JP2011078705A - Organism fatigue evaluation device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To solve such a problem that there is not developed any objective technique yet for evaluating accumulated fatigue by a simpler and physical method that is noninvasive, easy and not required to collect specimens. <P>SOLUTION: The device includes a biosignal measuring part 101 to measure a biosignal from a measured subject, a feature quantity extracting part 102 to extract the quantity of visual sight stimulation related features from the biosignal measured by the biosignal measuring part 101, and a fatigue evaluation part 103 to evaluate whether there is left any accumulated fatigue in the subject based on the feature quantity extracted by the feature quantity extracting part 102, wherein the fatigue evaluation part 103 evaluates whether there is any accumulated fatigue left in the subject based on the feature quantity detected during or after the prescribed amount of operations done by the subject, so that an objective evaluation is possible about his/her usual accumulated fatigue by the method without being required to collect specimens. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a biological fatigue evaluation apparatus and method for evaluating a human fatigue state.

  In recent years, the importance of objectively evaluating human fatigue has been advocated by specialists and the like in the fields of cars and occupations in order to prevent death from traffic accidents or death from overwork. At this time, it is important to evaluate in real time in practice, not the conventional fatigue evaluation in the laboratory, but the conventional method is an evaluation method that is non-invasive, unconstrained, and poor in simplicity. Met.

  Therefore, as a biological fatigue assessment device aimed at practical use, a method for evaluating fatigue from pulse waves has been proposed by clarifying the relationship between the feature value obtained from human pulse wave signals and fatigue ( For example, see Patent Document 1). FIG. 12A and FIG. 12B are block diagrams showing the configuration of a conventional biological fatigue evaluation apparatus described in Patent Document 1. FIG. The apparatus described in Patent Document 1 will be described below with reference to FIGS. 12 (a) and 12 (b).

  When the pulse wave signal is measured by the pulse wave measurement unit 1201, the acceleration pulse wave calculation (calculation) unit 1202 converts the pulse wave signal into an acceleration pulse wave, extracts the waveform component of the acceleration pulse wave, and extracts the first wave (a wave) to the fifth wave. The wave height up to the wave (e wave) is calculated. Next, when the newly calculated wave height is smaller than the reference value of the pulse height of the acceleration pulse wave stored in the storage unit 1203, the evaluation unit 1204 evaluates that the user is tired. In Patent Document 1, attention is particularly paid to the a wave among the waveform components of the acceleration pulse wave, and the relationship between the decrease of the a wave wave height and the fatigue is shown as data. 12B, the pulse wave signal is measured by the pulse wave measuring unit 1205, converted into an acceleration pulse wave by the acceleration pulse wave calculating unit 1206, and then the acceleration pulse wave is chaotic by the chaos analyzing unit 1208. It also discloses analyzing and calculating the maximum Lyapunov exponent. At this time, when the maximum Lyapunov exponent newly calculated with respect to the reference value of the maximum Lyapunov exponent stored in the storage unit 1207 is small, the evaluation unit 1209 evaluates fatigue.

  Focusing on the magnetoencephalogram, which is considered to be superior in both time resolution and spatial resolution in evaluating brain activity, the driver's magnetoencephalogram is measured in an actual vehicle, and the arousal level and concentration are determined from the change in the magnetoencephalogram. A method for evaluating the degree has also been proposed (see, for example, Patent Document 2). FIG. 13 is a block diagram showing a configuration of a conventional in-vehicle biological state monitoring and control system described in Patent Document 2. As shown in FIG. Hereinafter, the system described in Patent Document 2 will be described with reference to FIG.

  When the brain activity detection device 15 detects the magnetoencephalogram of the driver 11, the arithmetic device 17 determines two or more physical states of the driver 11 from the reference data and the magnetoencephalogram stored in the storage device 18. When the determined body condition is not suitable for driving, the driver 11 is activated by the activation device 19. As a specific activation method, a method of applying high concentration oxygen from the oxygen supply machine 20 to the driver 11 is adopted.

  In addition, for objective assessment of accumulated fatigue in daily life that has not yet been pioneered, a biochemical method for analyzing the amount of virus secreted in human saliva has recently been published (for example, patent literature). 3 and Patent Document 4). Patent Document 3 and Patent Document 4 propose as a specific evaluation method that the accumulated fatigue is evaluated based on the increase or decrease in the amount of secretion of herpesvirus 6 or 7 in saliva.

Japanese Patent No. 3790266 Japanese Patent Laid-Open No. 2008-6007 Japanese Patent No. 4218842 JP 2007-330263 A

Hiroaki Tanaka and two others, “Clinical field and developed magnetoencephalographic analysis technology”, Biomedical Engineering, April 2009, 47, 2, p. 125-130

  However, the conventional configurations in Patent Document 1 and Patent Document 2 are intended for evaluation of acute changes in the user's relatively short time (several hours), and the subacute accumulation accumulated in actual daily life. It was difficult to use as an application for evaluating fatigue (fatigue lasting for about one week to one month). Therefore, a technique for evaluating accumulated fatigue in daily life that can prevent overwork and accidents has been required.

  On the other hand, although methods in Patent Literature 3 and Patent Literature 4 have been proposed as methods for objectively evaluating accumulated fatigue in daily life, these are objective assessment techniques for accumulated fatigue using biochemical methods. Therefore, it was a time-consuming method for evaluation. The objective assessment technique of accumulated fatigue by a simpler method that does not require sample collection has not been developed yet.

  SUMMARY OF THE INVENTION The present invention solves the above-described conventional problems, and an object thereof is to provide a biological fatigue evaluation apparatus or method for objectively evaluating accumulated fatigue without requiring sample collection.

  In order to solve the above conventional problems, the biological fatigue evaluation apparatus of the present invention is characterized in that a biological signal measuring unit that measures a biological signal of a subject and a feature amount that is related to a visual stimulus are extracted from the measured biological signal. A quantity extraction unit; and a fatigue evaluation unit that evaluates the presence or absence of accumulated fatigue in the subject based on the extracted feature quantity. The biological signal measuring unit measures the biological signal and evaluates the presence or absence of accumulated fatigue after the subject performs an operation that becomes a mental fatigue load.

  With this configuration, it is possible to provide a biological fatigue evaluation apparatus that can objectively evaluate fatigue accumulated on a daily basis by a method that does not require sample collection.

  The biological fatigue evaluation apparatus of the present invention measures an electrical signal or a magnetic signal indicating a brain function as a biological signal, and the feature amount extraction unit extracts an event-related signal induced by a visual stimulus from the biological signal. The fatigue evaluation unit may evaluate the presence or absence of accumulated fatigue based on the intensity of the event-related signal.

  With this configuration, a biological fatigue assessment device that can objectively evaluate fatigue accumulated on a daily basis simply by bringing the biological signal measurement unit into contact with the living body by a method that does not require sample collection such as magnetoencephalogram or electroencephalogram. Can be provided.

  Further, in the biological fatigue assessment device of the present invention, when the feature amount extraction unit is a task that uses a working memory in the brain, the feature amount extraction unit is related to an event in a predetermined time interval after 100 msec or more after visual stimulation. The signal may be extracted as a feature amount, and the fatigue evaluation unit may evaluate that accumulated fatigue exists when the average intensity of the event-related signal in a predetermined time interval exceeds a preset threshold.

  With this configuration, it is possible to provide a living body fatigue evaluation apparatus that can easily and objectively evaluate the fatigue that accumulates on a daily basis after the work of a subject who is performing difficult work or between work. . As a result, business owners and managers can objectively understand the performance of workers and use it for management, and workers can also grasp the degree of their daily fatigue accumulation. Can be used for health management.

  Further, in the biological fatigue assessment device of the present invention, when the work performed by the subject is a work that does not use a working memory in the brain, 145 msec after the visual stimulus elapses from immediately after the visual stimulus. The event-related signal in the predetermined time interval until the previous time is extracted as a feature amount, and the fatigue evaluation unit evaluates that accumulated fatigue exists when the average intensity of the event-related signal in the predetermined time interval exceeds a preset threshold value It may be a configuration.

  With this configuration, it is possible to provide a living body fatigue evaluation apparatus that can easily and objectively evaluate the fatigue that accumulates on a daily basis after the work of a worker who performs monotonous work or between work. . As a result, business owners and managers can objectively understand the performance of workers and use it for management, and workers can also grasp the degree of their daily fatigue accumulation. Can be used for health management.

  The biological fatigue evaluation apparatus of the present invention further includes a stimulus output unit that gives a visual stimulus to the subject, and the feature amount extraction unit extracts a feature amount related to the visual stimulus by the stimulus output unit from the biological signal. It may be.

  With this configuration, it is possible to automatically give a visual stimulus during or after a worker's work, and a more convenient biological fatigue evaluation apparatus can be provided.

  In the biological fatigue assessment apparatus of the present invention, the stimulus output unit may output blinking light having a frequency in the δ wave band or the β wave band.

  With this configuration, an appropriate visual stimulus can be automatically given to the subject, and objective assessment of fatigue accumulated on a daily basis can be realized with higher accuracy.

  The biological fatigue assessment apparatus of the present invention further includes a work execution unit that causes the subject to perform a work that uses a working memory in the brain or a work that does not use a working memory in the brain. The configuration may be such that the biological signal of the subject is measured after the work is executed by the work execution unit.

  With this configuration, it becomes possible to automatically perform difficult tasks or monotonous tasks for the target person, and can be easily introduced as a testing device even in the medical or medical check-up, and can be used for primary screening of diseases. It can be applied to the intended test or a regular test in the course after the disease.

  Moreover, the structure which further includes the apparatus control part which controls an external apparatus based on the result evaluated by the fatigue evaluation part may be sufficient as the biological fatigue evaluation apparatus of this invention.

  With this configuration, it is possible to present the evaluation result of fatigue that is routinely accumulated in the subject, or to automatically perform care based on the evaluation result.

  Moreover, the structure which further includes the memory | storage part which memorize | stores the result evaluated by the fatigue evaluation part may be sufficient as the biological fatigue evaluation apparatus of this invention.

  With this configuration, it is possible to record the evaluation results of fatigue accumulated on a daily basis by the subject over a long period of time.

  In order to solve the above-described problem, the biological fatigue evaluation method of the present invention includes a biological signal measuring step for measuring a biological signal of a subject, and a feature for extracting a feature amount related to a visual stimulus from the measured biological signal. A quantity extraction step, and a fatigue evaluation step for evaluating the presence or absence of accumulated fatigue in the subject based on the extracted feature quantity. In the biological signal measurement step, the biological signal is measured after the subject performs a predetermined work.

  With this configuration, it is possible to objectively evaluate fatigue accumulated on a daily basis by a method that does not require specimen collection.

  According to the biological fatigue evaluation apparatus of the present invention, it is possible to provide a biological fatigue evaluation apparatus that can objectively evaluate daily accumulated fatigue without collecting a specimen.

It is a block diagram which shows the structure of the biological fatigue evaluation apparatus in Embodiment 1 of this invention. It is a flowchart which shows the process of the biological fatigue evaluation apparatus in Embodiment 1 in the case of the operation | work which the user is implementing difficult. It is a flowchart which shows the process of the biological fatigue evaluation apparatus in Embodiment 1 in case the operation | work which the user is implementing is a monotonous operation. It is a block diagram which shows the structure of the biological fatigue evaluation apparatus of Embodiment 2 of this invention. It is a flowchart which shows the process in the biological fatigue evaluation apparatus of Embodiment 2 of this invention when the work program run by the work execution part is a difficult work program which forces a difficult work. It is a flowchart which shows the process in the biological fatigue evaluation apparatus of Embodiment 2 of this invention when the work program run by the work execution part is a monotonous work program which forces a monotonous work. It is a graph which shows the results change of ATMT before and after mental fatigue load. (A) is a figure which shows the subjective report score before and behind mental fatigue load, and (b) shows the subjective report score at the time of N-back test recorded at the end of a test, respectively. It is a correlation diagram of the reaction intensity | strength of VEF before and after implementation of a task, and a Chalder's fatigue scale score. It is a correlation diagram of the reaction intensity | strength of VEF before and after implementation of a task, and a Chalder's fatigue scale score. It is a correlation diagram of the reaction intensity | strength of VEF before and after implementation of a task, and a Chalder's fatigue scale score. It is a block diagram which shows the structure of the conventional biological fatigue evaluation apparatus by (a), respectively, and the structure of the conventional biological fatigue evaluation apparatus by (b). It is a block diagram which shows the structure of the conventional in-vehicle biological condition monitoring and control system.

  Embodiments of the present invention will be described below with reference to the drawings.

(Embodiment 1)
FIG. 1 is a block diagram showing the configuration of the biological fatigue evaluation apparatus in Embodiment 1 of the present invention. As shown in FIG. 1, the biological fatigue evaluation apparatus according to Embodiment 1 of the present invention includes a biological signal measurement unit 101 that measures a biological signal, a feature amount extraction unit 102 that extracts a feature amount from the biological signal, and a feature amount. Are provided with a fatigue evaluation unit 103 that evaluates accumulated fatigue, a stimulus output unit 104 that outputs a stimulus to the user, and a device control unit 105 that controls the device based on the fatigue evaluation result.

  The biological signal measuring unit 101 is a biological sensor that measures a brain function such as an electroencephalogram or a magnetoencephalogram. When acquiring the amount of bioelectricity such as an electroencephalogram, a typical method is to attach a plurality of electrodes to the surface of the living body and derive it as an electrical signal outside the body. When acquiring a biomagnetism quantity such as a magnetoencephalogram, a fluxgate magnetometer or a more sensitive SQUID (Superducting Quantum Interference Device) magnetometer is used to measure a weak magnetic flux density. Used. In the biological fatigue evaluation apparatus according to Embodiment 1 of the present invention, a case where a magnetoencephalogram is measured by the biological signal measurement unit 101 will be described below.

  A magnetoencephalogram is a weak magnetic field in which a current that flows along with the excitatory post-synaptic potential of pyramidal cells present in the cerebral cortex is generated. By measuring the magnetoencephalogram, the function of the brain can be observed non-invasively as in the case of a device such as a conventional electroencephalograph or fMRI (Functional Magnetic Resonance Imaging). The greatest feature of the magnetoencephalogram measuring apparatus is that it has both a high temporal resolution in milliseconds and a high spatial resolution in millimeters. In recent years, it has been rapidly spreading mainly in the medical field. There are many large-scale magnetoencephalography measuring devices that are currently in widespread use, such as SQUID magnetometers that require cooling with liquid helium or liquid nitrogen. Thin-film magnetic field sensors are also being developed, and the world in which magnetoencephalograms can be measured in an everyday scene is not far away due to technological advances.

  Currently, the equivalent current dipole method (ECD) and the spatial filter method are often used as methods for expressing the signals obtained from the magnetoencephalogram measuring apparatus. The former is a method of performing estimation by repeating fitting of a forward problem and a measurement magnetic field, assuming a single current dipole as a signal source. It is most frequently applied in clinical practice as mapping of brain functions with high positional accuracy by superimposing results on anatomical images such as MRI using a coordinate transformation matrix and quantitative evaluation of brain activity. However, this method requires a lot of human intervention, such as the necessity to set the number of dipoles in advance, and the analysis takes time, and the objectivity is sometimes lacking. On the other hand, the latter method has recently attracted attention as a method that can be analyzed without being conscious of the magnetic field pattern and the number of signal sources as described above, and the brain activity of voxels set in the brain was measured by each sensor. This is a technique expressed by weighted linear combination of signals. The spatial filter method is further divided into non-adaptive and adaptive, which means whether information on the time change of the signal source is taken in (Adaptive) or not (Non-adaptive). If separation of nearby signal sources is not particularly required, a non-adaptive method may be selected. Among them, sLORETA-qm (standardized low resolution electrical magnetic) recently developed by Tanaka et al. (See Non-Patent Document 1). A technique called tomography modified for a quantifiable method is becoming widespread. The sLORETA-qm method is a method that picks up only the voxels that take the maximum value or maximum value of spatial intensity and converts them into a quantitative value based on the idea that the spatial filter analysis results cannot originally capture the spread. It is. As a result, it has become possible to make comparisons between individuals that have traditionally been limited to expressing relative changes within individuals. Therefore, when the sLORETA-qm method is used for magnetoencephalogram signal analysis, if there is little need to classify nearby signal sources, human intervention is unnecessary and the magnetic field activity in the brain is used as a quantitative value. Since it can be output, it is sufficiently possible to automatically realize a series of processes such as measuring a magnetoencephalogram as an input signal, analyzing the signal and outputting the result, using a computer or the like.

  This time, the present inventors conducted a possibility verification experiment on non-invasive evaluation of biological fatigue conducted independently, and visually induced magnetic field of magnetoencephalogram by 1 Hz or 16 Hz red flashing light stimulation after subject was given mental fatigue load. (Visual Evoked Magnetic Fields, abbreviated as VEF) In the analysis, the reaction intensity between 70 msec and 210 msec after blinking stimulation obtained by the sLORETA-qm method and the intensity of chronic fatigue in subjects who were collected before mental fatigue loading It was found that there was a positive correlation with the score of the indicated Chalder's fatigue scale. Specifically, when the subject is made to perform a relatively difficult task using the working memory in the brain as a mental fatigue load, the reaction intensity of VEF and the score of Chalder's fatigue scale between 130 and 210 msec after the blinking stimulus and On the other hand, when a relatively monotonous work that does not use the working memory in the brain is used as a mental load, the reaction intensity of VEF between 70 msec and 130 msec after flashing stimulation and Chalder's fatigue It was found that there was a positive correlation with the score of the scale. The possibility verification experiment regarding the non-invasive evaluation of biological fatigue conducted by the present inventors will be described in detail later. As will be described later in the experimental contents, the above 130 msec and 210 msec are not limited to these values. In view of the characteristics of the brain signal induced by the visual stimulus, the value 130 described above may be a value of 100 or more and less than 145. Also, the value 210 above may be 145 or more and less than 330.

  The details will be described below assuming that a user who is forced to perform a difficult task or a monotonous task that is a mental fatigue load at a work site or the like uses the biological fatigue assessment device.

  In the living body fatigue evaluation apparatus according to the present embodiment, the stimulus output unit 104 is an actuator that outputs a visual stimulus, and blinking light having a frequency of δ wave band (3 Hz or less) or β wave band (13 Hz to 25 Hz). Has a function of outputting. The stimulus output unit 104 gives a visual stimulus to the subject by blinking light having a frequency of δ wave band and blinking light having a frequency of β wave band. Specifically, it is preferable to output red flashing light of 1 Hz or 16 Hz, which is often used in clinical experiments in the medical field, as the frequency of the σ wave band or β wave band, respectively.

  When the work performed by the user is difficult, the feature amount extraction unit 102 uses the sLORETA-qm method to output the visual output from the magnetoencephalogram measured by the biological signal measurement unit 101. When the response intensity of VEF between 130 msec and 210 msec after stimulation is extracted as a feature quantity, and the work performed by the user is a monotonous work, the sLORETA-qm method is obtained from the magnetoencephalogram measured by the biological signal measurement unit 101. Thus, the reaction intensity of VEF between 70 msec and 130 msec after visual stimulation output by the stimulus output unit 104 is extracted as a feature amount. The extracted feature amount is output to the fatigue evaluation unit 103. Note that the 130 msec VEF may be extracted as a feature value, whether it is a complex work or a monotonous work, or only in one of the work. May be.

  The fatigue evaluation unit 103 compares the average value of the VEF reaction intensity extracted by the feature amount extraction unit 102 with a previously held threshold value, and the VEF reaction intensity extracted by the feature amount extraction unit 102 is greater than the threshold value. When it is large, it is evaluated that accumulated fatigue exists. A specific example of the threshold value used at this time is a numerical value of 2.5 nA · m (hereinafter referred to as a threshold value L1), for example, in the case where the work performed by the user is difficult. On the other hand, when the work performed by the user is a monotonous work, the value is, for example, 5.0 nA · m (hereinafter, threshold L2). In addition, although the specific numerical value of the threshold value L1 and the threshold value L2 used here is a numerical value extracted based on the result of the possibility verification experiment regarding the non-invasive evaluation of living body fatigue which this inventor implemented, it is limited to this Is not to be done. The details of the verification experiment and the extraction of the threshold based on the result will be described later. The threshold L1 is desirably set to 2.5 nA · m to 3.3 nA · m, and the threshold L2 is set to 4.5 nA · m. It is desirable to set to m or more and 6.0 nA · m or less.

  The device control unit 105 controls the device based on the accumulated fatigue evaluation result output by the fatigue evaluation unit 103. For example, the fatigue evaluation result may be reported to the user by controlling a display with a display function or a speaker that outputs sound, or a stimulus such as fragrance, airflow, or heat that is effective in restoring or reducing fatigue is output. May be. Alternatively, the evaluation results output by the fatigue evaluation unit 103 may be stored and accumulated, or may be notified to a department that supervises and supervises the user.

  FIG. 2 is a flowchart showing the process of the biological fatigue evaluation apparatus according to the present embodiment in the case where the work performed by the user is difficult.

  As shown in FIG. 2, in the biological fatigue evaluation apparatus according to the present embodiment, the user's magnetoencephalogram is measured by the biological signal measuring unit 101 during or after the user's difficult work (step S <b> 21). When a 1 Hz red flashing light stimulus is output by the visual stimulation unit (stimulation output unit) 104 (step S22), the magnetoencephalogram measured by the biological signal measurement unit 101 by the feature amount extraction unit 102 is obtained by the sLORETA-qm method. The reaction intensity of VEF between 130 msec and 210 msec after the blinking stimulus is extracted and output (step S23). In the fatigue evaluation unit 103, when the VEF reaction intensity is output from the feature amount extraction unit 102, the threshold value L1 held in advance is compared with the magnitude (step S24). If the reaction intensity of VEF output from the feature quantity extraction unit 102 is greater than the threshold L1 (Yes in step S24), it is evaluated that accumulated fatigue exists, and the evaluation result is output to the device control unit 105 (step S25). The device control unit 105 notifies the user of the evaluation result based on the evaluation result output from the fatigue evaluation unit 103 (step S26). If the VEF reaction intensity output from the feature quantity extraction unit 102 is smaller than the threshold L1 (No in step S24), the process waits until the next time the VEF reaction intensity is output from the feature quantity extraction unit 102 (step S23).

  On the other hand, FIG. 3 is a flowchart showing a process of the biological fatigue evaluation apparatus in the present embodiment when the work performed by the user is a monotonous work.

  As shown in FIG. 3, in the biological fatigue evaluation apparatus according to the present embodiment, the user's magnetoencephalogram is measured by the biological signal measuring unit 101 during or after the user's monotonous work (step S <b> 31). When a 1 Hz red flashing light stimulus is output by the stimulus output unit 104 (step S32), from the magnetoencephalogram measured by the biometric signal measurement unit 101 by the feature amount extraction unit 102 by the sLORETA-qm method from 70 msec after the flashing stimulus. The reaction intensity of VEF for 130 msec is extracted and output (step S33). When the FEF reaction intensity is output from the feature amount extraction unit 102 in the fatigue evaluation unit 103, the threshold value L2 held in advance is compared with the magnitude (step S34). If the reaction intensity of VEF output from the feature quantity extraction unit 102 is greater than the threshold value L2 (Yes in step S34), it is evaluated that accumulated fatigue exists, and the evaluation result is output to the device control unit 105 (step S35). The device control unit 105 notifies the user of the evaluation result based on the evaluation result output from the fatigue evaluation unit 103 (step S36). If the VEF reaction intensity output from the feature quantity extraction unit 102 is smaller than the threshold L2 (No in step S34), the process waits until the next time the VEF reaction intensity is output from the feature quantity extraction unit 102 (step S33).

  According to this configuration, during or after the user's work, the biological signal measurement unit 101 measures the magnetoencephalogram of the user, the stimulus output unit 104 gives a visual stimulus to the user, and the feature amount extraction unit 102 receives the visual stimulus. By extracting the reaction intensity of VEF, the fatigue evaluation unit 103 evaluates accumulated fatigue based on the reaction intensity of VEF extracted by the feature amount extraction unit 102, so that during or after the user's work in the workplace such as labor, It is possible to provide a living body fatigue evaluation apparatus that can objectively evaluate fatigue accumulated on a daily basis by a simple method that does not require sample collection. As a result, business owners and managers can objectively understand the performance of workers and use it for management, and workers can also grasp the degree of their daily fatigue accumulation. Can be used for health management.

  In addition, although the biological fatigue evaluation apparatus in this Embodiment was demonstrated as a structure provided with the stimulus output part 104, what is necessary is just to give irritation | stimulation using an external apparatus and can also implement | achieve even the structure which does not hold | maintain the stimulus output part 104 itself. .

  In addition, although the biological fatigue evaluation apparatus in this Embodiment was demonstrated as a structure provided with the apparatus control part 105, what is necessary is just to control by an external structure and the structure which does not hold | maintain the apparatus control part 105 itself is realizable.

  In the biological fatigue evaluation apparatus according to the present embodiment, the biological signal measurement unit 101 measures the magnetoencephalogram, and the feature amount extraction unit 102 extracts the VEF response intensity after visual stimulation from the magnetoencephalogram, but the present invention is not limited thereto. Alternatively, the biological signal measuring unit 101 measures the electroencephalogram, and the feature amount extraction unit 102 extracts the reaction intensity of the event-related potential that is a voltage value induced from the visual stimulus after the visual stimulus from the electroencephalogram.

(Embodiment 2)
FIG. 4 is a block diagram showing a configuration of the biological fatigue evaluation apparatus according to the second embodiment of the present invention. 4, the same components as those in FIG. 1 are denoted by the same reference numerals, and the description thereof is omitted.

  As shown in FIG. 4, the biological fatigue evaluation apparatus according to the second embodiment of the present invention includes a biological signal measurement unit 101, a feature amount extraction unit 102, a fatigue evaluation unit 103, and a stimulus output unit 104 according to the first embodiment. In addition to the device control unit 105, a work execution unit 401 that executes a work program, and a storage unit 402 that accumulates fatigue evaluation results.

  Therefore, in the present embodiment, it is assumed that a biological fatigue assessment device equipped with a program that forces a user to perform a difficult task or a monotonous task that causes a mental fatigue load in a medical or labor site. Details will be described below.

  The operations in the biological signal measurement unit 101, the feature amount extraction unit 102, the fatigue evaluation unit 103, the stimulus output unit 104, and the device control unit 105 are performed in the same manner as in the first embodiment. As in the first embodiment, the device control unit 105 is not an essential configuration.

  The work execution unit 401 executes a work program that gives a task to the user. As a work program, for example, at least one kind of program such as content forcing relatively difficult work using the working memory in the brain, or content forcing relatively monotonous work without using the working memory in the brain. Execute. As a specific example, as a program for forcing a difficult task, numbers and symbols are presented at regular intervals, and it is determined whether the presented numbers and symbols are the same as the numbers and symbols presented two times before. -A test called "back test" is installed, and as a program forcing monotonous work, numbers and symbols are presented at regular intervals, and the presented numbers and symbols are announced in advance. It is desirable that a test called a 0-back test for determining whether they are the same is installed. An interactive program in which a user inputs an answer each time using a PC input interface device such as a mouse, and the program side presents whether the answer is correct or incorrect. Is desirable. It is desirable that the work program is continuously executed for at least several tens of minutes, for example, 20 minutes.

  The storage unit 402 is a storage medium that accumulates evaluation results in time series by the fatigue evaluation unit 103.

  FIG. 5 is a flowchart showing processing in the biological fatigue evaluation apparatus according to the second embodiment of the present invention when the work program executed by the work execution unit 401 is a difficult work program forcing a difficult work.

  As shown in FIG. 5, when the difficult task program is executed in the task execution unit 401 (step S51), the biosignal measuring unit 101 measures the user's magnetoencephalogram (step S52). When the work program executed by the work execution unit 401 ends, the stimulus output unit 104 outputs a visual stimulus (step S53). When a 1 Hz red flashing light stimulus is output by the stimulus output unit 104, a VEF between 130 msec and 210 msec after the flashing stimulus is generated from the magnetoencephalogram measured by the biometric signal measurement unit 101 by the feature amount extraction unit 102 by the sLORETA-qm method. Are extracted and output (step S54). When the FEF reaction intensity is output from the feature amount extraction unit 102 in the fatigue evaluation unit 103, the threshold value L1 held in advance is compared with the magnitude (step S55). If the reaction intensity of the VEF output from the feature amount extraction unit 102 is greater than the threshold L1 (Yes in step S55), it is evaluated that accumulated fatigue exists, and the evaluation results are output to the storage unit 402 and the device control unit 105, respectively ( Step S56). The storage unit 402 stores the evaluation results output from the fatigue evaluation result (fatigue evaluation unit) 103 in time series (step S57). The appliance control unit 105 notifies the user of the evaluation result output from the fatigue evaluation unit 103 (step S58). If the reaction intensity of VEF output from the feature quantity extraction unit 102 is smaller than the threshold value L1 (No in step S55), the evaluation result indicating no accumulated fatigue is output to the storage unit 402. (Step S57).

  On the other hand, FIG. 6 is a flowchart showing processing in the biological fatigue evaluation apparatus according to the second embodiment of the present invention when the work program executed by the work execution unit 401 is a monotonous work program forcing monotonous work. .

  As shown in FIG. 6, when the monotonous work program is executed in the work execution unit 401 (step S61), the biosignal measurement unit 101 measures the user's magnetoencephalogram (step S62). When the work program executed by the work execution unit 401 ends, the stimulus output unit 104 outputs a visual stimulus (step S63). When a 1 Hz red flashing light stimulus is output by the stimulus output unit 104, a VEF between 70 msec and 130 msec after the flashing stimulus is obtained from the magnetoencephalogram measured by the biometric signal measurement unit 101 by the feature amount extraction unit 102 by the sLORETA-qm method. Are extracted and output (step S64). In the fatigue evaluation unit 103, when the reaction intensity of VEF is output from the feature amount extraction unit 102, the threshold value L2 held in advance is compared with the magnitude (step S65). If the reaction intensity of VEF output from the feature quantity extraction unit 102 is greater than the threshold value L2 (Yes in step S65), it is evaluated that accumulated fatigue exists, and the evaluation results are output to the storage unit 402 and the device control unit 105, respectively ( Step S66). The storage unit 402 stores the evaluation results output from the fatigue evaluation unit 103 in time series (step S67). The appliance control unit 105 notifies the user of the evaluation result output from the fatigue evaluation unit 103 (step S68). If the reaction intensity of VEF output from the feature quantity extraction unit 102 is smaller than the threshold value L2 (No in step S65), the evaluation result without accumulated fatigue is output to the storage unit 402. (Step S67).

  According to such a configuration, the work execution unit 401 executes a work program for the user, the biological signal measurement unit 101 measures the user's magnetoencephalogram, the stimulus output unit 104 gives a visual stimulus to the user, and the feature amount extraction unit 102 extracts the VEF reaction intensity after visual stimulation, the fatigue evaluation unit 103 evaluates accumulated fatigue based on the VEF reaction intensity extracted by the feature amount extraction unit 102, and stores the evaluation result in the storage unit 402. The device control unit 105 notifies the user of the evaluation result output from the fatigue evaluation unit 103, so that the fatigue accumulated on a daily basis by executing the work program for the user in the field of medical care or labor is objectively observed. It can be realized as an inspection device to be evaluated, and as a device that supports recovery by device control based on the evaluation result, and it can be easily introduced on site. Examination for the purpose of primary screening of the disease, or it is possible to apply a periodic inspection or the like for keeping track of the illness of the patient.

  In the biological fatigue evaluation apparatus according to the present embodiment, the fatigue evaluation unit 103 compares the VEF reaction intensity output from the feature amount extraction unit 102 with the threshold value L1 or L2 held in advance, thereby accumulating fatigue. However, the present invention is not limited to this, the VEF reaction intensity used in the previous evaluation stored in the storage unit 402 is compared with the VEF reaction intensity output from the current feature amount extraction unit 102, and When the reaction intensity of the VEF output from the feature amount extraction unit 102 this time is large, it may be evaluated that accumulated fatigue exists.

  In the first and second embodiments described above, the present inventors conducted a subject experiment for the purpose of verifying the feasibility of assessing non-invasive living body fatigue. There is a positive correlation between the response intensity of visual evoked magnetic field (VEF) by visual stimulation in the magnetoencephalogram and the score of Chalder's fatigue scale indicating the intensity of chronic fatigue in the state of fatigue due to work. This is based on the finding. Hereinafter, the present invention will be described in more detail based on examples, but the present invention is not limited to these examples.

<Validity verification of mental fatigue load>
(1) Test design The present inventors used 20 healthy adults (male, age 32.0 ± 10.2 years (mean ± standard deviation)) as subjects, and two types of N using a personal computer (PC). -A mental fatigue load was applied by performing a back test for 30 minutes, and performance evaluation (measurement of the total number of trials and errors during task execution) was performed for 30 minutes before and after that, respectively, by advanced trail making test (ATMT). Subjective tests were conducted before and after the ATMT, and the contents included visual fatigue scale (VAS), overall fatigue, mental fatigue, physical fatigue, stress, motivation, drowsiness, difficulty, monotony, Boredness was measured with a Karolinska sleepness scale (KSS). Two types of tests were performed at the crossover, and the influence of the order of the tests was excluded.

(2) Mental fatigue loading method Among the N-back tests, 0-back test and 2-back test were adopted. The 0-back test is a test that makes a subject judge whether or not a designated number, character, or symbol is displayed without using a working memory, and imposes monotonous work. The present inventors assumed that fatigue was caused by monotonous work on the subject by carrying out this continuously for 30 minutes. Specifically, when a specified number, character, or symbol is displayed on the PC screen, the PC mouse is right-clicked, and if not, the PC mouse is left-clicked. . On the other hand, the 2-back test is a test that uses a working memory and allows the subject to determine whether the currently displayed number, character, or symbol is the same as the last displayed number, character, or symbol. It is a difficult task. The present inventors assumed that the fatigue caused by difficult work was caused to the subject by carrying out this continuously for 30 minutes. Specifically, if the number, character, or symbol displayed on the PC screen is the same as the number, character, or symbol displayed two times before, right-clicking on the PC mouse, otherwise PC It asks you to perform a left mouse click. The display time of numbers, characters or symbols was 0.5 sec, and the display timing from the disappearance of the display of numbers, characters or symbols to the next display was 2.5 sec.

(3) Results In order to determine whether or not fatigue is induced by performing the N-back test for 30 minutes, looking at the results of ATMT before and after mental fatigue, the 0-back test group and 2- In the back test group, a significant increase in the number of errors was observed (Fig. 7. In addition, it was previously confirmed that there was no change in the number of errors in the ATMT before and after the 30-minute relaxation task. ) Furthermore, looking at the results of overall fatigue and mental fatigue VAS scores before and after mental fatigue loading, a significant increase was observed in both the 0-back test implementation group and the 2-back test implementation group (FIG. 8). (A)). Therefore, a decrease in mental performance and an increase in fatigue were shown by performing a 30-minute N-back test, and this test (30-minute N-back test) was determined to be appropriate as a fatigue test. Moreover, in the subjective test at the time of performing the N-back test recorded at the end of the test, the 2-back test group showed significantly higher mental fatigue and difficulty VAS score than the 0-back test group. On the other hand, monotonicity and boredom VAS and KSS scores were significantly higher in the 0-back test implementation group than in the 2-back test implementation group (FIG. 8B).

  This means that the 30-minute 0-back test is a "monotonous, tedious, low-load problem" and the 30-minute 2-back test is a "difficult, high-load problem" Show.

  From the above, the 30-minute 0-back test is appropriate as “a problem that causes fatigue due to monotonous and light-load work”, and at the same time, the 30-minute 2-back test is “difficult and heavy-load work” It was thought that it was appropriate as “a task that causes fatigue by

<Verification of possibility of noninvasive fatigue assessment>
(1) Test design The present inventors used 10 healthy adults (male, age 30.8 ± 9.4 years (mean ± standard deviation)) as subjects in Example 1, “monotonous and light work” Tasks that cause mental fatigue: 0-back test proved appropriate as “problems that cause fatigue due to stress” and 2-back test proved appropriate as “issues that cause fatigue due to difficult and heavy work” Each for 30 minutes. As a specific flow of the test, a resting test, a visual stimulus test, and an auditory stimulus test were performed as a pre-task test. First, as a resting test, the patient was rested for 2 minutes in the open eye state, and then rested for 1 minute in the closed eye state. Next, as a visual stimulus test, a light stimulus was applied to the left half visual field by blinking of a red light emitting diode. Stimulation was tried twice a minute, and a blinking stimulus of 1 Hz was used for the first time and 16 Hz for the second time. Next, as an auditory stimulation test, a tone burst stimulation (1000 Hz, 90 dB) was used, and stimulation was applied to the right ear for the first time for about 4 minutes and to the left ear for the second time. After completion of the auditory stimulation test, a 0-back test and a 2-back test were performed for 30 minutes. After the N-back test, an inspection after the task was performed. The post-task inspection was the same as the pre-task inspection, but was performed in the order of rest test, auditory stimulus test, and visual stimulus test. Then, during the period from the rest test before the task execution to the visual stimulus test after the task execution, the electroencephalogram (EEG) and magnetoencephalogram (MEG) were measured continuously. Subjective tests are conducted before and after the task, and overall fatigue scale, mental fatigue, physical fatigue, stress, motivation, drowsiness, difficulty, monotony, and boredom are achieved through Visual analog scale (VAS). Drowsiness was measured by Karolinska sleepness scale (KSS). Furthermore, in order to investigate the chronic fatigue condition in the test subjects, the fatigue strength was measured only by the first day of the two kinds of test days before the start of the test by means of Chalder's fatigue scale. In addition, two types of tests were conducted at the crossover, and the influence due to the order of the tests was excluded.

(2) Observation items MEG examination: A 160-channel helmet type magnetoencephalograph (MEG vision) (manufactured by Yokogawa Electric Corporation) was used for measurement. From this, the magnetic field activity was measured by the MEG apparatus, and visual evoked magnetic field (VEF) analysis by the sLORETA-qm method was performed.

  For comparison between the two groups, Paired t-test was performed. For the correlation between the two groups, Pearson's correlation analysis was performed. A P value of less than 0.05 was determined to be statistically significant.

(3) Results In the subjective data after the N-back test, the 0-back test group showed significantly higher drowsiness, monotony, and bored VAS scores than the 2-back test group. The back test group tended to show significantly higher VAS scores for stress and difficulty compared to the 0-back test group. These results were almost the same as the results of Example 1, and were considered to guarantee the reliability and validity of this test.

  In VEF analysis with 1 Hz or 16 Hz red flashing light stimulation in MEG, the reaction intensity between 70 msec and 330 msec after stimulation determined by sLORETA-qm method and the score of Chalder's fatigue scale that was investigated before the test was conducted The correlation was analyzed. The reason for analyzing the reaction intensity at the time interval in this experiment is that a signal induced by the visual stimulus is likely to occur in the brain signal after about 70 msec from the visual stimulus. Further, when the experimental data was observed, the signal induced by the visual stimulus was generated until about 330 msec after the stimulus.

  When a 1 Hz red flashing light stimulus was applied, in the 2-back test group, there was a correlation between the reaction intensity between 130 msec and 210 msec after the red flashing light stimulus before the task was performed and the score of the Chalder's fatigue scale. There wasn't. On the other hand, a positive correlation was observed between the reaction intensity between 130 msec and 210 msec after stimulation of the red flashing light after the task was implemented, and the score of the Chalder's fatigue scale (FIG. 9). Similarly, when a 1 Hz red flashing light stimulus is given, in the 0-back test group, there is a correlation between the reaction intensity between 70 msec and 130 msec after the red flashing stimulus before the task is performed and the score of the Chalder's fatigue scale. I couldn't. On the other hand, a positive correlation was found between the reaction intensity between 70 msec and 130 msec after the red light stimulation after the task was performed, and the score of the Chalder's fatigue scale (FIG. 10).

  When a 16 Hz red flashing light stimulus was applied, in the 2-back test group, there was a correlation between the reaction intensity between 130 msec and 210 msec after the red flashing light stimulus before the task was performed and the score of the Chalder's fatigue scale. There wasn't. However, a positive correlation was found between the reaction intensity between 130 msec and 210 msec after stimulation of the red flashing light after the task was implemented, and the score of the Chalder's fatigue scale (FIG. 11). Similarly, when a 16 Hz red flashing light stimulus was applied, no significant correlation was observed in the 0-back test implementation group both before and after the implementation of the task.

  Note that the reason why the reaction intensity between 70 msec to 130 msec and 130 msec to 210 msec was analyzed in particular is that experimental data were observed to have a difference in the interval. However, the numerical values 130 and 210 are values set for convenience in the analysis, and are not limited to these numerical values.

  In view of the fact that it has been proposed in the medical field to focus on signals in the vicinity of 75 msec, 100 msec, and 145 msec after stimulation as signals induced by visual stimulation, among the signals at three time points to be noted, Difficulty in work due to the reaction intensity of the section including two signals that occur (particularly a strong signal near 100 msec) and the reaction intensity of the section including the remaining one signal (signal near 145 msec) It is thought that a difference according to

  Then, the threshold value for evaluating the accumulation fatigue in the reaction intensity of VEF was examined. In that case, first, from the data obtained in the conventional research of the present inventors, the cutoff value for the presence or absence of severe fatigue in the Chalder's fatigue scale was examined, and the Chalder's fatigue scale was set to 17 or more. I found it desirable. This value is obtained by calculation using a ROC (Receiver Operating Characteristic curve) curve. In this case, the significance probability is 0.001 or less, the area under the ROC is 0.80 or more, the sensitivity is 75.0%, and the specificity is 77. It was 1%, which was a reliable result. In other words, it is determined that there is accumulated fatigue if the Chalder's fatigue scale is 17 or more, and it is determined that there is no accumulated fatigue if it is less than 17. Note that the number 17 is not strictly limited to this, and may be within a range of 16 or more and 18 or less with some reliability. 8 and FIG. 9 and further the correlation intensity of the correlation shown in FIG. 10 by the least square method, the reaction intensity of VEF corresponding to the cut-off value 17 that can be judged that severe fatigue is present in the Chalder's fatigue scale The value of was extracted. From the correlation equation (Equation 1) of FIG. 9, in the 2-back test implementation group, the case of 1 Hz red flashing light stimulation is 2.8 nA · m (logarithmic value 1.0), and the correlation equation of FIG. ) Led to 1.7 nA · m (logarithmic value 0.56) in the case of 16 Hz red flashing light stimulation. Also, from the correlation equation (Equation 3) in FIG. 10, in the 0-back test implementation group, a value of 5.3 nA · m (logarithmic value of 1.7) was derived in the case of 1 Hz red flashing light stimulation.

(Formula 1) y = 0.1255x-1.0866
(Formula 2) y = 0.0824x-0.8428
(Formula 3) y = 0.1838x-1.465

  If the cut-off value is 16 or more and 18 or less, in the 2-back test implementation group, it is 2.5 nA · m to 3.3 nA · m in the case of 1 Hz blinking light stimulus, and in the case of 16 Hz blinking stimulus 4 It is not less than 5 nA · m and not more than 6.0 nA · m. Similarly, in the 0-back test implementation group, it is 1.6 nA · m or more and 1.9 nA · m or less.

  Based on the above results, the present inventors conducted a subject experiment for the purpose of verifying the possibility of evaluating non-invasive body fatigue performed independently, and the reaction intensity in the VEG analysis of MEG and the score of the Chalder's fatigue scale. It was found that the correlation appears deeply when it causes “fatigue caused by work that is monotonous and lightly loaded” and “fatigue caused by work that is difficult and heavily loaded”. Furthermore, the threshold value in the reaction intensity of VEF for evaluating accumulated fatigue was extracted from the obtained correlation. Thus, the present inventors have demonstrated the possibility that chronic accumulated fatigue can be evaluated by a physical biosensor such as a magnetoencephalogram which has not been made so far.

  The biological fatigue evaluation apparatus according to the present invention can non-invasively and easily evaluate human fatigue, and is useful for early detection of fatigue in daily life. The present invention can also be applied to uses such as an inspection system for primary screening of diseases in a medical field, an employee management system in an occupational area, and a driver state estimation system in an automobile.

DESCRIPTION OF SYMBOLS 101 Biometric signal measurement part 102 Feature-value extraction part 103 Fatigue evaluation part 104 Stimulus output part 105 Device control part 401 Work execution part 402 Storage part 1201 Pulse wave measurement part 1202 Acceleration pulse wave calculation part 1203 Storage part 1204 Evaluation part 1205 Pulse wave measurement Unit 1206 Acceleration Pulse Wave Calculation Unit 1207 Storage Unit 1208 Chaos Analysis Unit 1209 Evaluation Unit 11 Driver 12 Front Scene 13 Steering 14 Pedal 15 Brain Activity Detection Device 16 Signal Processing Unit 17 Arithmetic Device 18 Storage Device 19 Activation Device 20 Oxygen Supply Machine 21 Speaker 22 Light source 23 Vibration generator 24 Sheet

Claims (10)

A biological signal measuring unit for measuring the biological signal of the subject,
A feature amount extraction unit that extracts a feature amount related to a visual stimulus from the biological signal measured by the biological signal measurement unit;
A fatigue evaluation unit that evaluates the presence or absence of accumulated fatigue in the subject based on the feature amount extracted by the feature amount extraction unit,
The biological signal measuring unit is a biological fatigue evaluation device that measures the biological signal after the subject performs an operation that becomes a mental fatigue load. The biological signal is an electrical signal or a magnetic signal indicating brain function,
The feature amount extraction unit extracts an event-related signal induced by a visual stimulus from the biological signal,
The biological fatigue evaluation apparatus according to claim 1, wherein the fatigue evaluation unit evaluates the presence or absence of accumulated fatigue based on the intensity of the event-related signal. The feature amount extraction unit extracts, as a feature amount, an event-related signal in a predetermined time interval after 100 msec has elapsed after visual stimulation when the work performed by the subject is a work using a working memory in the brain.
The said fatigue evaluation part evaluates that accumulation fatigue exists when the average intensity | strength in the predetermined time interval of the said event related signal extracted by the said feature-value extraction part exceeds the preset threshold value. The biological fatigue evaluation apparatus described in 1. When the work performed by the subject is a work that does not use a working memory in the brain, the feature amount extraction unit detects an event-related signal in a predetermined time interval from 145 msec after the visual stimulation to immediately before the visual stimulation. Are extracted as features,
The said fatigue evaluation part evaluates that accumulation fatigue exists when the average intensity | strength in the predetermined time interval of the said event related signal extracted by the said feature-value extraction part exceeds the preset threshold value. The biological fatigue evaluation apparatus described in 1. A stimulus output unit for applying visual stimulus to the subject;
5. The biological fatigue evaluation apparatus according to claim 1, wherein the feature amount extraction unit extracts a feature amount related to visual stimulation by the stimulus output unit from the biological signal.   The living body fatigue evaluation apparatus according to claim 5, wherein the stimulus output unit outputs blinking light having a frequency in a δ wave band or a β wave band. A work execution unit for causing the subject to perform a work using a working memory in the brain or a work not using a working memory in the brain;
The biological fatigue evaluation apparatus according to claim 1, wherein the biological signal measurement unit measures the biological signal of the subject after the work is executed by the work execution unit.   The living body fatigue evaluation apparatus according to any one of claims 1 to 7, further comprising a device control unit that controls an external device based on a result evaluated by the fatigue evaluation unit.   The living body fatigue evaluation apparatus according to any one of claims 1 to 8, further comprising a storage unit that stores a result evaluated by the fatigue evaluation unit. A biological signal measuring step for measuring a biological signal of the subject;
A feature amount extraction step for extracting a feature amount related to a visual stimulus from the biological signal measured in the biological signal measurement step;
A fatigue evaluation step of evaluating the presence or absence of accumulated fatigue in the subject based on the feature amount extracted in the feature amount extraction step,
In the biological signal measuring step, the biological fatigue evaluation method of measuring the biological signal after the subject performs a predetermined work.

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