JP2020130336A - Brain activity state monitoring device, brain activity state monitoring program and brain activity state monitoring method - Google Patents

Abstract

To precisely determine a brain activity state of a subject individual.SOLUTION: A brain activity state monitoring device includes: a data acquisition unit showing a brain activity state of a subject, showing first data collected in a first period and the brain activity state of the subject, and acquiring second data collected in a second period following the first period; a gravity center calculation unit for calculating the gravity center of the first data on a phase plane where the Mahalanobis distance is defined; a distance calculation unit for calculating the Mahalanobis distance from the gravity center about the second data, and calculating a temporal change of the Mahalanobis distance of the second data; a determination unit for determining whether or not the Mahalanobis distance of the second data exceeds a predetermined threshold more than a predetermined frequency; and an output unit for outputting the information of showing the brain activity state of the subject, when determined that the Mahalanobis distance of the second data exceeds the predetermined threshold more than the predetermined frequency.SELECTED DRAWING: Figure 1

Description

The present invention relates to a brain activity state monitoring device, a brain activity state monitoring program, and a brain activity state monitoring method.

Research has been conducted on techniques for monitoring the activity state of the brain of a subject, using it for grasping the health state of the subject, and estimating the influence on the movement of the subject. For example, Patent Document 1 discloses a seizure reporting device including a phase analysis unit, a feature amount calculation unit, a Mahalanobis distance calculation unit, a determination unit, and a notification control unit. The phase analysis unit converts the electroencephalogram time series data from the measurement electrode and the reference electrode mounted on the patient's head into an electroencephalogram trajectory in the phase space. The feature amount calculation unit calculates the feature amount from the electroencephalogram trajectory. The Mahalanobis distance calculation unit obtains the Mahalanobis distance of the feature quantity with reference to the reference space. The determination unit determines whether or not an epileptic seizure has occurred according to the Mahalanobis distance. The notification control unit notifies the patient that the seizure occurrence is reported in response to the seizure occurrence signal.

Japanese Unexamined Patent Publication No. 2004-350870

However, since it is necessary to create a reference space in advance for this seizure reporting device, it may not be possible to calculate the Mahalanobis distance of an appropriate feature amount if the reference space is not created. In addition, this seizure reporting device does not always calculate an appropriate reference space for each individual subject. Therefore, this seizure reporting device may not be able to accurately determine whether or not an epileptic seizure has occurred.

Therefore, it is an object of the present invention to provide a brain activity state monitoring device, a brain activity state monitoring program, and a brain activity state monitoring method capable of accurately determining the brain activity state of an individual subject.

One aspect of the present invention shows the activity state of the brain of the subject, shows the first data collected in the first period and the activity state of the brain of the subject, and follows the first period. A data acquisition unit that acquires the second data collected in the second period, a center of gravity calculation unit that calculates the center of gravity of the first data on the phase plane in which the Mahalanobis distance is defined, and the center of gravity of the second data. The distance calculation unit that calculates the Mahalanobis distance from the second data and calculates the change over time in the Mahalanobis distance of the second data, and whether or not the Mahalanobis distance of the second data exceeds a predetermined threshold number of times or more. A determination unit for determining and an output unit for outputting information indicating the activity state of the brain of the subject when it is determined that the Mahalanobis distance of the second data exceeds a predetermined threshold number of times or more. It is a brain activity status monitoring device equipped.

In one aspect of the present invention, the computer shows the activity state of the brain of the subject, the first data collected in the first period, and the activity state of the brain of the subject, and the first period. A data acquisition function for acquiring the second data collected in the second period following the above, a center of gravity calculation function for calculating the center of gravity of the first data on the phase plane in which the Mahalanobis distance is defined, and the second data. The distance calculation function that calculates the Mahalanobis distance from the center of gravity and calculates the change over time in the Mahalanobis distance of the second data, and whether the Mahalanobis distance of the second data exceeds a predetermined threshold number of times or more. A judgment function for determining whether or not the data is present, and an output function for outputting information indicating the activity state of the brain of the subject when it is determined that the Mahalanobis distance of the second data exceeds a predetermined threshold number of times or more. It is a brain activity status monitoring program to realize.

One aspect of the present invention shows the activity state of the brain of the subject, shows the first data collected in the first period and the activity state of the brain of the subject, and follows the first period. A data acquisition step for acquiring the second data collected in the second period, a center of gravity calculation step for calculating the center of gravity of the first data on the phase plane in which the Mahalanobis distance is defined, and the center of gravity for the second data. The distance calculation step of calculating the Mahalanobis distance from the second data and calculating the change over time of the Mahalanobis distance of the second data, and whether or not the Mahalanobis distance of the second data exceeds a predetermined threshold number of times or more. A determination step for determining and an output step for outputting information indicating the activity state of the brain of the subject when it is determined that the Mahalanobis distance of the second data exceeds a predetermined threshold number of times or more. It is a brain activity monitoring method including.

According to the present invention, it is possible to accurately determine the brain activity state of an individual subject.

It is a figure which shows an example of the functional structure of the brain activity state monitoring apparatus which concerns on embodiment of this invention. It is a figure for demonstrating the principle that the sensor which concerns on embodiment of this invention collects the data which shows the activity state of the brain of a subject from the oxygen concentration of the blood flow of a subject using near infrared light. An example of changes over time in oxygen saturation, oxygenated hemoglobin concentration, and deoxidized hemoglobin concentration when the subject according to the embodiment of the present invention is performing manual operation using a simulated operation device and before and after that. It is a figure which shows. Oxygen saturation, oxygenated hemoglobin concentration and deoxygenated hemoglobin concentration when the subject according to the embodiment of the present invention is in a vehicle in which automatic driving using a simulated driving device is executed and before and after that. It is a figure which shows an example of the time-dependent change of. It is a figure which shows an example of the case where the first data and the second data collected when the subject which concerns on embodiment of this invention performs a manual operation using a simulated operation apparatus is shown in the phase space. An example in which the first data and the second data collected when the subject according to the embodiment of the present invention is in a vehicle in which automatic driving using a simulated driving device is executed are shown in the phase space. It is a figure which shows. It is a figure which shows an example of the change with time of the Mahalanobis distance of the first data and the Mahalanobis distance of the second data collected when the subject according to the embodiment of the present invention is performing manual operation using a simulated driving device. is there. The Mahalanobis distance of the first data and the Mahalanobis distance of the second data collected when the subject according to the embodiment of the present invention is in a vehicle in which automatic driving using the simulated driving device is executed, over time. It is a figure which shows an example of the change. It is a flowchart which shows an example of the processing executed by the brain activity state monitoring apparatus which concerns on embodiment of this invention.

An example of the brain activity state monitoring device according to the embodiment will be described with reference to FIGS. 1 to 8. FIG. 1 is a diagram showing an example of a functional configuration of a brain activity state monitoring device according to an embodiment of the present invention. As shown in FIG. 1, the brain activity state monitoring device 1 includes a data acquisition unit 11, a center of gravity calculation unit 12, a distance calculation unit 13, a determination unit 14, and an output unit 15.

The data acquisition unit 11 acquires the first data and the second data indicating the activity state of the brain of the subject from the sensor 20 shown in FIG. The first data is collected by the sensor 20 in the first period. The second data is collected by the sensor 20 in the second period following the first period.

FIG. 2 is a diagram for explaining the principle that the sensor according to the embodiment of the present invention collects data indicating the activity state of the brain of the subject from the oxygen concentration of the blood flow of the subject using near infrared light. Is. In FIG. 2, the horizontal axis represents time, the vertical axis on the right side represents oxygen saturation, and the vertical axis on the left side represents hemoglobinometry. Changes over time in oxygen saturation, oxygenated hemoglobinometry, and deoxygenated hemoglobinometry. Is indicated by a single point chain line C1, a solid line C2, and a dotted line C3.

As shown in the portion surrounded by the dotted line B in FIG. 2, when the brain of the subject is actively active, the cranial nerves actively consume oxygen and glucose, so that the brain of the subject is in the blood of the brain. Oxygen saturation and oxygenated hemoglobinometry increase.

The sensor 20 is attached to the head of the subject, for example, and collects the first data and the second data using near-infrared spectroscopy (NIRS). Specifically, the sensor 20 has a light source and a light receiving sensor that emit near-infrared light having a wavelength of about 700 nm to about 900 nm in close contact with the head of the subject, emits near-infrared light, and receives light from the light receiving sensor. To do. Since hemoglobin has a property of absorbing near-infrared light in the sensor 20, the more actively the subject's brain is active, the smaller the intensity of the received near-infrared light is, and the more active the subject's brain is. The less active, the greater the intensity of the received near-infrared light. Therefore, in this case, the first data and the second data are, for example, the hemoglobin concentration calculated based on each of the intensities of the near-infrared light received by the sensor 20 at a fixed cycle, or the hemoglobin calculated by such a method. It is a statistical value of concentration. This constant period is, for example, 1 minute. The oxygen saturation shown in FIG. 2 is also calculated based on the intensity of the near-infrared light received by the sensor 20 at regular intervals.

FIG. 3 shows the time course of oxygen saturation, oxygenated hemoglobin concentration, and deoxidized hemoglobin concentration when the subject according to the embodiment of the present invention is performing manual operation using a simulated operation device and before and after that. It is a figure which shows an example of the change. In FIG. 3, the horizontal axis represents time, the vertical axis on the right side represents oxygen saturation, and the vertical axis on the left side represents hemoglobinometry. Changes over time in oxygen saturation, oxygenated hemoglobinometry, and deoxygenated hemoglobinometry. Is indicated by a single point chain line M1, a solid line M2, and a dotted line M3.

In the manual driving using the simulated driving device referred to here, for example, the subject uses the simulated driving device, and the virtual own vehicle is driven by operating the steering wheel, accelerator, brake, etc., and the figure 8 It means to keep track of a virtual vehicle traveling 80m ahead of the course at 100km / h. Further, the manual operation using this simulated operation device is performed during the period TD shown in FIG. The length of the period TD is, for example, 30 minutes. The first 10 minutes of the period TD is an example of the first period described above. The next 20 minutes of the period TD is an example of the above-mentioned second period.

Further, immediately before the period TD, a period TR1 for the subject to rest is provided, and immediately after the period TD, a period TR2 for the subject to rest is provided. The length of the period TR1 and the length of the period TR2 are, for example, 3 minutes.

FIG. 4 shows oxygen saturation, oxygenated hemoglobinometry, and oxygen scavenging when the subject according to the embodiment of the present invention is in a vehicle in which automatic driving using a simulated driving device is being executed, and before and after that time. It is a figure which shows an example of the time-dependent change of the oxygenated hemoglobin concentration. In FIG. 4, the horizontal axis represents time, the vertical axis on the right side represents oxygen saturation, and the vertical axis on the left side represents hemoglobinometry. Changes over time in oxygen saturation, oxygenated hemoglobinometry, and deoxygenated hemoglobinometry. Is indicated by a single point chain line A1, a solid line A2, and a dotted line A3.

In the automatic driving using the simulated driving device referred to here, the simulated driving device virtually executes the automatic driving, and the subject is in the vehicle that keeps tracking the virtual vehicle traveling in front at 100 km / h. It means that you are boarding with your hands on the steering wheel. Further, the automatic operation using this simulated operation device is performed during the period TD shown in FIG. The length of the period TD is, for example, 30 minutes. The first 10 minutes of the period TD is an example of the first period described above. The next 20 minutes of the period TD is an example of the above-mentioned second period.

Further, immediately before the period TD, a period TR1 for the subject to rest is provided, and immediately after the period TD, a period TR2 for the subject to rest is provided. The length of the period TR1 and the length of the period TR2 are, for example, 3 minutes. The subject from which the data shown in FIG. 3 was collected and the subject from which the data shown in FIG. 4 was collected are the same subject.

Comparing FIG. 3 and FIG. 4, the oxygen saturation and the oxygenated hemoglobin concentration are higher as time passes when the subject is in automatic operation than when the subject is in manual operation. It can be seen that it has decreased significantly. Further, comparing FIG. 3 and FIG. 4, the oxygen scavenging hemoglobin concentration tends to be higher when the subject is automatically operated than when the subject is manually operated. I understand. The reason for this difference is that the subject's brain is more active when the subject is manually driving than when he is just in a vehicle where autonomous driving is being executed. It is thought that this is because it is.

FIG. 5 is a diagram showing an example of a case where the first data and the second data collected when the subject according to the embodiment of the present invention is performing manual operation using the simulated operation device are shown in the phase space. Is. FIG. 6 shows the first data and the second data collected when the subject according to the embodiment of the present invention is in a vehicle in which automatic driving using the simulated driving device is executed in the phase space. It is a figure which shows an example of the case. In FIGS. 5 and 6, the horizontal axis represents the oxygenated hemoglobin concentration, and the vertical axis represents the time derivative of the oxygenated hemoglobin concentration. Further, in FIGS. 5 and 6, the more the point is located at the upper right of the phase plane, the more active the brain activity of the subject is, and the more the point is located at the lower left of the phase plane. , Indicates that the subject's brain activity is inactive.

The black circles shown in FIG. 5 are points calculated from each of the hemoglobin concentrations calculated based on the near-infrared light received by the sensor 20 every minute in the first 10 minutes of the period TD shown in FIG. Indicates the position. Similarly, the white triangles shown in FIG. 5 are calculated from each of the hemoglobin concentrations calculated based on the near-infrared light received by the sensor 20 every minute in the next 10 minutes of the period TD shown in FIG. It shows the position of the point. Further, the white square shown in FIG. 5 is calculated from each hemoglobin concentration calculated based on the near infrared light received by the sensor 20 every minute in the last 10 minutes of the period TD shown in FIG. It shows the position of the point.

The black circles shown in FIG. 6 are points calculated from each of the hemoglobin concentrations calculated based on the near-infrared light received by the sensor 20 every minute in the first 10 minutes of the period TD shown in FIG. Indicates the position. Similarly, the white triangles shown in FIG. 6 are calculated from each of the hemoglobin concentrations calculated based on the near-infrared light received by the sensor 20 every minute in the next 10 minutes of the period TD shown in FIG. It shows the position of the point. The white squares shown in FIG. 6 are calculated from each of the hemoglobin concentrations calculated based on the near-infrared light received by the sensor 20 every minute in the last 10 minutes of the period TD shown in FIG. It shows the position of the point.

The centroid calculation unit 12 calculates the centroid of the first data on the phase plane in which the Mahalanobis distance is defined. For example, the centroid calculation unit 12 calculates the centroid GM of the first data based on the positions on the phase plane of each of the points represented by all 10 black circles shown in FIG. Similarly, the centroid calculation unit 12 calculates the centroid GA of the first data based on the position on the phase plane of each of the points represented by all 10 black circles shown in FIG. It is preferable that the center of gravity calculation unit 12 calculates the center of gravity GM or the center of gravity GA as soon as possible after the acquisition of the first data by the data acquisition unit 11 is completed. Alternatively, it is preferable that the center of gravity calculation unit 12 recalculates the center of gravity GM or the center of gravity GA each time the data acquisition unit 11 acquires new first data. This is because when the center of gravity GM or the center of gravity GA is calculated at an early stage, the processes executed by the distance calculation unit 13, the determination unit 14, and the output unit 15 can be executed at an early stage.

The distance calculation unit 13 calculates the Mahalanobis distance from the center of gravity for the first data and the second data. For example, the distance calculation unit 13 calculates the Mahalanobis distance from the center of gravity GM for each of the points represented by the black circles, the white triangles, and the white squares shown in FIG. Similarly, the distance calculation unit 13 calculates the Mahalanobis distance from the center of gravity GA for each of the points represented by the black circles, the white triangles, and the white squares shown in FIG. These Mahalanobis distances are indicators of the degree of arousal of the subject's brain. It is preferable that the distance calculation unit 13 calculates the Mahalanobis distance from the center of gravity of the first data and the second data as soon as possible. This is because when the Mahalanobis distance is calculated at an early stage, the processes executed by the determination unit 14 and the output unit 15 can be executed at an early stage.

Comparing FIG. 5 and FIG. 6, the position of the point calculated from the hemoglobin concentration elapses more time when the subject is performing the automatic operation than when the subject is performing the manual operation. It can be seen that there is a large tendency to move away from the center of gravity.

FIG. 7 shows an example of changes over time in the Mahalanobis distance of the first data and the Mahalanobis distance of the second data collected when the subject according to the embodiment of the present invention is performing manual operation using the simulated driving device. It is a figure which shows. FIG. 8 shows the Mahalanobis distance of the first data and the Mahalanobis distance of the second data collected when the subject according to the embodiment of the present invention is in a vehicle in which automatic driving using the simulated driving device is executed. It is a figure which shows an example of the change with time of. In FIGS. 7 and 8, the horizontal axis represents time and the vertical axis represents Mahalanobis distance.

The black circles shown in FIG. 7 represent the Mahalanobis distances of the points indicated by the black circles in FIG. 5, respectively. Similarly, the white triangles shown in FIG. 7 represent the Mahalanobis distances of the points shown by the white triangles in FIG. 5, respectively. The white squares shown in FIG. 7 represent the Mahalanobis distances of the points shown by the white squares in FIG. 5, respectively.

The black circles shown in FIG. 8 represent the Mahalanobis distances of the points indicated by the black circles in FIG. 6, respectively. Similarly, the white triangles shown in FIG. 8 represent the Mahalanobis distances of the points shown by the white triangles in FIG. 6, respectively. The white squares shown in FIG. 8 represent the Mahalanobis distances of the points shown by the white squares in FIG. 6, respectively.

The distance calculation unit 13 calculates changes in the Mahalanobis distance of the first data and the second data over time. For example, the distance calculation unit 13 shows in FIG. 7 the Mahalanobis distance of the first data and the Mahalanobis distance of the second data collected when the subject is performing manual driving using the simulated driving device in chronological order. Create a graph. Similarly, the distance calculation unit 13 sets the Mahalanobis distance of the first data and the Mahalanobis distance of the second data collected when the subject is in a vehicle in which automatic driving using the simulated driving device is executed. The graph shown in FIG. 8 is created by arranging them in a series.

As shown in FIG. 5, when the subject is manually operated, the Mahalanobis distance of the second data is about the same as the Mahalanobis distance of the first data, and does not change significantly over time. On the other hand, as shown in FIG. 6, when the subject is in a vehicle in which automatic driving is being executed, the Mahalanobis distance in the second data is longer than the Mahalanobis distance in the first data, and as time passes. It tends to increase.

The determination unit 14 determines whether or not the Mahalanobis distance of the first data and the Mahalanobis distance of the second data exceed a predetermined threshold value more than a predetermined number of times. Specifically, the determination unit 14 determines whether or not the Mahalanobis distance shown in FIG. 7 or 8 exceeds a predetermined threshold value more than a predetermined number of times. The predetermined threshold value is, for example, "40" shown by the alternate long and short dash line Th in FIGS. 7 and 8. The predetermined number of times is, for example, "3 times". In the case shown in FIG. 7, there is no Mahalanobis distance exceeding the threshold value, but in the case shown in FIG. 8, it can be seen that there are three Mahalanobis distances exceeding the threshold value. The predetermined number of times is preferably two or more times. This is because the Mahalanobis distance is accidentally lengthened, and the possibility that the determination unit 14 makes an erroneous determination can be reduced.

When it is determined that the Mahalanobis distance of the first data and the Mahalanobis distance of the second data exceed a predetermined threshold value more than a predetermined number of times, the output unit 15 outputs information indicating the activity state of the brain of the subject. For example, the output unit 15 transmits voice data, which is a source of voice according to the activity state of the brain of the subject, to the speaker 30 shown in FIG. Then, the speaker 30 receives the voice data and outputs the voice. Alternatively, the output unit 15 transmits the still image data or the moving image data that is the source of the still image or the moving image according to the activity state of the brain of the subject to the speaker 30 shown in FIG. The still image data or the moving image data is received, and the still image or the moving image is output.

Next, an example of the process executed by the brain activity state monitoring device according to the embodiment will be described with reference to FIG. FIG. 9 is a flowchart showing an example of processing executed by the brain activity state monitoring device according to the embodiment of the present invention. The brain activity state monitoring device may execute the process shown in FIG. 9 each time the first data or the second data is acquired, or the process shown in FIG. 9 may be executed by the first data or the second data. May be executed after a certain number of are acquired.

In step S10, the data acquisition unit 11 shows the activity state of the brain of the subject, shows the first data collected in the first period and the activity state of the brain of the subject, and after the first period. Acquire the second data collected in the second period that follows.

In step S20, the centroid calculation unit 12 calculates the centroid of the first data on the phase plane in which the Mahalanobis distance is defined.

In step S30, the distance calculation unit 13 calculates the Mahalanobis distance from the center of gravity calculated in step S20 for the first data and the second data, and calculates the change over time in the Mahalanobis distance of the first data and the second data. To do.

In step S40, the determination unit 14 determines whether or not the Mahalanobis distance calculated in step S30 exceeds a predetermined threshold value more than a predetermined number of times. When the determination unit 14 determines that the Mahalanobis distance calculated in step S30 exceeds a predetermined threshold value by a predetermined number of times or more (step S40: YES), the determination unit 14 proceeds to step S50. On the other hand, when the determination unit 14 determines that the Mahalanobis distance calculated in step S30 does not exceed the predetermined threshold value more than a predetermined number of times (step S40: NO), the determination unit 14 ends the process.

In step S50, the output unit 15 outputs information indicating the activity state of the brain of the subject.

The brain activity state monitoring device 1 according to the embodiment has been described above. The brain activity state monitoring device 1 calculates the center of gravity of the first data on the phase plane, and calculates the change over time in the Mahalanobis distance of the first data and the second data. Then, when it is determined that the Mahalanobis distance exceeds a predetermined threshold value more than a predetermined number of times, the brain activity state monitoring device 1 outputs information indicating the activity state of the brain of the subject. Therefore, since the brain activity state monitoring device 1 calculates the Mahalanobis distances of the first data and the second data based on the center of gravity of the first data, which is a reference for each individual subject, the brain of each individual subject It is possible to accurately determine the activity state and notify the result of the determination.

Further, the brain activity state monitoring device 1 calculates the change of the Mahalanobis distance with time not only for the second data but also for the first data, and determines whether or not the predetermined threshold value is exceeded by a predetermined number of times or more. Therefore, the brain activity state monitoring device 1 can be linked to the purpose of utilizing the data collected by the sensor 20 without waste and accurately determining and notifying the brain activity state of each individual subject.

In the above-described embodiment, the brain activity state monitoring device 1 has been described by taking as an example a scene in which the subject is in a vehicle in which automatic driving is being executed, but the present invention is not limited to this. For example, the brain activity state monitoring device 1 may be applied to a scene where the subject is listening to a lecture, a scene where the subject is participating in a biological experiment related to sleep, and the like. Even in these situations, the brain activity state monitoring device 1 can exert the above-mentioned effects.

Further, in the above-described embodiment, the case where the sensor 20 collects the first data and the second data by using the near-infrared spectroscopy has been described as an example, but the present invention is not limited thereto. For example, the sensor 20 may measure the brain wave of the subject, not the hemoglobin concentration in the blood of the brain of the subject. However, it is preferable that the sensor 20 collects data that can be measured even if the subject does not move consciously. This is because, in the above-mentioned situations, the focus is often on automatic driving, lectures, experiments, etc., and if the subject is required to perform conscious movements, the burden on the subject increases.

Further, in the above-described embodiment, the brain activity state monitoring device 1 calculates the change over time in the Mahalanobis distance not only for the second data but also for the first data, and whether or not the predetermined threshold value is exceeded a predetermined number of times or more. The case of determining whether or not is described as an example, but the present invention is not limited to this. The brain activity state monitoring device 1 may calculate the change over time of the Mahalanobis distance only for the second data, and determine whether or not the predetermined threshold value is exceeded a predetermined number of times or more.

A program for realizing each function of the brain activity state monitoring device 1 described above is recorded on a computer-readable recording medium, and the program recorded on the recording medium is read into a computer system and executed. At least a part of the above-mentioned processing may be executed.

The computer system referred to here includes at least one of hardware such as an operating system (OS: Operating System) and peripheral devices. The computer-readable recording medium includes, for example, a floppy disk, a photomagnetic disk, a ROM (Read Only Memory), a writable non-volatile memory such as a flash memory, and a portable medium such as a DVD (Digital Versatile Disc). A computer system that holds a program for a certain period of time, such as a volatile memory inside a computer system that serves as a server or client when a program is transmitted via a storage device such as a hard disk built into the computer system, a network, or a communication line. Also includes.

Further, the above-mentioned program may be transmitted from a computer system in which this program is stored in a storage device or the like to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the transmission medium for transmitting a program means a medium having a function of transmitting information, such as a network such as the Internet or a communication line such as a telephone line.

Further, the above-mentioned program may be for realizing a part of the above-mentioned functions, and is a program that can realize the above-mentioned functions in combination with a program already recorded in the computer system, a so-called difference program. There may be. The above-mentioned program is read and executed by a processor such as a CPU (Central Processing Unit) included in the computer, for example.

Although the embodiment of the present invention has been described in detail with reference to the drawings, the specific configuration is not limited to this embodiment, and various modifications, substitutions and designs are made without departing from the gist of the present invention. At least one of the changes can be made. The configurations described in each of the above-described embodiments may be combined.

1 ... Brain activity status monitoring device, 11 ... Data acquisition unit, 12 ... Center of gravity calculation unit, 13 ... Distance calculation unit, 14 ... Judgment unit, 15 ... Output unit, 20 ... Sensor, 30 ... Speaker, 40 ... Display

Claims (6)

It shows the activity state of the brain of the subject, the first data collected in the first period and the activity state of the brain of the subject, and was collected in the second period following the first period. The data acquisition unit that acquires the second data,
A center of gravity calculation unit that calculates the center of gravity of the first data on the phase plane in which the Mahalanobis distance is defined, and
A distance calculation unit that calculates the Mahalanobis distance from the center of gravity of the second data and calculates the change over time in the Mahalanobis distance of the second data.
A determination unit that determines whether or not the Mahalanobis distance of the second data exceeds a predetermined threshold value more than a predetermined number of times.
When it is determined that the Mahalanobis distance of the second data exceeds a predetermined threshold value more than a predetermined number of times, an output unit that outputs information indicating the activity state of the brain of the subject and an output unit.
A brain activity status monitoring device equipped with. The distance calculation unit further calculates the Mahalanobis distance from the center of gravity of the first data, and further calculates the change over time in the Mahalanobis distance of the first data.
The determination unit further determines whether or not the Mahalanobis distance of the first data exceeds the predetermined threshold value more than the predetermined number of times.
When it is determined that the Mahalanobis distance of the first data exceeds the predetermined threshold value more than the predetermined number of times, the output unit further outputs information indicating the activity state of the brain of the subject.
The brain activity state monitoring device according to claim 1. On the computer
It shows the activity state of the brain of the subject, the first data collected in the first period and the activity state of the brain of the subject, and was collected in the second period following the first period. Data acquisition function to acquire the second data and
A center of gravity calculation function that calculates the center of gravity of the first data on the phase plane in which the Mahalanobis distance is defined, and
A distance calculation function that calculates the Mahalanobis distance from the center of gravity of the second data and calculates the change over time in the Mahalanobis distance of the second data.
A determination function for determining whether or not the Mahalanobis distance of the second data exceeds a predetermined threshold value more than a predetermined number of times, and
When it is determined that the Mahalanobis distance of the second data exceeds a predetermined threshold value more than a predetermined number of times, an output function for outputting information indicating the activity state of the brain of the subject and an output function
Brain activity status monitoring program to realize. The distance calculation function further calculates the Mahalanobis distance from the center of gravity of the first data, and further calculates the change over time in the Mahalanobis distance of the first data.
The determination function further determines whether or not the Mahalanobis distance of the first data exceeds the predetermined threshold value more than the predetermined number of times.
When it is determined that the Mahalanobis distance of the first data exceeds the predetermined threshold value more than the predetermined number of times, the output function further outputs information indicating the activity state of the brain of the subject.
The brain activity status monitoring program according to claim 3. It shows the activity state of the brain of the subject, the first data collected in the first period and the activity state of the brain of the subject, and was collected in the second period following the first period. The data acquisition step to acquire the second data and
The center of gravity calculation step for calculating the center of gravity of the first data on the phase plane in which the Mahalanobis distance is defined, and
A distance calculation step of calculating the Mahalanobis distance from the center of gravity of the second data and calculating the change over time of the Mahalanobis distance of the second data.
A determination step for determining whether or not the Mahalanobis distance of the second data exceeds a predetermined threshold value more than a predetermined number of times, and
When it is determined that the Mahalanobis distance of the second data exceeds a predetermined threshold value more than a predetermined number of times, an output step for outputting information indicating the activity state of the brain of the subject and an output step.
Brain activity status monitoring method including. In the distance calculation step, the Mahalanobis distance from the center of gravity is further calculated for the first data, and the change over time in the Mahalanobis distance of the first data is further calculated.
In the determination step, it is further determined whether or not the Mahalanobis distance of the first data exceeds the predetermined threshold value more than the predetermined number of times.
In the output step, when it is determined that the Mahalanobis distance of the first data exceeds the predetermined threshold value more than the predetermined number of times, information indicating the activity state of the brain of the subject is further output.
The brain activity state monitoring method according to claim 5.

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