046] Next, processing by the estimation device 1 is initiated. First, the foot pressure information acquisition unit 11 of the estimation device 1 acquires the foot pressure information of the subject (S1, foot pressure information acquisition step). Specifically, the foot pressure information acquisition unit 11 acquires the foot pressure information from the estimation terminal 2 via the communication network 3 using the communication device 108. Furthermore, if the estimation device 1 is equipped with the storage unit, for example, the estimation device 1 may store the acquired foot pressure information in the storage unit. If the storage unit of the estimation terminal 1 stores the foot pressure information, the foot pressure information acquisition unit 11 may read the foot pressure information stored in the storage unit and acquire the subject's foot pressure information. Furthermore, for example, if the foot pressure information measured by the estimation terminal 2 is stored in a database external to the system, the foot pressure information acquisition unit 11 may acquire the subject's foot pressure information from, for example, the database.

[0047] Next, the estimation parameter calculation unit 12 of the estimation device 1 calculates cognitive function estimation parameters based on the foot pressure information (S2, estimation parameter calculation step). The cognitive function estimation parameters are various parameters for estimating the cognitive function of the subject, and the estimation parameter calculation unit 12 calculates, for example, at least one of ground contact time difference information and ground contact ratio information based on the foot pressure information.

[0048] The contact time difference information is information about the time from when the first part of the sole of the subject's foot touches the ground to when another part of the sole of the subject touches the ground, for example, information about the time from when the heel touches the ground to when another part of the sole of the subject touches the ground. Specifically, for example, the time when the subject's heel touches the ground is defined as "0 (reference time)," and examples of such information include the time elapsed until the big toe touches the ground, the time elapsed until the ball of the foot touches the ground, the time elapsed until the center of the forefoot touches the ground, the time elapsed until the ball of the little toe touches the ground, and the time elapsed until the lateral heel touches the ground. The contact time difference information for each part may be, for example, the value obtained by dividing the contact time difference for each part by the time from when the sole of the subject touches the ground to when it completely leaves the ground, i.e., the time required for one step by the subject. By dividing by the time required for one step by the subject, the influence of the subject's walking speed can be suppressed. The estimated parameter calculation unit 12 may calculate, as the ground contact time difference information, for example, the first step taken by the subject, i.e., the initial ground contact time difference, or may calculate the ground contact time differences for two or more steps. In the latter case, the estimated parameter calculation unit 12 may, for example, use the average value of the ground contact time differences for the multiple steps as the ground contact time difference information for each part, or the minimum or maximum value of the multiple ground contact time differences as the ground contact time difference information for each part, but it is preferable to use the minimum value. Shuffling gait is known to be one of the symptoms of cognitive impairment, and the more severe the shuffling gait, the shorter the time from the heel touching down to the ground contact of each part. Therefore, by using the minimum value as the ground contact time difference information, it is possible to more accurately determine, for example, whether or not the subject has cognitive impairment.

[0049] The contact-ground ratio information is, for example, information on the ratio of the time that each part of the sole of the subject is on the ground to the time that the subject's foot touches the ground and then leaves the ground. Specifically, for example, it is information on the ratio of the time that the sole of the subject touches the ground and then completely leaves the ground, that is, the time that it takes the subject to take one step, to the time that it takes the subject to take one step, such as the time that the big toe touches the ground and then completely leaves the ground, the time that the ball of the foot touches the ground and then completely leaves the ground, the time that the middle of the forefoot touches the ground and then completely leaves the ground, the time that the ball of the little toe touches the ground and then completely leaves the ground, the time that the lateral heel touches the ground and then completely leaves the ground, or the time that the heel touches the ground and then completely leaves the ground. The estimated parameter calculation unit 12 may calculate, as the contact-ground ratio information, for example, the first step that the subject takes, i.e., the contact-ground ratio of the first step, or may calculate the contact-ground ratios for two or more steps. In the latter case, the estimated parameter calculation unit 12 may, for example, use the average value of the ground contact ratios over multiple times as the ground contact ratio information for each part, or the minimum or maximum value of the ground contact ratios over multiple times as the ground contact ratio information for each part, but it is preferable to use the average value.

[0050] Next, the determination unit 13 of the estimation device 1 determines whether or not the subject has a cognitive dysfunction based on at least one of the foot pressure information and the cognitive function estimation parameters (S3, determination step). The determination unit 13 can determine whether or not the subject has a cognitive dysfunction based on, for example, at least two selected from the group consisting of the foot pressure information, the ground contact time difference information, and the ground contact ratio information.

[0051] A specific example of the determination of the presence or absence of cognitive dysfunction of a subject by the determination unit 13 will be given below. The determination unit 13 determines the presence or absence of cognitive dysfunction of the subject, for example, based on the following formula (1). In the following formula (1), γ represents the foot pressure information, σ represents the ground contact time difference information, φ represents the ground contact ratio information, and p represents probability. In the following formula (1), for example, m is 1 or 2, with 1 representing the forefoot of the subject and 2 representing the rearfoot of the subject. Also, in the following formula (1), n ​​is 1, 2, 3, 4, 5, or 6, with 1 representing the thumb of the subject, 2 representing the ball of the subject's thenar foot, 3 representing the center of the forefoot of the subject, 4 representing the ball of the subject's hypothenar foot, 5 representing the lateral heel of the subject, and 6 representing the heel of the subject. In the following formula (1), α (α1 to α3) and β are coefficients, and can be calculated, for example, based on the examples described below, by performing a binomial logistic regression analysis using the subject's Revised Hasegawa Dementia Scale (HDS-R score) as the dependent variable and the foot pressure information, the contact time difference information, and the contact rate information as independent variables.

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[0052] A further specific example will be given to explain the determination of whether or not a subject has cognitive impairment by the determination unit 13. The determination unit 13 can determine whether or not a subject has cognitive impairment, i.e., whether the subject's HDS-R score is 30 (healthy subject) or 29 or less (cognitive impairment), based on, for example, the following formula (1A): In the following formula (1A), μ1 represents the probability that the subject is healthy, i.e., does not have cognitive impairment; γ2 represents foot pressure information on the subject's hind feet, i.e., the sum of foot pressure values ​​on the heel and lateral heel of the subject; and φ2 represents the ground contact rate of the subject's ball of the foot.

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[0053] A further specific example will be given to explain the determination of the presence or absence of cognitive impairment in a subject by the determination unit 13. The determination unit 13 may determine, for example, based on the following formula (1B), whether the subject is healthy or has mild cognitive impairment (MCI), i.e., whether the subject's HDS-R score is 30 to 21, or whether the subject has dementia, i.e., whether the subject's HDS-R score is 20 or less. In the following formula (1B), μ2 represents the probability that the subject is healthy or has mild cognitive impairment, σ4 represents ground contact time difference information between the heel and the ball of the hypothenium of the subject, and φ5 represents the ground contact rate of the outer heel of the subject.

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[0054] Then, the output unit 14 of the estimation device 1 outputs the determination result (S4, output step). The output unit 14 may, for example, output the determination result to a display 107, or may output the determination result to an external device via a communication device 108. Examples of the external device include a printing machine such as a printer, a mobile terminal such as a tablet terminal, and the estimation terminal 2. Then, the processing by the estimation device 1 ends (END).

[0055] When the output unit 14 outputs the determination result to the inferred terminal 2, the display 207 of the inferred terminal 2 may be capable of displaying the determination result.

[0056] In this embodiment, the estimation device 1 performs the functions of the foot pressure information acquisition unit 11, estimation parameter calculation unit 12, determination unit 13, and output unit 14, and the estimation terminal 2 performs the function of the foot pressure measurement unit 21, but the present invention is not limited to this. For example, the estimation device 1 and the estimation terminal 2 may each perform the functions of at least one or more components of each other's configuration. Specifically, for example, the estimation device 1 may be equipped with a foot pressure sensor. In this case, the foot pressure information acquisition unit 11 of the estimation device 1 can acquire the foot pressure information of the subject from the foot pressure sensor.

[0057] The cognitive function estimation device of this embodiment can determine whether or not a subject has cognitive impairment based on the subject's foot pressure information. In this way, the cognitive function estimation device of the present invention can estimate the subject's cognitive function based on, for example, the subject's walking behavior, which is a daily movement of the subject, thereby reducing the burden on the subject and making it possible to easily estimate the subject's cognitive function.

[0058] [Embodiment 2] This embodiment is similar to the estimation device 1 of embodiment 1 except that a cognitive function estimation unit is further provided in addition to the configuration of the estimation device 1 of embodiment 1, and the description therefor can be cited. The estimation device of this embodiment further includes a cognitive function estimation unit, and the estimation parameter calculation unit calculates, based on the foot pressure information, at least one piece of information selected from the group consisting of contact time difference information, contact percentage information, and foot pressure center trajectory information as the cognitive function estimation parameter, wherein the contact time difference information includes information about the time from when a part of the sole of the subject's foot that first touches the ground to when another part of the sole touches the ground, the contact percentage information is information about the proportion of the time that each part of the subject's foot is in contact with the ground relative to the time from when the foot touches the ground to when it leaves the ground, and the foot pressure center trajectory length information is information about the length connecting the points indicating the foot pressure center during the time from when the subject's foot touches the ground to when it is completely released, and the cognitive function estimation unit estimates a cognitive function level of the subject determined to have impaired cognitive function based on at least two pieces of information selected from the group consisting of the foot pressure information, the contact time difference information, the contact percentage information, and the foot pressure center trajectory information, and the output unit outputs at least one of the determination result and the cognitive function level. Therefore, according to this embodiment, it is possible to estimate the cognitive function level of the subject, rather than whether or not the subject has a cognitive impairment. Therefore, the estimation device of this embodiment can estimate the cognitive function of the subject with higher accuracy.

[0059] Fig. 6 is a block diagram showing an example of the configuration of an estimation device 1A of this embodiment. As shown in Fig. 6, the estimation device 1A further includes a cognitive function estimation unit 15 in addition to the configuration of the estimation device 1 of embodiment 1. The hardware configuration of the estimation device 1A is the same as that of the estimation device 1 of Fig. 2, except that the CPU 101 includes the configuration of the estimation device 1A of Fig. 6 instead of the configuration of the estimation device 1 of Fig. 1.

[0060] An example of processing in an estimation system including the estimation device 1A and the estimation terminal 2 of this embodiment will be described with reference to the flowchart of Fig. 7. Fig. 7 is a flowchart showing an example of processing (S1 to S3, S11, S4) of the estimation device 1A.

[0061] First, S1 is performed in the same manner as S1 in the processing of the estimation device 1 of the first embodiment, and foot pressure information of the subject is acquired.

[0062] Next, the estimation parameter calculation unit 12 of the estimation device 1A calculates one piece of information selected from the group consisting of the contact time difference information, contact rate information, and foot pressure center trajectory information as the cognitive function estimation parameter (S2, estimation parameter calculation step). The contact time difference information and the contact rate information are, for example, as described above.

[0063] The foot pressure center trajectory length information is, for example, information on the length connecting points indicating the subject's foot pressure center during the period from when the subject's foot touches the ground until it completely leaves the ground, i.e., during one step of the subject. The foot pressure center (COP) refers to, for example, the central point of the distribution of forces acting on the contact surface between the subject's sole and the floor, and is also called the floor reaction force application point or pressure center. Specifically, for example, when the subject's sole contacts the floor, the center of gravity of a floor reaction force vector, which is a combination of multiple floor reaction forces generated on the sole, indicates the subject's foot pressure center at that time. Note that the multiple floor reaction forces may be, for example, floor reaction forces in one direction or floor reaction forces in two or more directions. In the former case, it is preferable that the floor reaction force is, for example, directed vertically to the floor surface.

[0064] Next, S3 is carried out in the same manner as S3 in the first embodiment.

[0065] Next, the cognitive function estimation unit 15 of the estimation device 1A estimates the cognitive function level of the subject (S3, YES) who has been determined to have a cognitive function disorder in S3 based on at least two selected from the group consisting of the foot pressure information, the ground contact time difference information, the ground contact ratio information, and the foot pressure center trajectory information (S11, cognitive function estimation process).

[0066] A specific example of estimation of the cognitive function level of the subject by the cognitive function estimation unit 15 will be given below. The cognitive function estimation unit 15 can estimate the cognitive function level of the subject, for example, based on the following formula (2). In the following formula (2), γ represents the foot pressure information, σ represents the ground contact time difference information, and φ represents the ground contact ratio information. In the following formula (2), for example, m is 1 or 2, with 1 representing the forefoot of the subject and 2 representing the rearfoot of the subject. Also, in the following formula (2), n is 1, 2, 3, 4, 5, or 6, with 1 representing the thumb of the subject, 2 representing the ball of the subject's thenar foot, 3 representing the center of the forefoot of the subject, 4 representing the ball of the subject's hypothenar foot, 5 representing the lateral heel of the subject, and 6 representing the heel of the subject. In addition, in the following formula (2), α (α1 to α3) and β are coefficients, and can be calculated, for example, based on the examples described below, by performing multiple regression analysis with the subject's Revised Hasegawa Dementia Scale (HDS-R score) as the dependent variable and the foot pressure information, the contact time difference information, and the contact rate information as independent variables.

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[0067] The estimation of the cognitive function level of the subject by the cognitive function estimation unit 15 will be further described with a specific example. The cognitive function estimation unit 15 can estimate the cognitive function level of the subject, for example, based on the following formula (2A). In the following formula (2A), σ1 represents the ground contact time difference information between the heel and the big toe of the subject, φ3 represents the ground contact ratio of the center of the forefoot of the subject, and φ4 represents the ground contact ratio of the ball of the little toe of the subject. The cognitive function estimation unit 15 can estimate the HDS-R score of the subject, i.e., the cognitive function level, based on the following formula (2A), for example.

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[0068] Further, other examples of estimation of the cognitive function level of the subject by the cognitive function estimation unit 15 will be specifically illustrated. The cognitive function estimation unit 15 can estimate the cognitive function level of the subject, for example, based on the following formula (3). In the following formula (3), γ represents the foot pressure information, σ represents the ground contact time difference information, φ represents the ground contact ratio information, and ψ represents the foot pressure center trajectory length information. In the following formula (3), for example, m is 1 or 2, with 1 representing the forefoot of the subject and 2 representing the rearfoot of the subject. In the following formula (3), n is 1, 2, 3, 4, 5, or 6, with 1 representing the thumb of the subject, 2 representing the ball of the subject's thenar foot, 3 representing the center of the forefoot of the subject, 4 representing the ball of the subject's hypothenar foot, 5 representing the lateral heel of the subject, and 6 representing the heel of the subject. In the following formula (3), α (α1 to α4) and β are coefficients, and can be calculated, for example, based on the examples described below, by performing multiple regression analysis with the subject's Revised Hasegawa Dementia Scale (HDS-R score) as the dependent variable and the foot pressure information, the contact time difference information, the contact rate information, and the foot pressure center trajectory length information as independent variables.

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[0069] The estimation of the cognitive function level of the subject by the cognitive function estimation unit 15 will be further described with a specific example. The cognitive function estimation unit 15 can estimate the cognitive function level of the subject based on, for example, the following formula (3A). In the following formula (3A), γ1 represents foot pressure information of the forefoot of the subject, γ2 represents foot pressure information of the rearfoot of the subject, σ1 represents contact time difference information between the heel and the ball of the subject, σ2 represents contact time difference information between the heel and the ball of the subject, σ4 represents contact time difference information between the heel and the ball of the little toe of the subject, σ5 represents contact time difference information between the heel and the lateral heel of the subject, φ1 represents contact rate information of the ball of the subject, φ2 represents contact rate information of the ball of the subject, φ6 represents contact rate information of the heel of the subject, and ψ represents trajectory length information of the center of foot pressure. The cognitive function estimation unit 15 can estimate the HDS-R score, that is, the cognitive function level, of the subject based on, for example, the following formula (3A).

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[0070] Then, the output unit 14 of the estimation device 1A outputs at least one of the determination result and the cognitive function level (S4, output step). For example, the output unit 14 outputs the determination result and the cognitive function level for a subject determined to have a cognitive function disorder, and outputs the determination result for a subject determined not to have a cognitive function disorder (S3, No). Then, the processing by the estimation device 1A ends (END).

[0071] [Embodiment 3] The program of this embodiment is a program for causing a computer to execute each step of the cognitive function estimation method described above. Specifically, the program of this embodiment is a program for estimating the cognitive function of a subject, and causes the computer to execute a foot pressure information acquisition procedure, an estimation parameter calculation procedure, a judgment procedure, and an output procedure.

[0072] The foot pressure information acquisition procedure acquires foot pressure information of the subject, the estimation parameter calculation procedure calculates a cognitive function estimation parameter based on the foot pressure information, the determination procedure determines whether the subject has a cognitive function disorder based on at least one of the foot pressure information and the cognitive function estimation parameter, and the output procedure outputs the determination result.

[0073] The program of this embodiment can also be said to be a program that causes a computer to function as a foot pressure information acquisition procedure, an estimated parameter calculation procedure, a determination procedure, and an output procedure.

[0074] The program of this embodiment can be implemented by invoking the descriptions of the cognitive function estimation device and cognitive function estimation method of the present invention. For each of the steps, for example, "step" can be read as "processing." The program of this embodiment may also be recorded on a computer-readable recording medium. The recording medium is, for example, a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples thereof include random access memory (RAM), read-only memory (ROM), hard disk (HD), optical disk, and floppy disk (FD). [Example]

[0075] [Example 1] We confirmed that the cognitive function estimation parameters calculated from the subjects' foot pressure information correlated with the subjects' cognitive function level.

[0076] (1) Subjects The subjects were 61 elderly people (11 men and 50 women) with an average age of 82 years (range 67-92 years). The subjects were informed of the purpose and objectives of the study and how the results would be handled, and the study was conducted after obtaining informed consent. The study in this example was approved by the Ichinoseki National College of Technology Ethics Committee.

[0077] (2) Measurement of foot pressure and calculation of cognitive function estimation parameters The estimation terminal 2 used was a foot pressure monitor insole PiT (registered trademark) 2 from Leaf Corporation. As shown in FIG. 8, the estimation terminal 2 was attached to the subject's foot, and ground contact pressure (foot pressure information) was measured at each part of the subject's foot (the big toe, the ball of the foot, the central forefoot, the arch, the lateral heel, and the heel). The walking speed during measurement was set to a free walking speed, and each subject was instructed to walk as usual. The walking distance was set to 10 m, and measurements were taken twice for each subject. Then, from the obtained foot pressure information, the ground contact time difference information and the ground contact percentage information were calculated as the various cognitive function estimation parameters.

[0078] (3) Measurement of cognitive function level Next, the cognitive function level of each subject was measured using the Revised Hasegawa Dementia Scale (HDS-R). The HDS-R is a cognitive function test consisting of nine items: age, time orientation, place orientation, word recall and delayed recall, calculation, digit recitation, object memorization, and verbal fluency. The lower the HDS-R score, the higher the likelihood of cognitive impairment, and a score of 20 or less is considered to be suspicious of dementia. Therefore, in this example, subjects with an HDS-R score of 0 to 10 were classified as severely demented, those with an HDS-R score of 11 to 20 as dementia, those with an HDS-R score of 21 to 29 as mild cognitive impairment (MCI), and those with an HDS-R score of 30 as normal.

[0079] (4)Analysis Each subject was classified according to their cognitive function level as shown in Table 1 below (Group I: all subjects, Group II: severe dementia, dementia, and MCI, Group III: severe dementia and dementia, Group IV: dementia and MCI, Group V: MCI and healthy subjects, Group VI: MCI only), and a multiple regression analysis was performed using the HDS-R score measured in (3) above as the dependent variable and the foot pressure information and cognitive function estimation parameters measured and calculated in (2) above as independent variables. In Table 1 below, the N column indicates the number of people in each group or dementia level. The coefficient of determination (R 2 ) and the coefficient of determination adjusted for the degrees of freedom (Adjusted R 2 ) are shown in Table 2 below.

[0080] [Table 1]

[0081] [Table 2]

[0082] As a result, in Group VI (MCI patient group), the coefficient of determination adjusted for the degrees of freedom was R 2 =0.754, and it was found that the HDS-R score of the MCI patient group can be estimated using the following formula (2A).

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[0083] The coefficients and standardized coefficients of the above formula (2A) are shown in Table 3 below, and Figure 9 shows the relationship between the HDS-R score estimated by formula (2A) and the HDS-R score of each subject measured by the above formula (3).

[0084] [Table 3]

[0085] Figure 9 shows the HDS-R score (HDS-R est ) and the HDS-R score of each subject measured in (3) above (HDS-R mes 9 is a graph showing the relationship between the HDS-R score estimated by Equation (2A) and the HDS-R score measured by Equation (2B), where the vertical axis shows the HDS-R score estimated by Equation (2A) and the horizontal axis shows the measured HDS-R score. est and HDS-R mes Between 2 =0.81 (P<0.01), which was a strong correlation. In other words, it was found that the cognitive function level of the subjects can be estimated using equation (2A).

[0086] (5) Verification of generalization performance Next, leave-one-out (LOO) cross-validation was performed to confirm the generalization performance of Equation (2A). In the LOO cross-validation, test data for one subject was extracted from the data of all subjects, and the remaining data was used as training data. Then, using the pre-extracted test data, Equation (2A) was verified from the training data, and verification was performed for the number of subjects while exchanging the training data and test data. As a result, the root mean square of the error of Equation (2A) was 1.43, which is related to the resolution of the HDS-R score, confirming that Equation (2A) has generalization performance.

[0087] (6)Error analysis Next, an error analysis of Equation (2A) was performed using Bland and Altman analysis. The results are shown in Figure 10. Figure 10 is a graph showing the results of the error analysis, with the vertical axis representing the HDS-R score (HDS-R est ) and the HDS-R score of each subject measured in (3) above (HDS-R mes ) and the horizontal axis shows the difference between the HDS-R score (HDS-R est ) and the HDS-R score of each subject measured in (3) above (HDS-R mes ) and the average value of HDS-R. est and HDS-R mesThe average difference between the HDS-R and the HDS-R was close to 0 and was within the mean ± 2SD, so no additive error was observed. est and HDS-R mes The average value of and HDS-R est and HDS-R mes The correlation coefficient for the difference was small at 0.24, with a significance probability of P = 0.39. Therefore, there was no significance and no proportional error was observed.

[0088] As shown in Table 3 above, the standardized coefficients in equation (2A) are the coefficients of the multiple regression model calculated from the standardized values ​​of the independent variables and dependent variables. This is an index showing the degree of influence of each variable in the estimation equation. As shown in Table 3 above, the standardized coefficients for σ1 (heel-to-thumb contact time difference) and φ3 (forefoot center contact percentage) showed negative values, while the standardized coefficient for φ4 (hypothenar contact percentage) showed positive values. This suggests that as the subject's heel-to-thumb contact time difference and forefoot center contact percentage increase and the hypothenar contact percentage decrease, the subject's cognitive function level decreases.

[0089] (7) Assessment of cognitive impairment Next, we investigated whether subjects had cognitive impairment, i.e., whether they were healthy or mildly cognitively impaired. For Group V (MCI and healthy subjects) in Table 1, we performed a binomial logistic regression analysis using the HDS-R score measured in (3) above as the dependent variable and the foot pressure information and cognitive function estimation parameters measured and calculated in (2) above as independent variables. As a result, we found that the probability that a subject was healthy could be estimated using the following equation (1A). The coefficients and odds ratios of equation (1A) are shown in Table 4 below. Furthermore, a Hosmer-Lemeshow test was performed to verify the suitability of equation (1A). The results are shown in Table 5 below.

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[0090] [Table 4]

[0091] [Table 5]

[0092] As shown in Table 5, the significance probability in the test of formula (1A) was P=0.185. In the test, when P<0.05, the regression equation is considered not to be a good fit, so formula (1A) can be determined to be a good fit.

[0093] Next, to examine the accuracy of formula (1A), a contingency table was created as shown in Table 6 below. As shown in Table 6, the accuracy of formula (1A) was 79.4%, indicating that formula (1A) has very high estimation accuracy.

[0094] [Table 6]

[0095] Furthermore, as shown in Table 4 above, the significance probability of the variable γ2 (hindfoot pressure) in equation (1A) was P = 0.008, and the significance probability of φ2 (ground contact rate of the ball of the foot) was P = 0.061. Since multicollinearity is suspected when the significance probability of all variables is P ≧ 0.05, it was shown that equation (1A) does not contain multicollinearity. The odds ratio indicates the degree of influence on the dependent variable, and 1 indicates no influence at all. As shown in Table 4 above, since OR ≠ 1 for all variables, it can be said that the variables in equation (1A) are significant.

[0096] (8) Determining the cutoff value Next, we investigated whether subjects had mild cognitive impairment (MCI) or dementia, i.e., whether their HDS-R scores were 20 or less or 21 or more. For Group IV (MCI and dementia patients) in Table 1, a binomial logistic regression analysis was performed using the HDS-R scores measured in (3) above as the dependent variable and the foot pressure information and cognitive function estimation parameters measured and calculated in (2) above as independent variables. As a result, we found that the probability of a subject's HDS-R score being 21 or more can be estimated using the following equation (1B). The coefficients and odds ratios for equation (1B) are shown in Table 7. A Hosmer-Lemeshow test was also performed to verify the suitability of equation (1B). The results are shown in Table 8.

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[0097] [Table 7]

[0098] [Table 8]

[0099] As shown in Table 8, the significance probability in the test of formula (1B) was P=0.758. In the test, when P<0.05, the regression equation is considered not to fit, so formula (1B) can be determined to fit.

[0100] Next, to examine the accuracy of formula (1B), a contingency table was created as shown in Table 9 below. As shown in Table 9, the accuracy of formula (1B) was 76.4%, indicating that formula (1B) has very high estimation accuracy.

[0101] [Table 9]

[0102] Furthermore, as shown in Table 7 above, the significance probability of variable σ4 (ground contact time difference of the ball of the little toe) in equation (1B) was P = 0.0044, and the significance probability of φ5 (outer heel ground contact rate) was P = 0.018. Since multicollinearity is suspected when the significance probability of all variables is P ≥ 0.05, it was shown that equation (1B) does not contain multicollinearity. The odds ratio indicates the degree of influence on the dependent variable, and 1 indicates no influence at all. As shown in Table 7 above, since OR ≠ 1 for all variables, it can be said that the variables in equation (1B) are significant.

[0103] From these findings, it was found that the formula (1) can be used to determine whether or not a subject has cognitive impairment, and the formula (2) can be used to estimate the subject's cognitive function level.

[0104] [Example 2] We confirmed that by taking into account the trajectory length information of the center of foot pressure, it is possible to estimate the subject's cognitive function level more accurately.

[0105] For the subjects in Example 1, foot pressure center trajectory length information was calculated based on the foot pressure information measured in Example 1 (2). Then, for Group IV (group of MCI and dementia patients) in Table 1, a multiple regression analysis was performed using the HDS-R score measured in (3) above as the dependent variable and the foot pressure information, contact time difference information, contact rate information, and foot pressure center trajectory length information measured and calculated in Example 1 (2) above as independent variables. The coefficients of determination and coefficients of determination adjusted for the degrees of freedom are shown in Table 10 below.

[0106] [Table 10]

[0107] As a result, in Group IV, the coefficient of determination adjusted for the degrees of freedom was R 2 =0.931, and it was found that the HDS-R scores of the MCI patient group and the dementia patient group can be estimated using the following formula (3A).

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[0108] FIG. 11 shows the relationship between the HDS-R score estimated by equation (3A) and the HDS-R score of each subject measured by (3) above.

[0109] Figure 11 shows the HDS-R score (HDS-R est ) and the HDS-R score of each subject measured in (3) above (HDS-R mes ) where the vertical axis represents the HDS-R score estimated by Equation (3A) and the horizontal axis represents the measured value of the HDS-R score. est and HDS-R mes Between 2 =0.96 (P<0.05), which indicates a strong correlation. In other words, it was found that the cognitive function level of the subjects can be estimated using equation (3A).

[0110] Next, an error analysis of Equation (3A) was performed using Bland and Altman analysis. The results are shown in Figure 10. Figure 12 is a graph showing the results of the error analysis, with the vertical axis representing the HDS-R score (HDS-R est ) and the HDS-R score of each subject measured in (3) above (HDS-R mes ) and the horizontal axis shows the difference between the HDS-R score (HDS-R est ) and the HDS-R score of each subject measured in (3) above (HDS-R mes ) and the average value of HDS-R. est and HDS-R mes The average difference between the HDS-R and the HDS-R was close to 0, and most of the values ​​were within the mean ± 2SD, so no additive error was observed. est and HDS-R mes The average value of and HDS-R est and HDS-R mes The correlation coefficient for the difference was small at 0.10, with a significance probability of P = 0.68. Therefore, there was no significance and no proportional error was observed.

[0111] From these findings, it was found that the cognitive function level of the subject can be estimated by the above formula (3).

[0112] Although the present invention has been described above with reference to the embodiments and examples, the present invention is not limited to the above embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

[0113] <Additional Notes> Some or all of the above-described embodiments and examples can be described as, but are not limited to, the following supplementary notes. (Appendix 1) The device includes a foot pressure information acquisition unit, an estimation parameter calculation unit, a determination unit, and an output unit, the foot pressure information acquisition unit acquires foot pressure information of the subject; the estimation parameter calculation unit calculates a cognitive function estimation parameter based on the foot pressure information; the determination unit determines whether or not the subject has a cognitive dysfunction based on at least one of the foot pressure information and the cognitive function estimation parameter; The cognitive function estimation device, wherein the output unit outputs the determination result. (Appendix 2) the estimation parameter calculation unit calculates, as the cognitive function estimation parameter, at least one of ground contact time difference information and ground contact ratio information based on the foot pressure information; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The cognitive function estimation device described in Appendix 1, wherein the determination unit determines whether or not the subject has a cognitive function disorder based on at least two selected from the group consisting of the foot pressure information, the ground contact time difference information, and the ground contact ratio information. (Appendix 3) 3. The cognitive function estimation device according to claim 1, wherein the determination unit determines whether or not the subject has cognitive dysfunction based on the following formula (1):

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[0114] The present invention can estimate a subject's cognitive function based on the subject's foot pressure information. Therefore, the present invention can easily estimate cognitive function with less burden on the subject. Therefore, the present invention is extremely useful in fields such as nursing care and medicine. [Explanation of symbols]

[0115] 1. Cognitive function estimation device 11 Foot pressure information acquisition unit 12 Estimation parameter calculation section 13 Judgment section 14 Output section 15 Cognitive Function Estimation Unit 101 CPU 102 memory 103 Bus 104 Storage device 105 Programs 106 Input Device 107 Display 108 Communication Devices 2. Estimated device 21 Pressure sensor (pressure measurement part) 22 Communication unit (communication device) 201 CPU 202 memory 203 Bus 204 Storage device 205 Programs 206 Input Device 207 Display 3. Communication Network

Claims

1. The device comprises a foot pressure information acquisition unit, an estimation parameter calculation unit, a determination unit, a cognitive function estimation unit, and an output unit, the foot pressure information acquisition unit acquires foot pressure information of the subject; the estimation parameter calculation unit calculates, based on the foot pressure information, ground contact time difference information, ground contact ratio information, and foot pressure center trajectory length information as cognitive function estimation parameters; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The information on the trajectory length of the foot pressure center is information on the length connecting points indicating the foot pressure center from the time when the foot of the subject contacts the ground until the foot is completely released from the ground, the determination unit determines a possibility that the subject has a cognitive impairment based on the foot pressure information and the ground contact ratio information; The cognitive function estimation unit For a subject determined to have a possibility of having cognitive impairment, a cognitive function level of the subject is estimated based on at least two information selected from the group consisting of the foot pressure information, the ground contact time difference information, the ground contact ratio information, and the foot pressure center trajectory length information; The cognitive function estimation device, wherein the output unit outputs at least one of the determination result and the cognitive function level.

2. The determination unit determines a possibility that the subject has cognitive impairment based on at least one of the following formulas (1C) and (1D): In the following formula (1C): μ １ means the probability that the subject is a healthy individual, gamma ２ means the foot pressure information of the subject's rear foot, φ ２ means the percentage of the subject's ball of the foot touching the ground, α １ , α ２ , and β is a coefficient, 【Number 1C】 In the following formula (1D), μ ２ denotes the probability that a subject is healthy or has mild cognitive impairment, σ ４ means the time difference between the heel and the ball of the foot touching the ground, φ ５ means the percentage of the subject's outer heel touching the ground, α １ , α ２ , and β is a coefficient, [Math 1D] The cognitive function estimation device according to claim 1 .

3. The cognitive function estimation unit estimates the subject's Revised Hasegawa Dementia Scale (HDS-R score) as the subject's cognitive function level based on the following formula (2B): In the following formula (2B): σ １ means the contact time difference information between the heel and the thumb of the subject, φ ３ means the percentage of the subject's forefoot center on the ground, φ ４ means the contact rate of the subject's hypothenar ball, α １ , α ２ , α ３ and β is a coefficient, 【Number 2B】 The cognitive function estimation device according to claim 1 or 2.

4. The cognitive function estimation unit estimates the subject's Revised Hasegawa Dementia Scale (HDS-R score) as the subject's cognitive function level based on the following formula (3B): In the following formula (3B): gamma １ means the foot pressure information of the subject's forefoot, gamma ２ means the foot pressure information of the subject's rear foot, σ １ means the contact time difference information between the heel and the thumb of the subject, σ ２ means the contact time difference information between the heel and the ball of the foot of the subject, σ ４ means the contact time difference information between the heel and the ball of the foot of the subject, σ ５ means the contact time difference information between the heel and the lateral part of the heel of the subject, φ １ means the contact rate information of the subject's thumb, φ ２ means the ground contact rate information of the subject's ball of the foot, φ ６ means the heel contact rate information of the subject, ψ represents the trajectory length information of the subject's foot pressure center, α １ , α ２ , α ３ , α ４ , α ５ , α ６ , α ７ , α ８ , α ９ , α １０ and β is a coefficient, 【Number 3B】 The cognitive function estimation device according to claim 1 or 2.

5. The system comprises a foot pressure information acquisition step, an estimation parameter calculation step, a determination step, a cognitive function estimation step, and an output step, the foot pressure information acquiring step acquires foot pressure information of the subject; the estimation parameter calculation step calculates, based on the foot pressure information, ground contact time difference information, ground contact ratio information, and foot pressure center trajectory length information as cognitive function estimation parameters; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The information on the trajectory length of the foot pressure center is information on the length connecting points indicating the foot pressure center from the time when the foot of the subject contacts the ground until the foot is completely released from the ground, the determining step determines a possibility that the subject has cognitive impairment based on the foot pressure information and the ground contact ratio information; The cognitive function estimation step includes: For a subject determined to have a possibility of having cognitive impairment, a cognitive function level of the subject is estimated based on at least two information selected from the group consisting of the foot pressure information, the ground contact time difference information, the ground contact ratio information, and the foot pressure center trajectory length information; The output step is characterized in that at least one of the determination result and the cognitive function level is output. A cognitive function estimation method in which each step is performed by a computer.

6. The determination step includes determining a possibility that the subject has cognitive impairment based on at least one of the following formulas (1C) and (1D): In the following formula (1C): μ １ means the probability that the subject is a healthy individual, gamma ２ means the foot pressure information of the subject's rear foot, φ ２ means the percentage of the subject's ball of the foot touching the ground, α １ , α ２ , and β is a coefficient, 【Number 1C】 In the following formula (1D), μ ２ denotes the probability that a subject is healthy or has mild cognitive impairment, σ ４ means the time difference between the heel and the ball of the foot touching the ground, φ ５ means the percentage of the subject's outer heel touching the ground, α １ , α ２ , and β is a coefficient, [Math 1D] The cognitive function estimation method according to claim 5.

7. The cognitive function estimation step estimates the subject's Revised Hasegawa Dementia Scale (HDS-R score) as the subject's cognitive function level based on the following formula (2B): In the following formula (2B): σ １ means the contact time difference information between the heel and the thumb of the subject, φ ３ means the percentage of the subject's forefoot center on the ground, φ ４ means the contact rate of the subject's hypothenar ball, α １ , α ２ , α ３ and β is a coefficient, 【Number 2B】 The cognitive function estimation method according to claim 5 or 6.

8. The cognitive function estimation step estimates the subject's Revised Hasegawa Dementia Scale (HDS-R score) as the subject's cognitive function level based on the following formula (3B): In the following formula (3B): gamma １ means the foot pressure information of the subject's forefoot, gamma ２ means the foot pressure information of the subject's rear foot, σ １ means the contact time difference information between the heel and the thumb of the subject, σ ２ means the contact time difference information between the heel and the ball of the foot of the subject, σ ４ means the contact time difference information between the heel and the ball of the foot of the subject, σ ５ means the contact time difference information between the heel and the lateral part of the heel of the subject, φ １ means the contact rate information of the subject's thumb, φ ２ means the ground contact rate information of the subject's ball of the foot, φ ６ means the heel contact rate information of the subject, ψ represents the trajectory length information of the subject's foot pressure center, α １ , α ２ , α ３ , α ４ , α ５ , α ６ , α ７ , α ８ , α ９ , α １０ and β is a coefficient, 【Number 3B】 The cognitive function estimation method according to claim 5 or 6.

9. A program for estimating a cognitive function of a subject, causing a computer to execute a foot pressure information acquisition procedure, an estimation parameter calculation procedure, a judgment procedure, a cognitive function estimation procedure, and an output procedure; the step of acquiring foot pressure information includes acquiring foot pressure information of the subject; the estimation parameter calculation step calculates, based on the foot pressure information, ground contact time difference information, ground contact ratio information, and foot pressure center trajectory length information as cognitive function estimation parameters; the contact time difference information includes information about a time from when a part of the sole of the subject's foot first touches the ground to when another part of the sole touches the ground, The ground contact ratio information is information on the ratio of the time that each part of the foot is in contact with the ground to the time that the foot of the test subject is released from the ground, The information on the trajectory length of the foot pressure center is information on the length connecting points indicating the foot pressure center from the time when the foot of the subject contacts the ground until the foot is completely released from the ground, The determination procedure includes: determining a possibility that the subject has cognitive impairment based on the foot pressure information and the ground contact ratio information; The cognitive function estimation procedure includes: For a subject determined to have a possibility of having cognitive impairment, a cognitive function level of the subject is estimated based on at least two information selected from the group consisting of the foot pressure information, the ground contact time difference information, the ground contact ratio information, and the foot pressure center trajectory length information; The program, wherein the output step outputs at least one of the assessment result and the cognitive function level.

10. The determination step includes determining a possibility that the subject has cognitive impairment based on at least one of the following formulas (1C) and (1D): In the following formula (1C): μ １ means the probability that the subject is a healthy individual, gamma ２ means the foot pressure information of the subject's rear foot, φ ２ means the percentage of the subject's ball of the foot touching the ground, α １ , α ２ , and β is a coefficient, 【Number 1C】 In the following formula (1D), μ ２ denotes the probability that a subject is healthy or has mild cognitive impairment, σ ４ means the time difference between the heel and the ball of the foot touching the ground, φ ５ means the percentage of the subject's outer heel touching the ground, α １ , α ２ , and β is a coefficient, [Math 1D] The program according to claim 9.

11. The cognitive function estimation step estimates the subject's Revised Hasegawa Dementia Scale (HDS-R score) as the subject's cognitive function level based on the following formula (2B): In the following formula (2B): σ １ means the contact time difference information between the heel and the thumb of the subject, φ ３ means the percentage of the subject's forefoot center on the ground, φ ４ means the contact rate of the subject's hypothenar ball, α １ , α ２ , α ３ and β is a coefficient, 【Number 2B】 The program according to claim 9 or 10.

12. The cognitive function estimation step estimates the subject's Revised Hasegawa Dementia Scale (HDS-R score) as the subject's cognitive function level based on the following formula (3B): In the following formula (3B): gamma １ means the foot pressure information of the subject's forefoot, gamma ２ means the foot pressure information of the subject's rear foot, σ １ means the contact time difference information between the heel and the thumb of the subject, σ ２ means the contact time difference information between the heel and the ball of the foot of the subject, σ ４ means the contact time difference information between the heel and the ball of the foot of the subject, σ ５ means the contact time difference information between the heel and the lateral part of the heel of the subject, φ １ means the contact rate information of the subject's thumb, φ ２ means the ground contact rate information of the subject's ball of the foot, φ ６ means the heel contact rate information of the subject, ψ represents the trajectory length information of the subject's foot pressure center, α １ , α ２ , α ３ , α ４ , α ５ , α ６ , α ７ , α ８ , α ９ , α １０ and β is a coefficient, 【Number 3B】 The program according to claim 9 or 10.

13. A computer-readable recording medium having the program according to any one of claims 9 to 12 recorded thereon.

14. A cognitive function estimation device comprising: a cognitive function estimation terminal; and the cognitive function estimation device according to any one of claims 1 to 4; the cognitive function estimation terminal includes a foot pressure measurement unit and a communication unit, the foot pressure measuring unit is capable of measuring the foot pressure of the subject as the foot pressure information; the communication unit is capable of communicating with the cognitive function estimation device according to any one of claims 1 to 4 and transmitting the foot pressure information to the cognitive function estimation device; A cognitive function estimation system apparatus, wherein the cognitive function estimation terminal and the cognitive function estimation device are capable of communicating with each other.

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