Brain function evaluation system

Abstract

To provide a system capable of evaluating the degree of brain function highly accurately, safely and simply.SOLUTION: A brain function evaluation system comprises: a storage part for storing exemplifying data for exemplifying as video operation repeating finger movements with a period that fingers contact each other; a display part projecting video data corresponding to the exemplifying data; a sensor for measuring movements of a subject; and a control operation part performing arithmetic of instructions to display the exemplifying data to the display part and obtained measurement data. The control operation part adopts means which has a period with video in which the subject moves according to the video, extracts from the measurement data during the period with video a component of stimulation movement frequency to be stimulation component of stimulation movements repeating the finger movements and a stimulation movement external component to be a total of one or more components from frequencies other than the stimulation movement frequency component, has a calculation method for calculating a proportion of the stimulation movement external component and the stimulation movement frequency component, and has value calculated by the calculation method as evaluation value of a brain function.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a brain function evaluation system, and more particularly to a technique for easily performing evaluation of brain function through repeated finger movements including touching of fingers. [Background technology]

[0002] Conventional methods for evaluating brain function, including brain dysfunction such as dementia, include question-based tests such as the Mini Mental State Examination (MMSE) and analysis based on motor functions such as finger tapping, which involves repeatedly touching and releasing the fingers together (hereinafter referred to as finger tapping). The applicant has also developed a method in which the palm of the hand is rotated along with an image, the change in the angle of the rotation is subjected to frequency analysis, and evaluation is performed based on the ratio of the frequency of the rotation period to any higher frequency. Incidentally, finger tapping or other movements in which the fingers come into contact with each other are also easy for subjects to imagine, and are effective as a simpler repetitive finger movement than palm rotation.

[0003] However, unlike palm rotation, when fingers touch each other, the movement becomes discontinuous at the moment of contact, so the repetition period is interrupted and unnecessary frequency components are generated. Therefore, there was a problem that it could not be evaluated in the same way as palm rotation. Therefore, in order to increase the number of repetitive finger movements that can be measured, a method was needed that would enable evaluation of the ability of motor control function based on the ratio of the frequency of the repetition period to higher frequencies, even for repetitive movements that include contact between fingers.

[0004] In response to this technology, the applicant of the present application has already filed an application for a coordination assessment system using finger rotation (see Patent Document 1). More specifically, to assess coordination, the system rotates the fingers along with the video, detects the angle of the finger rotation with a sensor, and performs frequency analysis on the data to obtain an evaluation value. However, as described above, with the configuration of this prior art, it is difficult to perform a similar evaluation when the action includes touching fingers together, and the above problem is not yet solved. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2019-54988 A Summary of the Invention [Problem to be solved by the invention]

[0006] In view of the above problems, the present invention has an objective of providing a system that can evaluate brain function in a highly accurate, safe and simple manner in the same way as when rotational movements are used, by appropriately correcting data obtained from repetitive finger movements, including contact movements between fingers. [Means for solving the problem]

[0007] In order to solve the above problems, the present invention is a system capable of evaluating the degree of brain function, which is composed of a memory unit that stores example data for illustrating, as an image, repetitive finger movement having a period in which the fingers are in contact with each other, a display unit that displays image data corresponding to the example data, a sensor that measures the subject's movement, and a control and calculation unit that instructs the display unit to display the example data and calculates the acquired measurement data, wherein the control and calculation unit has an image period in which the subject moves in accordance with the image, and has a calculation method for extracting, from the measurement data of the image period, a stimulation movement frequency component, which is the frequency component of the stimulation movement of the repetitive finger movement, and a stimulation non-motion component, which is the sum of one or more components from frequencies other than the stimulation movement frequency component, and calculating the ratio of the stimulation non-motion component and the stimulation movement frequency component, and adopts a means for using the value calculated by the calculation method as an evaluation value of brain function.

[0008] The present invention also provides a system capable of evaluating the degree of brain function, which comprises a memory unit that stores example data for illustrating, as an image, repetitive finger movement having a period in which the fingers are in contact with each other, a display unit that displays image data corresponding to the example data, a sensor that measures the subject's movement, and a control and calculation unit that instructs the display unit to display the example data and performs calculations on the acquired measurement data, wherein the control and calculation unit has an image period in which the subject moves in accordance with the image, and an image-free period in which, after the image is stopped, the subject continues to move in accordance with the image in the image-free period, and has a calculation method for extracting, from the measurement data in the image-free period, a stimulation movement frequency component, which is the frequency component of the stimulation movement of the repeated finger movement, and a stimulation non-motion component, which is the sum of one or more components from frequencies other than the stimulation movement frequency component, and calculating a ratio between the stimulation non-motion component and the stimulation movement frequency component, and employs a means for using the value calculated by the calculation method as an evaluation value for brain function.

[0009] Furthermore, the present invention employs a means in which the repeating finger movement is a finger tapping motion in which the thumb and other fingers tap.

[0010] Furthermore, the present invention employs a means in which the control and calculation unit corrects the measurement data during a period in which the fingers are in contact with each other, based on the measurement data during a non-contact period.

[0011] Furthermore, the present invention employs a means in which the correction is performed using measurement data other than finger contact duration at the stimulation motion frequency.

[0012] Furthermore, the present invention employs a means in which the example data has a finger contact period as part of one cycle of a repeating finger movement.

[0013] Furthermore, the present invention provides a method in which the finger contact period is less than 10% of the period of the stimulation motion frequency.

[0014] The present invention also provides a means for evaluating cognitive impairment or mild cognitive impairment.

[0015] According to the brain function evaluation system of the present invention, by appropriately correcting data obtained from repeated finger movements including touching of the fingers, analysis based on frequency components is possible, and brain function can be evaluated using many movements that are simpler than rotating the hand. This has the excellent effect of contributing to an expansion of the number of subjects and reducing the burden on subjects, as well as enabling evaluation to be performed safely and easily with high accuracy. [Brief description of the drawings]

[0016] [Figure 1] 1 is a system block diagram showing an embodiment of a brain function evaluation system according to the present invention. [Diagram 2] FIG. 1 is a schematic diagram showing the procedure for implementing the brain function evaluation system according to the present invention. [Diagram 3] FIG. 2 is an explanatory diagram showing measurement data of the brain function evaluation system according to the present invention. [Figure 4] FIG. 2 is an explanatory diagram showing measurement data when the brain function evaluation system according to the present invention is implemented. [Diagram 5] FIG. 2 is a diagram showing frequency components of data from the brain function evaluation system according to the present invention. [Figure 6] FIG. 2 is a schematic diagram showing a procedure for correcting data in the brain function evaluation system according to the present invention. [Figure 7] FIG. 13 is a diagram showing the relationship between finger contact period and frequency in the brain function evaluation system according to the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] The greatest feature of the brain function evaluation system of the present invention is that it enables simple, safe, objective and quantitative evaluation of brain function in a short time by repeating finger movements that include periods of contact between the fingers. Hereinafter, an embodiment of a brain function evaluation system according to the present invention will be described with reference to the drawings.

[0018] The overall configuration and the configuration of each part of the brain function evaluation system described below are not limited to the examples below, and can be modified as appropriate within the scope of the technical idea of ​​the present invention, i.e., within the scope of configurations that can achieve the same functional effects.

[0019] The present invention will be described with reference to FIGS. FIG. 1 is a system block diagram showing an embodiment of a brain function evaluation system according to the present invention. FIG. 2 is a schematic diagram showing the procedure for implementing the brain function evaluation system according to the present invention. FIG. 3 is an explanatory diagram showing measurement data from sensors in the brain function evaluation system according to the present invention. FIG. 4 is an explanatory diagram showing measurement data from sensors over time when the brain function evaluation system according to the present invention is implemented. FIG. 5 is a histogram showing frequency components of data from the brain function evaluation system according to the present invention. FIG. 6 is a schematic diagram showing the procedure for correcting data in the brain function evaluation system according to the present invention, in which (a) to (c) show the procedure for calculating correlation values ​​to identify the position at which correction is to be performed, and (d) to (e) show the procedure for performing the correction and aligning the start and end points during the correction. FIG. 7 is a diagram showing waveforms, frequency characteristics, and NSM values ​​indicating the finger contact period in the brain function evaluation system according to the present invention, in which (a) shows the case where the finger contact period is 40% of the total, (b) shows the case where it is 20%, and (c) shows the case where it is 10%.

[0020] The evaluation device 1 is a system for evaluating brain function. This system measures and analyzes the subject's movements to evaluate the degree of the subject's brain function. It can also quantify cognitive impairment, the progress of which is difficult to grasp, and mild cognitive impairment (MCI), which is the early stage of cognitive impairment. In this embodiment, an evaluation will be described for a finger tapping motion in which the thumb and other fingers are tapped. The evaluation device 1 mainly comprises a sensor 100, a display unit 110, a control and calculation unit 130, and a storage unit 140.

[0021] The sensor 100 measures the movement of a subject, and more specifically, measures the distance between the tip of the subject's thumb and the tip of the index finger. The measurement value is acquired as a value going back and forth between a state where the distance between the fingers is zero, in other words, a state where the fingers are in contact with each other, and a state where the distance between the fingers is at its greatest. The speed of the reciprocation is the speed along the image displayed as the guide. The speed of the reciprocation of the guide is about 1 cycle per second. If the frequency components of the finger movement are measured by the sensor, for example, up to about 25 Hz, sampling at a cycle of 50 Hz or more, which is double 25 Hz, is required. In this embodiment, sampling is performed at 100 Hz to provide a margin.

[0022] The sensor 100 is a method of attaching finger-cap-like measuring devices to the tips of the thumb and index finger and magnetically or optically reading the distance between the two measuring devices. This method allows the distance between the fingers to be measured accurately. Alternatively, the distance between the thumb and index finger may be calculated from a camera image. By adopting such a method, the burden on the subject of attaching a device, etc. can be reduced. Another example is an infrared sensor such as LEAP MOTION (registered trademark of Leap Motion Inc.) which is recommended in terms of performance and price. By placing the LEAP MOTION at a position several tens of centimeters away from the hand, the movements of the fingers of the subject can be measured in detail in three dimensions without any special processing of the subject's hand. For example, three-axis data of the movements of both the tip of the thumb and the tip of the index finger can be extracted. Therefore, the distance between the fingers can also be measured accurately.

[0023] The display unit 110 is a part that shows the subject an example image, which is image data corresponding to example data that is a reference for finger movements, and displays measurement results and evaluation values. The display unit 110 is preferably located in a position where the subject can comfortably view it while making repetitive finger movements. This is because being located in such a position allows the subject to concentrate on the repetitive finger movements. The size is preferably a size that the subject can confirm without squinting. In addition, in order to display an image of the repetitive finger movements, it is preferable that the size of the hand on the display unit 110 is close to the actual size of the hand, which is less uncomfortable.

[0024] It is also possible to consider a mode including a speaker 120 that can provide guidance to the subject about the test, notify the start and end of the test, and notify the subject of measurement values ​​and evaluation values ​​by voice. Notifications can be made by the display unit 110, but by conveying information by voice, the notification effect is increased and it is more effective for people with poor eyesight than notifications by the display unit 110. In addition, it is often easier for subjects to understand the measurement itself if audio instructions are given. For example, audio instructions such as "Please tap your finger in time with the finger tapping image" or "Please continue moving your finger even after the display disappears" can help subjects proceed with the task more smoothly. Furthermore, by changing the sound, lamps, etc. according to the frequency of finger movement, they can be used in place of images, which is particularly suitable for visually impaired people or those with weak eyesight.

[0025] The control and calculation unit 130 is a part that controls the entire evaluation device 1, calculates data, etc. In other words, it instructs the display unit 110 to display the video data 210, and calculates the acquired measurement data 230. The control includes starting up the evaluation device 1, instructing the display unit 110 to display video data 210 which is an example image, instructing the speaker 120 to sound a sound, instructing the sensor 100 to operate, storing the acquired data in the memory unit 140, and instructing the display unit 110 to display the measurement values ​​and evaluation values. Furthermore, the control and calculation unit 130 corrects the measurement data during the contact period between the fingers and the surrounding period based on the measurement data during the non-contact period. The acquired measurement data 230 is divided by period and managed. The measurement data 230 of each period is stored in the storage unit 140 without being divided, and information for division is stored separately. If necessary, data divided into measurement unit data 240 in units of one second may be generated. Also, depending on the data processing method, the data may be divided into measurement unit data 240 in units of one second and stored in the storage unit 140. The evaluation value is calculated for each period. The evaluation value can be calculated for each period. For a given period, the finger contact period is corrected for each measurement unit data 240, and FFT is performed to calculate the relationship between the stimulation movement frequency 250, which is the repetitive frequency of the finger, and the measurement data 230. A representative value is calculated from the calculated multiple values ​​and used as the evaluation value. When measuring both the left and right fingers, the relationship between the stimulation movement frequency 250 and the measurement data 230 is calculated for each measurement unit data 240 for each hand, and a representative value is calculated. The two representative values ​​are then processed appropriately to obtain the final evaluation value.

[0026] Each operation and process of the control and calculation unit 130 will be described. The display unit 110 displays instructions for the measurement guidance, such as "We will perform a measurement to evaluate exercise. Please place your thumb and index finger together and apart in accordance with the hand movements on the screen. The image will disappear after 10 seconds, but please continue to place your thumb and index finger together and apart for 15 seconds after the image disappears, just as in the image that disappeared." This allows the subject to move smoothly into the measurement. By instructing the display unit 110 to display an example image, the video data 210 in the storage unit 140 is displayed as a moving image on the display unit 110. The video data 210 may be moving image data or a collection of still image data. The video data 210 is used to teach the subject how to tap with a finger.

[0027] It issues instructions to start and stop measurement to the sensor 100. During measurement, it receives data from the sensor 100 and stores it as measurement data 230 in the storage unit 140 together with the measurement time. Measurement is started, and after 10 seconds, which is the duration of period 1, have elapsed, the display on display unit 110 is stopped. At this point, the data from sensor 100 is grouped as data for period 1, and stored in memory unit 140 as a group of measurement unit data 240 in units of one second. Thereafter, the data from sensor 100 is grouped into one group for each of periods 2 to 4 every five seconds, and stored in memory unit 140 as a group of measurement unit data 240 in units of one second. 15 seconds after the image is turned off, a message such as "Thank you for your hard work. Measurement is now complete" is displayed on the display unit 110, and sound is also output as necessary.

[0028] After the measurement is completed, the measurement data is subjected to frequency analysis and the evaluation value is calculated. At this time, the measurement data contains multiple frequencies generated by the finger contact period 241. Therefore, the measurement results alone cannot be used for the motor control function evaluation method that assumes that the ideal stimulus movement has a single wave. Therefore, the measurement data is corrected to reduce the multiple frequency components generated by the finger contact period. Specifically, the finger contact period 241 of the measurement data is corrected with the data of the finger non-contact period, the relationship between the stimulation movement frequency 250, which is a single frequency, and the frequency of the corrected measurement unit data 230 is calculated, a representative value is calculated, and an evaluation value is obtained. In this way, the control and calculation unit 130 has image periods in which the subject moves in accordance with the image, and image-free periods in which the subject continues to move in accordance with the image from the image periods after the image has stopped, and has a calculation method for extracting, from the measurement data in the image-free periods, a stimulation movement frequency component, which is the frequency component of the stimulation movement of repeated finger movements, and a stimulation non-motion component, which is the sum of one or more components from frequencies other than the stimulation movement frequency component, and calculating the ratio of the stimulation non-motion component to the stimulation movement frequency component (the value obtained by dividing the stimulation non-motion component by the stimulation movement frequency component), and the value calculated by this calculation method is used as an evaluation value of brain function, or the original data for the evaluation value.

[0029] The image period is at least 8 seconds or more, preferably 10 seconds or more. At least 3 seconds is required for the subject to recognize the movement shown in the image and start moving in accordance with that movement, and a measurement period of at least 5 seconds is required to evaluate the subject's movement in accordance with the image. The image-free period is at least 10 seconds or more, preferably 15 seconds or more. If it is less than 10 seconds, there will be insufficient measurement data to evaluate the change in the subject's movement after the stimulating image disappears.

[0030] The storage unit 140 is a part that stores programs and data. It consists of a non-volatile memory and a volatile memory. The non-volatile memory stores programs, example data 200 for illustrating repetitive finger movements as images, image data 210 corresponding to the example data, and other data with fixed values. The program is a portion that describes the procedure for controlling the evaluation device 1. The program may be incorporated into the evaluation device 1 when it is manufactured, or may be installed later as an appropriate application. The example data 200 and the image data 210 are data that serve as a guide for making the subject exercise. Therefore, the example data 200 and the image data 210 must be constantly stored in the evaluation device 1. The measurement data 230, the measurement unit data 240, the fundamental frequency component 250, and the high frequency component 260 are data that are generated and calculated each time a measurement is performed, and therefore are stored in a volatile memory.

[0031] Example data 200, video data 210, measurement data 230, and unit of measurement data 240 will now be described. The example data 200 is a value indicating the distance between the fingers when the fingers are spread apart or narrowed, and indicates that one cycle is from the most open state to the state where the fingers are touching each other and then returning to the most open state, and that one cycle occurs in one second. The waveform is based on a sine wave with one cycle per second. By making the waveform a sine wave, it is possible to obtain a frequency configuration similar to that when the hand is rotated 180 degrees. Although a part of the sine wave with one cycle is limited by a certain value, there is only a stop period in one cycle, and as a whole, the fundamental frequency can be a sine wave with one cycle per second. In addition, the example data is assumed to have a finger contact period that is a part of one cycle of a repeating finger movement. Since the measurement data during and around the finger contact period needs to be corrected, the finger contact period is set to be shorter than the non-contact period. In this embodiment, the finger contact period is set to 1 / 5 of one cycle. The example data has at least one cycle of data and is used appropriately by repeating it as many times as necessary, etc. The example data is also called ideal stimulus motion data.

[0032] The video data 210 is a collection of videos showing the actual positions of the fingers corresponding to the example data 200. The video group may be a collection of still images or one cycle of video data. The measurement data 230 is data for each period, and the measurement unit data 240 is data obtained by further dividing the measurement data 230. In order to extract frequency components up to about 25 Hz, the data sampling frequency must be at least 50 Hz. In this embodiment, the sampling frequency is set to 100 Hz. Therefore, the data group is measured at 0.01 second intervals.

[0033] When calculating the evaluation value of brain function, it is possible to process the measurement data 230, which is the data for the entire measurement period, all at once, but in order to eliminate noise-like behavior such as sudden fluctuations, processing is performed for each measurement unit data 240. The length of the unit time to be divided is at least one period of the repeated finger movement. If FFT is used for processing, the fundamental frequency cannot be extracted sufficiently unless the period is at least the period of the fundamental frequency. In this embodiment, the measurement data 230 is divided into one-second intervals to generate measurement unit data 240, which is a measurable period of 1 Hz, which is the fundamental frequency. In other words, the measurement period of the measurement data is divided into a number of unit periods. The characteristic amount of the measured value for the ideal stimulus movement is calculated for each unit period, and the representative value is used as the evaluation value of the brain function.

[0034] 3 is a diagram showing the distance between the fingers of an ideal stimulus motion, which is an ideal finger tapping motion, and an example of a subject's reaction motion corresponding to the ideal stimulus motion. The horizontal axis is time. The vertical axis is the distance between the fingers. The ideal stimulus movement is a waveform with a part of a sine wave missing, and has a fundamental frequency of 1 Hz. During the first 10 seconds, when the image is present, the subject reacts in accordance with the image data of the ideal stimulus movement, and during the last 15 seconds, when the image is not present, the image data of the ideal stimulus movement is stopped, and the subject estimates, remembers, and reacts to the ideal stimulus movement, as shown in the waveform. For the first 10 seconds, the stimulus motion image is displayed, so the reaction motion of healthy subjects does not differ significantly from the ideal stimulus motion. However, after 10 seconds, the stimulus motion image stops being displayed, so the difference between the reaction motion and the ideal stimulus motion accumulates without being corrected, and the difference between them increases. In the first half, subjects perform movements similar to the ideal stimulus movements they have seen, so memory-related parts of the brain are less involved. In the second half, subjects perform movements based on their memories of the ideal stimulus movements they have seen in the past, so memory-related parts of the brain are more involved. Therefore, subjects whose performance deviates significantly from the ideal stimulus movement in the latter half of the experiment can be assumed to have a disorder in memory of the most recent movement (short-term memory), which is one of the characteristics of cognitive impairment or mild cognitive impairment.

[0035] In the present invention, the ideal stimulation movement is a waveform that is missing a part of a sine waveform, has a fundamental frequency of 1 Hz, and includes other frequencies. The measurement data of the subject's movement that imitates this ideal stimulus movement also imitates a waveform that is missing part of a sine waveform, so it originally contains frequencies other than the fundamental frequency of 1 Hz. Therefore, if the subject is evaluated based on the ratio of the fundamental frequency to other frequencies, there is a possibility that the evaluation value will deviate from the actual evaluation value. Therefore, a process is performed to correct the finger contact period 241 portion of the measurement data. The correction process is performed using measurement data from a period that corresponds to the opposite phase of the finger contact period at the stimulation movement frequency.

[0036] The outline of the correction is as follows: the section including the maximum value, but excluding the finger contact period and its vicinity, is used as the reference data (correction data), which is inverted (multiplied by -1), the correlation coefficient with the measurement data section including the finger contact period is calculated, and the correction is performed using the position where the correlation coefficient is largest as the reference. The correction data is linearly connected so that the connection points between the correction data and the measurement data are continuous. There are various methods for linearly connecting the correction data, but in this embodiment, a method for adjusting the time axis of the correction data will be described. That is, the function at+b is added to the value of each time of the correction data. a and b are values ​​that are continuous at the start and end points, which are the connection points.

[0037] The details will be explained with reference to FIG. 6(a), the measurement data 230 is a generally sine wave with a partially flat waveform, similar to the example data 200. The highest point of the waveform is the maximum finger spacing value 271, which represents the state in which the distance between the thumb and index finger is the largest. The lowest point of the waveform is the contact finger spacing value 272, which represents the state in which the fingers are in contact. The value at this time is set to zero. In addition, if it is assumed that a sine wave also has a negative portion, this is taken as an estimated sine wave waveform 242. The value at this time is an estimated minimum finger spacing value 273. For example, if finger contact period 241, which is the period during which the thumb and index finger are in contact, is 1 / 10 of one cycle, finger contact period 241 is 0.1 seconds. In this case, estimated minimum value 273 is calculated from the sine waveform to be approximately -0.1. If the correction is performed for 0.1 seconds before and after the finger contact period 241, in addition to the finger contact period 241, then the correction will be performed for a total of 0.3 seconds. It is preferable to perform the correction based on about 50% to 60% of the correction period of 30%, because the period to be corrected and the data to be corrected do not overlap. The correction period is determined by measurement, experiment, etc.

[0038] Data for correcting the vicinity of the finger contact period 241 is obtained from the non-contact period of the finger in the measurement data. Data near the maximum finger distance value 271, which is considered to be the furthest region, is used as data that is less affected by the finger contact period 241. When performing correction, it is believed that the higher the correlation coefficient between the waveform of the area to be corrected and the waveform used for correction, the smoother the correction can be. Therefore, the waveform to be used for correction near the maximum finger spacing value 271 is cut out and used as correlation confirmation data 270. The correlation confirmation data 270 is, for example, data for 0.25 seconds on either side of the maximum value 271, and 0.5 seconds in total (FIG. 6(a)).

[0039] The correlation confirmation data 270 is multiplied by −1, and the waveform shape is inverted upside down. Therefore, the correlation confirmation data 270 has a shape similar to the shape of the vicinity of the finger contact period 241 to be corrected (FIG. 6(b)).

[0040] A correlation coefficient between 0.5 seconds of correlation confirmation data 270 and 0.5 seconds of any region of the measurement data is calculated using a correlation function. The area to be checked is from the start of one cycle to the end of one cycle with a slight overlap. All correlation coefficients are calculated while moving through the data sequentially (Figure 6(c)). The area with the largest correlation coefficient is the position where the waveform of the original data and the correlation confirmation data 270 match best. Correct the central 3 / 10 of the area that matches best with the correlation confirmation data 270.

[0041] 6(d) shows the relationship between the original waveform data and the correction data 280. In this example, the central 0.3 seconds of the correlation confirmation data 270 is used as the correction data 280. A total of 0.3 seconds of measurement data is corrected, consisting of 0.1 seconds of the finger contact period 241 and 0.1 seconds before and after it. If there is little distortion of the waveform before and after the finger contact period 241, the period before and after may be narrowed to less than 0.1 seconds. In that case, the range of the correction data 280 is narrowed accordingly.

[0042] A correction data start point 281 of the correction data 280 is aligned with a measurement data correction start point 290, and a correction data end point 282 is aligned with a measurement data correction end point 291 (FIG. 6(e)). Linearly connect the correction data so that the start and end points are continuous. Determine the coefficients a and b of at+b so that the start and end points are continuous, and add the values ​​of at+b at each time to the correction data. Calculate a and b for correction. Let the y value of measurement data correction start point 290 be h0, and the y value of measurement data correction end point 291 be h1. The x and y values ​​of the correction data start point 281 are x0 and y0, and the x and y values ​​of the correction data end point 282 are x1 and y1. Simultaneous equation (Formula 1) h0=y0+ax0+b (Formula 2) h1=y1+ax1+b Substitute h0, y0, x0, h1, y1, and x1 into the simultaneous equations to obtain a and b. In this embodiment, h0=0.3, y0=-0.7, x0=0.6, h1=0.3, y1=-0.7, and x1=0.9. When calculating a and b, we get a = 0 and b = 1.0. By adding 0t+1.0 to the correction data, the correction data can be linearly connected. Therefore, the measurement unit data 240 and the adjusted correction data 284 can be smoothly connected at the connection portion, and an overall waveform can be obtained in which unnecessary high frequency components are suppressed.

[0043] By correcting the measurement data in this way, an evaluation method for calculating the relationship between the stimulation movement frequency 250 and the measurement data 230, similar to the pronation / supination movement of the hand, becomes available.

[0044] As a method for calculating the relationship between the stimulation motion frequency 250 and the measurement data 230, there is a method for calculating the value of NSM (Non Smoothness Measure). NSM quantifies the degree to which the measurement unit data, which is the subject's movement, differs from a sine wave when the stimulus movement is a sine wave. The measurement unit data 240 is converted to frequency components and the ratio of signal strength between the stimulation motion frequency 250 and other higher frequencies is calculated.

[0045] The specific procedure for calculating NSM will be explained. The measurement unit data 240 is converted into signal strength and phase for each frequency component by FFT (Fast Fourier Transform). In this embodiment, the finger is moved at a period of 1 Hz, so the stimulation movement frequency 250, which is the fundamental frequency, is 1 Hz. The frequency components include 1, 2, 3, 4, 5, 6, 7, 8, 9,...25 Hz. An example of frequency components of signal intensity is shown in Figure 5. The fundamental frequency, the stimulation motion frequency 250, is 1 Hz. 2, 3, 4, 5, 6, 7, 8, 9... 25 Hz is the HIGH frequency 260. The sum of the signal intensity of the HIGH frequency components is the HIGH frequency component.

[0046] If the signal strength component value of frequency n is pn, the value of NSM (Non Smoothness Measure) is (Formula 3)NSM=(p2+p3+p4+...+p25) / p1 In (Equation 3), pn is the signal intensity of the n Hz component. This is the value obtained by dividing the HIGH frequency component, which is the sum of the signal strengths of the frequency components p2 to p25, by the signal strength value of p1, which is the fundamental frequency. If the measurement data 230 has the same waveform as the ideal stimulus motion, the values ​​of p2 to p25 are zero, and the NSM is zero. The greater the difference from the ideal stimulus motion, the greater the values ​​of p2 to p25, and the greater the NSM value. In other words, the larger the NSM value, the greater the ratio of the component amount of deviation from the standard. The NSM value is calculated in units of measurement data 240, which is data per second. In this example, all values ​​from p2 to p25 are added, but it is also possible to add only components that are deemed effective for the inspection, or to change the weighting for each frequency.

[0047] Since NSM observes the subject's reaction movement based on an ideal stimulus movement, the ideal stimulus movement is displayed as an example image and measurement is started. For example, if the example images are not displayed, there is no standard and the subject will react with their own motor cycle. In that case, the measurement standard will tend to be how many times the subject can do the movement per unit time, which is suitable for evaluating motor ability, but makes it difficult to evaluate the brain's motor control function. The subject is forced to move his / her fingers as quickly as possible, which often results in fatigue. Displaying example images is also effective in reducing the burden on the subject. In addition, since the embodiment includes the contact movement of the fingers, the accuracy of the measurement will decrease unless the contact time of the fingers is managed. By using the example video, the subject will match the contact time of the fingers to the example video as well as the period of the entire movement, so that the contact time of the fingers can be managed. Therefore, the contact time can be corrected with high accuracy, and as a result, the measurement accuracy can be improved. In this embodiment, the period of the example data is set to 1 second. If the period is short, it will be a heavy burden on elderly people, etc. If the period is 1 second, it is a relatively slow period, so the subject can follow it sufficiently. By setting such values, the measurement can be performed easily for many people, from children to the elderly, without causing any mental burden.

[0048] For each measurement unit data, the relationship between the stimulation motion frequency and the measurement data is calculated using NSM, and then a representative value is calculated for the NSM value group. For example, when five NSM values ​​are calculated, a representative value is calculated from them. The representative value may be the average value, the median value, the minimum value, or the like. It is also possible to use the standard deviation value and the fluctuation range. By using the standard deviation value, the stability of the subject's movement can be evaluated. If the subject is healthy, the variation is small, so the standard deviation value will be small. The greater the degree of disability, the larger the standard deviation value will be. By using the fluctuation range, it is possible to grasp the maximum range of fluctuation in the subject's finger movement. For a healthy person, the maximum range of shaking is extremely small, but the greater the degree of disability, the greater the fluctuation. If the representative value is an average value, the average of the five NSM values ​​is calculated. When the measurement data 230 is relatively stable, such as when moving a finger while looking at an example image, there is little variation and blurring in the NSM value, and the noise is small, so the average value is effective as a representative value. When the measurement data is relatively unstable, such as when moving a finger without looking at an example image, the NSM values ​​vary widely and fluctuate significantly up and down, so the median, which can exclude values ​​that fluctuate up and down, is effective.

[0049] In addition, instead of simply using the measured values ​​for each side as the evaluation value, the difference between the left and right values ​​or their absolute value may be taken. By using such values, it may be possible to estimate the state of brain function in detail from the difference in left and right movements.

[0050] The measurement procedure will be explained with reference to Figures 2 and 4. The measurement procedure is shown diagrammatically in Figure 2. As shown in the figure, measurements are taken on both hands. Measurements can be made using either the left or right hand alone, but generally, when the fingers of the left and right hands are moved at the same time, the left and right movements are synchronized extremely well. In addition, when the left and right hands are moved in a synchronized manner, the motor control performance improves. This is because, when both hands are moved, a wider range of brain functions work in conjunction with the coordination of both hands, improving the motor control function. Conversely, when movements are performed using only one hand, the motor control function is thought to deteriorate. FIG. 4 is a diagram showing example data and measurement data from periods 1 to 4. The horizontal axis is time, and the vertical axis is finger spacing distance value, and shows the finger spacing distance waveform of example data in each period and the finger spacing distance waveform of the subject. The serial numbers written at the top of the waveforms are measurement unit data numbers 220 in which the measurement unit data are arranged in order. In this embodiment, the period is 25 seconds in 1-second increments, so the numbers are 1 to 25. The waveform data for each period is waveform data 230, and the data for each second in each period is waveform unit data 240.

[0051] The measurement is performed in four consecutive periods. Period 1 is a video period, during which the subject taps the fingers of the subject's right hand RH and the subject's left hand LH in imitation of the video data 210 on the display unit 110 (top of FIG. 2). 4, the subject performs finger tapping in imitation of the example data 200, performing a movement similar to that of the example data 200. Therefore, the measurement data 230 is data in a form similar to that of the example data. The measurement data 230 includes data on both the right hand and the left hand.

[0052] Periods 2, 3, and 4 will be played consecutively after period 1. Periods 2, 3, and 4 are periods without images, and the subject continues to perform finger tapping even after the image on the display unit 110 disappears (lower part of FIG. 2). Period 1 requires at least 8 seconds to allow the subject to get used to the movements and to memorize the video. In this embodiment, the period is set to 10 seconds to allow for some leeway. Periods 2, 3, and 4 are the periods in which the measurement work is performed. Period 2 is the period in which the measurement is performed and takes 5 seconds. Periods 3 and 4 are periods in which finger tapping is performed continuously. The total duration of periods 2, 3, and 4 is preferably 10 seconds or more. In this embodiment, to allow for some leeway, each of periods 2, 3, and 4 is set to 5 seconds, for a total of 15 seconds. 4, during periods 2, 3, and 4 where no image is present, the subject recalls the image of the example data 200 and performs finger tapping so as to approximate the movement of the example data 200. Therefore, the measurement data 230 follows the example data in memory, and the difference between the measurement data 230 and the example data is larger than that in period 1.

[0053] In this embodiment, the waveform data 230 of period 2 is used to generate an evaluation value. In other words, the measurement data of the no-video period used to generate an evaluation value is obtained only from period 2, which is the first period when the no-video period is divided into a plurality of periods. When considering brain dysfunction as part of brain function, it is important to check short-term memory for cognitive impairment and mild cognitive impairment. Period 2 is a very short period, just after the stimulus image disappeared, but the finger movement relies on motor memory. Therefore, the data from Period 2 is useful for confirming the correlation between memory and movement. Furthermore, when using period 2 in the measurement data, periods 3 and 4 may be used as supplementary data in some cases. Instructing the subject to move his / her fingers until periods 3 and 4 is also effective because it allows good data for the first half to be obtained even for subjects who tend to slacken in the latter half.

[0054] Select the waveform unit data 240 for the right hand and the left hand of period 2. There are five waveform unit data 240 with waveform unit data numbers 11 to 15. There are five of each. The NSM values ​​are calculated for these. The median of the determined NSM values ​​is calculated as a representative value for each of the right and left hands. As the evaluation value, either the representative value for the left or right hand may be selected, or a numerical value derived from both may be used.

[0055] In the case of a healthy person, the movements of the left and right hands are synchronized very well. Therefore, the movements of the left and right hands are almost the same, so naturally the representative values ​​for the left and right hands are also close. Therefore, if the representative values ​​are good enough, it is sufficient to use either the left or right value. In the case of mild cognitive impairment (MCI) testing, it is assumed that there is little difference between the left and right sides, so attention is focused on the measurement value on the right side, which has better measurements. If it is guaranteed that the measurements are good, it is also possible to analyze both the left and right sides and use the better or worse measurement value for each side as the evaluation value. Based on the calculated evaluation value, the subject will be encouraged to consult a doctor and undergo regular checkups.

[0056] Thus, according to this embodiment, brain function evaluation, particularly evaluation of cognitive impairment and mild cognitive impairment, can be performed without asking the subject many questions or requiring the subject to wear equipment, etc., and therefore the burden on the subject is reduced and the evaluation can be performed easily. Furthermore, according to this embodiment, it is possible to perform a numerical evaluation of cognitive impairment or mild cognitive impairment in just 25 seconds, thereby improving the efficiency of testing. Furthermore, according to this embodiment, since an image is used as a measurement standard, there is little individual variation, and data can be collected with high accuracy. Furthermore, according to this embodiment, the repetitive motion is repeated once per second, so that even elderly people can easily perform the motion.

[0057] Although an example using the measurement data of period 2 has been described as an embodiment, the measurement time of the subject can be shortened by using the measurement data of period 1. When performing a measurement during a period without examples, it takes a total of about 18 to 25 seconds, but when only examples are provided, it only takes about 8 to 10 seconds, which can further reduce the burden on the subject. The measurement time should be at least 8 seconds, taking into account the subject's familiarity with the finger movements and the measurement accuracy, but in this embodiment, it is set to 10 seconds to allow for some leeway.

[0058] The measurement was performed for 10 seconds only in period 1. Period 1 was a video period, during which the subject performed finger tapping with the subject's right hand RH and left hand LH in imitation of the video data 210 on the display unit 110 (top of FIG. 2). In terms of FIG. 4, the measurement is completed in period 1, so that the subject simply performs finger tapping following the example data 200 for 10 seconds and performs a movement similar to the example data 200 to complete the measurement. Calculate the NSM value for each of the 20 waveform unit data 240 for the right and left hands in period 1, 10 each. Calculate a representative value for each of the right and left hands. This is an operation following the example data, and there is often little variation, so the representative value is the average value. The evaluation score is calculated using either the representative value of the right hand, the representative value of the left hand, or both.

[0059] Subjects can undergo speedy testing for brain function, such as cognitive impairment and mild cognitive impairment, in a short time of just 10 seconds, lowering the barrier to testing and increasing the opportunities for testing. If the test results indicate that a doctor's confirmation is necessary, the user will be notified and a diagnosis can be made.

[0060] Since the evaluation system of the present invention allows testing to be performed in a short period of time, it is possible to periodically test a specific individual and check for changes in the evaluation value, thereby making it possible to ascertain subtle changes in the state of brain function. Therefore, it would be beneficial to incorporate this into regular health checkups, etc.

[0061] In this embodiment, an example has been described in which the measurement data of the finger contact period is corrected by the measurement data of the non-contact period, but an example will be described in which the correction process is omitted by adjusting the length of the finger contact period 241. As previously explained, having finger contact period 241 results in the example data including frequencies other than stimulus motion frequency 250. 7(a) shows a waveform diagram of example data when the finger contact period 241 is 0.4 seconds with one cycle being 1 second, and a frequency spectrum diagram of the example data. In the waveform diagram, there is a finger contact period 241 for 0.4 seconds in the latter half of the sine wave, during which the waveform is flat. In the frequency spectrum diagram, in addition to the fundamental wave of 1 Hz, values ​​corresponding to the finger contact period 241 are present in the vicinity of 2 Hz to 10 Hz. For example, the signal strength value is 25.2 at 1 Hz, 4.66 at 2 Hz, 2.21 at 3 Hz, etc. When each value is converted into an NSM value, it is approximately 0.38. Generally, the measurement values ​​of subjects using NSM include values ​​of about 0.1, so a value of 0.38 is large as noise and will not be a reliable evaluation value unless correction is made.

[0062] 7(b) shows a waveform diagram of example data when the finger contact period 241 is 0.2 seconds with one cycle being 1 second, and a frequency spectrum diagram of the example data. As shown in the waveform diagram of the example data, the finger contact period 241 is located near the lowest value of the sine wave and lasts for 0.2 seconds. Looking at the signal strength values ​​in the frequency spectrum diagram, the values ​​are 30.7 at 1 Hz, 1.16 at 2 Hz, 0.96 at 3 Hz, etc., which is 0.15 when converted to an NSM value. This exceeds the possible subject measurement value of 0.1, and without correction, a reliable evaluation value cannot be obtained.

[0063] 7(c) shows a waveform diagram of example data when the finger contact period 241 is 0.1 seconds with one cycle being 1 second, and a frequency spectrum diagram of the example data. As shown in the waveform diagram of the example data, the finger contact period 241 is located near the lowest value of the sine wave and lasts for 0.1 seconds. Looking at the signal strength values ​​in the frequency spectrum diagram, the values ​​are 31.0 at 1 Hz, 0.86 at 2 Hz, 0.67 at 3 Hz, etc., which is 0.072 when converted to an NSM value. This is below the possible subject measurement value of 0.1, making it possible to obtain a reliable evaluation value without correction.

[0064] When a subject is instructed to simply tap with his / her fingers at one second intervals, it is difficult to adjust the finger contact period 241 even if the overall cycle is about one second. However, by defining the overall cycle and the duration of the finger contact period 241 in the example data, the subject moves his or her fingers in accordance with the example data and the video data corresponding to the example data, so that it is quite possible to manage the finger contact period 241 to 0.1 seconds. Therefore, in the present invention, if the subject can perform a finger tapping motion with a finger contact period 241 of 0.1 seconds following the example data, an evaluation value can be generated without correcting the measurement data. In other words, by making the finger contact period 10% or less of the period of the stimulation movement frequency, an evaluation value can be generated without correcting the measurement data.

[0065] The present invention relates to a brain function evaluation system, and one of its features is that it can quantify the evaluation of brain function by actions including finger contact actions such as finger tapping. Dementia is one of the disorders related to brain function. Dementia is a disease that progresses gradually and is difficult to cure completely. Therefore, the present invention, which can quantify the progress of the disease, is effective as a system for identifying and evaluating dementia. In addition, it is more difficult to distinguish mild cognitive impairment (MCI), which is an early stage of dementia, than dementia. According to the present invention, it is possible to determine whether a more detailed test for mild cognitive impairment (MCI) is necessary in a short time. Use of the brain function evaluation system of the present invention during regular health checkups, etc. can contribute to the early detection of dementia and mild cognitive impairment. Furthermore, by managing brain function evaluation values ​​for each individual, it is possible to check the degree of progression of brain function, dementia, and mild cognitive impairment (MCI) with a high degree of accuracy, which can contribute to the early detection of dementia and mild cognitive impairment (MCI). [Industrial Applicability]

[0066] The brain function evaluation system of the present invention is a system that can evaluate the degree of brain function with high accuracy, safely and simply, and is particularly effective in evaluating cognitive impairment and mild cognitive impairment, and is believed to have great industrial applicability. [Explanation of symbols]

[0067] 1. Evaluation device 100 Sensors 110 Display section 120 Speaker 130 Control and calculation section 140 Storage section 200 Example Data 210 Video Data 220 Measurement unit data number 230 Measurement Data 240 Unit of measurement data 241 Hand contact period 242 Sine wave estimated waveform 250 Stimulus movement frequency (fundamental frequency) 260 HIGH FREQUENCY 270 Correlation confirmation data 271 Maximum finger interval value 272 Finger distance value at contact 273 Estimated minimum finger spacing 280 Correction Data 281 Start of correction data LH Subject's left hand RH Subject's right hand

Claims

1. A brain function evaluation system, comprising: The device is comprised of a storage unit that stores example data for illustrating, as an image, a repetitive finger movement having a period in which the fingers are in contact with each other, a display unit that displays image data corresponding to the example data, a sensor that measures the subject's movement, and a control and calculation unit that instructs the display unit to display the example data and performs calculations on the acquired measurement data, The control and calculation unit has an image period in which the subject exercises in accordance with the image, and A method for calculating a ratio of the stimulation motion frequency component, which is a frequency component of the stimulation motion of repeating the finger movement, to the stimulation motion frequency component, and the stimulation motion non-frequency component, which is a sum of one or more components from frequencies other than the stimulation motion frequency component, is provided. A brain function evaluation system, characterized in that the value calculated by the calculation method is used as an evaluation value of brain function.

2. A brain function evaluation system, comprising: The device is comprised of a storage unit that stores example data for illustrating, as an image, a repetitive finger movement having a period in which the fingers are in contact with each other, a display unit that displays image data corresponding to the example data, a sensor that measures the subject's movement, and a control and calculation unit that instructs the display unit to display the example data and performs calculations on the acquired measurement data, The control and calculation unit includes: an image period during which the subject exercises in accordance with the image; and a video-free period in which the subject continues to exercise following the video of the video-containing period after the video is stopped; A method for calculating a ratio of the stimulation motion frequency component, which is a frequency component of the stimulation motion of repeating the finger movement, and the stimulation motion non-frequency component, which is a sum of one or more components from frequencies other than the stimulation motion frequency component, is provided, from the measurement data of the image non-period; A brain function evaluation system, characterized in that the value calculated by the calculation method is used as an evaluation value of brain function.

3. 3. The brain function evaluation system according to claim 1, wherein the repeated finger movement is a finger tapping movement in which the thumb and other fingers tap.

4. 4. The brain function evaluation system according to claim 3, wherein the control and calculation unit corrects the measurement data during a finger contact period, which is a period during which fingers are in contact with each other, based on the measurement data during a non-contact period.

5. 5. The brain function evaluation system according to claim 4, wherein the correction is performed using the measurement data for a period that corresponds to an opposite phase of a finger contact period in a stimulation movement frequency.

6. 4. The brain function evaluation system according to claim 3, wherein the example data indicates that a part of one cycle of the repeated finger movement is a finger contact period.

7. 7. The brain function evaluation system according to claim 6, wherein the finger contact period is 10% or less of a period of the stimulation motion frequency.

8. The brain function evaluation system according to claim 3, which is used for evaluating cognitive impairment.

9. The brain function evaluation system according to claim 3, which is used for evaluating mild cognitive impairment.

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