JP2018057510A - Stress evaluation device and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a stress measuring device capable of quantitatively evaluating stress by a method in which a burden on a subject is further reduced.SOLUTION: A stress evaluation device for evaluating a stress state of a subject includes: signal acquisition means for acquiring a brain potential signal from one electrode attached to a frontal region of a subject; and arithmetic means for calculating a power spectrum from the brain potential signal acquired by the signal acquisition means within a predetermined time, determining an index value for evaluating a stress state by calculating a ratio of a total value of power of each frequency in a first frequency band including the δ wave band to a total value of power of each frequency in a second frequency band including a frequency band higher than the first frequency band, which is different from the first frequency band, and evaluating the stress state of the subject based on the index value and a reference index value which is an index value as a reference set beforehand.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a stress evaluation apparatus and method, and more particularly to a stress evaluation apparatus and method for evaluating a stress state based on brain potential.

  Conventionally, as a method for estimating the mental stress of an employee in the field of labor management or the like, a method of checking with an questionnaire is mainly used. However, since the check by the questionnaire has a strong subjective factor, there is a problem that a wrong judgment is made when disguising the stress damage by concealing the subject or concealing the stress damage, and a more objective evaluation method Development is desired.

  When the brain is subjected to mental stress such as sadness or fear, the limbic system, which is the center of emotions, is greatly affected, but primary emotional responses are thought to be generated mainly in the amygdala. For example, in Non-Patent Document 1, as a result of investigating active sites by fMRI by imposing language tasks related to the pets on 20 subjects who lost their pets, focusing on amygdala in response to sadness and avoidance It is disclosed that a superior activity is observed in the portion. This primary nerve activity acts on the hypothalamic nucleus, also in the limbic system, and through the autonomic nervous system consisting of the exchange and parasympathetic nerves (for example, blood pressure, It is known to cause a pulse, a pupil reaction, etc.). In addition, it is known that the secondary reaction extends to the frontal region and suppresses the activity of the self-reward system as the “centre of joy” centering on the nucleus accumbens. Furthermore, it is known that in subjects whose joy emotions have decreased due to mental illness, the δ component of the electroencephalogram (EEG) of the anterior cingulate cortex increases with the activity of the nucleus accumbens (Non-patent Document 2).

  If such physiological changes in brain activity related to stress are observed by PET or fMRI, it is expected that objective evaluation of stress can be performed more accurately. However, PET using an isotope is not suitable for a stress test that requires repeated measurements because it involves not only a large apparatus but also radiation exposure. In addition, in the fMRI method, the subject is exposed to a strong magnetic field and a high-frequency electromagnetic field. Therefore, the fMRI method cannot be used for a subject having a pacemaker or a metal prosthesis in the body, and a large-scale device for generating a strong magnetic field is required. The usage environment is greatly limited. The MEG (Magneto-encephalogram) method, which can be used in place of these measurement methods, not only requires a strong magnetic shield but also requires a cooling device for realizing superconductivity, An expensive measuring device is required.

  On the other hand, measurement of physiological changes in brain activity due to brain potential (electroencephalogram) observed from the scalp has been widely used in clinical settings because it does not require a large-scale device.

  In a general clinical field where the potential distribution on the scalp is observed with a large number of electrodes, the brain potential observed using 19 electrodes in the international 10-20 method is recorded in a pen recorder or a memory in a computer. Has been done. For example, assuming that the brain potential observed on the scalp is generated by an equivalent dipole power source that assumes the brain inside the brain, the position, direction, and current value of the equivalent dipole power source are inversely estimated from the brain potential distribution on the scalp. A method of equivalent expression using a “dipole estimation method” has been developed (Non-patent Document 3). In this method, in order to reversely estimate the dipole inside the brain from the potential distribution on the scalp, not only a large-scale operation involving a search operation in a multidimensional space is required, but also a stable solution is obtained. A large number of electrodes was required.

On the other hand, a method for estimating the sensitivity state of a subject using brain potentials observed from 10 electrodes arranged on the scalp has also been performed (Non-Patent Documents 6 and 7). Specifically, the correlation between the potentials observed between the two electrodes is evaluated with ₁₀ C ₂ = 45 cross-correlation functions, and this is evaluated for each of the brain potential θ, α, and β bands. However, a method of expressing with a total of 45 × 3 = 135 parameters has been used. However, even in this method, since at least 10 electrodes are required, it is difficult to keep the electrode contact stable during measurement.

Peter J. Freed, Ted K. Yanagihara, Joy Hirsch, and J. John Mann, “Neural mechanism of grief regulation”, Biol. Psychiatry, vol.66, no.1, pp.33-40, July 2009. Jan Wacker, Daniel G. Dillon, Diego A. Pissagalli, “The role of the nucleus accumbens and rostral anterior cingulate cortex in anhedonia: Integration of resting EEG, fMRI, and Volumetric Techniques, Neuroimage, vol.46, no.1, pp .327-337, May 2009. J. Hara, W. R. Shankle and T. Musha, Cortical Atrophy in Alzheimer's Disease Unmasks Electrically Silent Sulci and Lowers EEG Dipolarity, IEEE Trans. Biomed. Eng., Vol. 46, no. 8, 905-910, 1999. Toshimitsu Takeshi “Measuring“ Kokoro ”” Nikkei Science April 20-29 (1996) T. Musha, Y. Terasaki, H. A. Haque, and G. A. Ivamitsky, “Feature extraction from EEGs associated with emotions,” Artif. Life Robot., 1 (1): 15-19, 1997.

  As a device for evaluating mental stress, a device that evaluates stress based on a brain potential that can be configured relatively easily is preferable. However, each of the above approaches requires a large number of electrodes on the scalp. This was a heavy burden on the subject.

  The present invention has been made to solve such a problem, and provides a stress evaluation apparatus capable of quantitatively evaluating stress by a method that further reduces the burden on the subject. Main purpose.

  The above problem is solved by the present invention having the following features. That is, the stress evaluation apparatus as one aspect of the present invention is a stress evaluation apparatus for evaluating the stress state of a subject, and acquires a brain potential signal from one electrode attached to the frontal region of the subject. A power acquisition unit for calculating a power spectrum from the brain potential signal acquired within a predetermined time by the signal acquisition unit, and calculating the total value of the power of each frequency in the first frequency band including the δ wave band. An index value for stress state evaluation is determined by calculating a ratio with respect to a total value of power of each frequency in a second frequency band including a frequency band higher than one frequency band and different from the first frequency band. And calculating means for evaluating the stress state of the subject based on the index value and a reference index value that is a preset index value. And features.

  Also, as one aspect of the present invention, preferably, the reference index value is an average of each of the index values determined at rest and stress times determined based on brain potential signals at rest and stress of a plurality of subjects. The calculation means calculates the Z score of the index value determined based on the brain potential signal of the subject using the average value and standard deviation at rest and stress, respectively. Then, the stress state of the subject is evaluated from the combination of the magnitudes of the respective Z scores.

  Also, as one aspect of the present invention, preferably, the reference index value is a plurality of index values calculated in the past based on the brain potential signal of the subject, and the computing means is the brain potential of the subject. The stress state is evaluated by comparing the index value determined based on the signal with a plurality of the index values previously determined based on the brain potential signal of the subject.

  Moreover, as one aspect of the present invention, preferably, the first frequency band is 1 to 4 Hz, and the second frequency band is 4 to 20 Hz.

  Also, as one aspect of the present invention, preferably, the signal acquisition means acquires a brain potential signal from a part of F7 in the subject's international 10-20 method or one electrode attached within a radius of 30 mm of the part. To do.

  A stress evaluation method according to an aspect of the present invention is a stress evaluation method for evaluating a stress state of a subject, the step of acquiring a brain potential signal from one electrode attached to the forehead of the subject; The first frequency of the step of calculating the power spectrum from the brain potential signal acquired within a predetermined time by the signal acquisition means and the total value of the power of each frequency within the first frequency band including the δ wave band Determining an index value for stress condition evaluation by calculating a ratio to a total value of power of each frequency in a second frequency band that includes a frequency band higher than the band and is different from the first frequency band; And evaluating the stress state of the subject based on the index value and a reference index value that is a preset index value. The features.

  According to the present invention, stress can be quantitatively evaluated by a method that further reduces the burden on the subject.

It is a schematic block diagram of the stress evaluation apparatus of the 1st Embodiment of this invention. It is a figure which shows the attachment position of the electrode of the brain potential sensor by embodiment of this invention. It is a functional block diagram of the stress evaluation apparatus of the 1st Embodiment of this invention. It is a flowchart which shows the information processing which the electronic device 120 of the 1st Embodiment of this invention evaluates a stress state. It is one example of evaluation object brain potential data. It is one example of the power spectrum calculated from the evaluation object brain potential data. The figure which shows the average value and standard deviation of 20 test subjects for every frequency of power of four states (task 1, task 2, resting eyes 2 and resting eyes 3) based on the power of resting eyes 1 at the electrode of F7. It is. It is a figure which shows the power spectrum which standardized the difference of the power of the stress state and the power of a rest state in the electrode of F7. In the 21 electrodes shown in FIG. 2, a value obtained by subtracting the power of the resting eye 1 from the power of task 1 in each subject is calculated at each frequency, and the average of the calculated values of 20 subjects for each frequency and electrode placement position. It is a figure which shows a value. It is a figure which shows the power spectrum of FIG. 7 in 21 electrodes shown in FIG. 2 for every frequency and electrode arrangement position. It is a schematic block diagram of the stress evaluation apparatus 100 by the other Example of 2nd Embodiment. It is an outline outline figure of a hat wearing type electrode of stress evaluation device 100 by other examples of a 2nd embodiment of the present invention. It is a figure which shows the conductive rubber electrode schematic diagram for the reference potential measurement of the stress evaluation apparatus 100 shown in FIG. It is a figure which shows the electric potential of the uniform sphere model surface which has a dipole current source in center part. It is a figure which shows the electric potential of the uniform sphere model surface which has a dipole current source in center part. It is a figure which shows the electric potential of the uniform sphere model surface which has a dipole current source in center part. It is a figure which shows the electric potential of the uniform sphere model surface which has a dipole current source in center part. It is a figure which shows the plot on delay parameter space. It is a figure which shows the time evolution of the electric potential of each electrode A, B, C in the surface of a uniform sphere model which has a dipole current source in the center. It is a flowchart which shows the information processing in which the electronic apparatus 120 of the 2nd Embodiment of this invention calculates the triple correlation value S. The figure which shows the pseudo | simulation three-dimensional display of the triple correlation value distribution of the test subject A on the feature space which the two delay parameters ((tau) 1, (tau) 2) which produced by the electronic device 120 of the 2nd Embodiment of this invention forms. is there. The figure which shows the pseudo | simulation three-dimensional display of the triple correlation value distribution of the test subject B on the feature space which the two delay parameters ((tau) 1, (tau) 2) which produced by the electronic device 120 of the 2nd Embodiment of this invention forms. is there. FIG. 22 is a view of the three-dimensional display diagram of FIG. 21 as viewed from above, in which a region where three signals have the same sign is expressed in white, and a region where any one of the three signals is different is expressed in black. It is. The figure which looked at the figure of the three-dimensional display of FIG. 22 from the top, Comprising: The area | region where three signals have the same code | symbol is represented in white, The area | region where any one code | symbol of three signals differs is represented in black It is. 23 and 24, the distances dxi (i = 1, 2,..., M), dyj (j = 1, 2,..., N) between the white square regions when calculating the index SD from FIG. FIG.

  Hereinafter, a stress evaluation apparatus according to an embodiment of the present invention will be described with reference to the drawings.

[First Embodiment]
One of the technical features of the first embodiment of the present invention is not a β wave band (13 Hz or more) but a low frequency band such as a δ wave band (1 to 4 Hz) or a θ wave band (4 to 8 Hz). It is to evaluate the stress state using the EEG. In general, it is said that in the occipital region, β waves increase during stress, and θ waves and α waves increase during relaxation. It is difficult for ordinary people to measure clean brain waves without noise. Therefore, the stress evaluation apparatus according to the first embodiment of the present invention has the δ wave band (or the lower band of the δ wave band and the θ wave band) observed from one electrode in contact with the frontal head (preferably F7). ) The stress state is evaluated by the relative power level. Here, the relative power is, for example, the ratio of the power of the δ wave band to the power of a wide-band brain wave including the θ wave band to the β wave band. A specific configuration and the like will be described below.

[Device Overview]
FIG. 1 is a schematic configuration diagram of a stress evaluation apparatus 100 according to the first embodiment of the present invention. The stress evaluation device 100 includes a brain potential sensor 110 and an electronic device 120.

  The brain potential sensor 110 includes one electrode 111 and a communication unit (not shown) that transmits a brain potential signal (electroencephalogram data) measured by the electrode 111 to the electronic device 120. The electrode 111 is attached in contact with the head and measures a brain potential signal based on brain functional activity. Preferably, as shown in FIG. 1, the brain potential sensor 110 is a headgear type brain potential sensor in which electrodes are arranged in advance so that the electrodes come into contact with the forehead when the subject wears the head. For example, the electroencephalogram sensor 110 is an electroencephalograph manufactured by MUSE. The brain potential sensor 110 may be a cap or a helmet type in which electrodes are arranged in advance. The brain potential sensor 110 further includes a reference electrode (not shown). The reference electrode is used as a dead electrode, for example, an electrode attached to the earlobe.

  In the embodiment of the present invention, an electrode arrangement obtained by adding Fpz (defined as an intermediate point between Fp1 and Fp2) and Oz (defined as an intermediate point between O1 and O2) to the electrode arrangement of the international 10-20 method as shown in FIG. The electrode 111 is arranged at any position in the arrangement. As will be described later, preferably, the brain potential sensor 110 is configured such that when the subject wears the brain potential sensor 110 on the head, the electrode 111 is within a radius of 30 mm in the vicinity of the F7 site or the F7 site in the international 10-20 method. Configured to be arranged. In this case, the electrode 111 acquires the brain potential signal acquired from within the radius of 30 mm of the F7 part or the F7 part of the subject.

  The communication unit performs wireless communication and transmits the brain potential signal acquired by the electrode 111 to the electronic device 120. However, wired communication using an Ethernet (registered trademark) cable, a USB cable, or the like can also be performed. The brain potential sensor 110 includes a plurality of electrodes 111, and the communication unit may be configured to transmit a brain potential signal measured by one of the electrodes 111 to the electronic device 120.

  The electronic device 120 includes a processing unit 121, a display unit 122, an input unit 123, a storage unit 124, and a communication unit 125. Each of these components is connected by the bus 126, but each of them may be individually connected as necessary.

  The electronic device 120 is preferably a smartphone, but may be a general computer or a tablet computer.

  The processing unit 121 includes a processor (for example, a CPU) that controls each unit included in the electronic device 120, and performs various processes using the storage unit 124 (for example, a main memory) as a work area. The display unit 122 displays a screen for the user according to the control of the processing unit 121, and is configured by a liquid crystal display, for example.

  The input unit 123 receives an input from the user to the electronic device, and is, for example, a touch panel, a touch pad, a keyboard, or a mouse. The storage unit 124 includes a hard disk, a main memory, and a buffer memory. A program is stored in the hard disk. However, the hard disk may be any non-volatile storage or non-volatile memory as long as it can store information, and may be removable. For example, when electronic device 120 is a smart phone, ROM and RAM are included. The storage unit 124 stores a program and various types of data that can be referred to when the program is executed.

  The communication unit 125 performs wireless communication, receives a brain potential signal from the brain potential sensor, and stores it in the storage unit 124. However, wired communication using an Ethernet (registered trademark) cable, a USB cable, or the like can also be performed.

  FIG. 3 is a functional block diagram of the stress evaluation apparatus 100 according to the first embodiment of this invention. The stress evaluation apparatus 100 includes a signal acquisition unit 301 and a calculation unit 302.

  The signal acquisition means 301 has a function of acquiring a brain potential signal from the brain using an electrode attached to the subject's head, and the brain potential sensor 110 is one example. The signal acquisition unit 301 preferably has a function of acquiring a brain potential signal from one electrode attached to the frontal portion of the subject.

  The calculation unit 302 has a function of evaluating a stress state based on the brain potential signal acquired by the signal acquisition unit 301. The computing means 302 is realized by causing the electronic device 120 to execute a program. In one example, when the electronic device 120 is a smartphone, the function of the computing unit 302 is realized when a dedicated application that is a program is downloaded and activated.

[Information processing]
FIG. 4 is a flowchart illustrating information processing for evaluating the stress state by the electronic device 120 according to the first embodiment of this invention. Here, the brain potential sensor 110 has one electrode 111 attached to the site F7, and the electronic device 120 receives a brain potential signal acquired at the electrode 111.

  In step 401, the brain potential signal received from the brain potential sensor within the time to evaluate the stress state (evaluation target time) is stored in the storage unit 124 as evaluation target brain potential data (digital data). By dividing the evaluation target time, it is possible to store a plurality of evaluation target brain potential data corresponding to the evaluation target time. Here, one evaluation target brain potential data will be described. The evaluation target time is preferably 2 minutes or more, and can be 2 minutes or 5 minutes.

  In this step, the electronic device 120 removes excessive biological noise other than brain waves due to blinking or the like from the brain potential signal received from the brain potential sensor 110 by a known method, and stores it. Preferably, after removing these noises, a predetermined frequency band, for example, 0 to 50 Hz is extracted, and evaluation target brain potential data is stored. FIG. 5 is one example of the brain potential data to be evaluated, the horizontal axis is time, and the vertical axis is voltage.

  Subsequently, in step 402, a power spectrum is calculated by performing discrete Fourier transform on the evaluation target brain potential data and calculating the square (square mean value) of each discrete Fourier coefficient.

  FIG. 6 is an example of the power spectrum calculated from the brain potential data to be evaluated, where the horizontal axis is frequency and the vertical axis is power. In the power spectrum, a value (power) is discretely provided for each frequency point that is an integral multiple of the frequency resolution Δf. In one example, Δf = 1.56 Hz.

  The power spectrum is calculated in a frequency band including a δ wave and a broadband brain wave including at least a part of the θ wave to β wave region. In one example, the power spectrum is calculated from 0 to 20 Hz, and when Δf = 1.56 Hz, 1.56 Hz, 3.12 Hz, 4.68 Hz,..., And 18.72 Hz (1.56 Hz to 18.72 Hz) ), A power spectrum having power is calculated.

  Subsequently, in step 403, the first frequency including the frequency band higher than the first frequency band of the total value of the powers of the respective frequencies (the square of the discrete Fourier coefficient) in the first frequency band including the δ wave band. A ratio with respect to the total power of each frequency in the second frequency band different from the band is calculated. An index value for stress state evaluation is determined (calculated) from the calculated ratio. For example, the calculated ratio value itself can be used as the index value, the percentage of the calculated ratio can be used as the index value, or the logarithm of the calculated ratio value can be used as the index value. You can also.

  In one example, the first frequency band is 1 to 4 Hz corresponding to the δ wave band, and the second frequency band is 4 to 20 Hz corresponding to the frequency band of the θ wave to β wave region. In this case, the ratio of the total power value of each frequency of 1 to 4 Hz to the total power value of each frequency of 4 to 20 Hz is calculated. For example, when Δf = 1.56 Hz, the sum of the powers of the frequencies of 1.56 Hz and 3.12 Hz in the first frequency band is 4.68 Hz, 6.24 Hz, 7 in the second frequency band. An index value for stress state evaluation is calculated by calculating a ratio to a total value of powers of .8 Hz,.

  In another example, the first frequency band may be a δ wave band and a θ wave band, and the second frequency band may be a θ wave band to a β wave band.

  Subsequently, in step 404, the stress state is evaluated based on the calculated index value and the reference index value. Here, the reference index value is set in advance before the execution of this flowchart and is stored in the storage unit 124, and is used as a reference when evaluating a stress state from the calculated index value. It is.

  In one example, the stress evaluation device 100 (electronic device 120) acquires a reference index value and evaluates a stress state as follows.

  First, calculation of the reference index value will be described. By using the stress evaluation device 100 for a plurality of subjects, for example, 20 subjects in advance, an index value corresponding to step 403 is acquired. In the present embodiment, in order to acquire the reference index value, the electronic device 120 can execute information processing corresponding to Step 401 to Step 403 and store the acquired index value in the storage unit 124. Can do.

  The index value is acquired for each subject in two patterns of stress and rest. For example, when the subject is stressed, for example, when the subject is compelled to read a difficult-to-read Chinese character in front of the monitor, and when resting, for example, when the eyes are open. In either case, preferably, a brain potential signal for at least 2 minutes is acquired.

  Subsequently, an average value AVE1 and a standard deviation SD1 of a plurality of index values (data group 1) at the time of stress corresponding to the number of subjects calculated using the acquired brain potential signal are calculated. Similarly, an average value AVE2 and a standard deviation SD2 of a plurality of index values (data group 2) at rest for the number of subjects are calculated. In this case, there are four reference index values, AVE1, SD1, AVE2, and SV2.

  Next, a stress state evaluation method will be described. The electronic apparatus 120 uses the Z score (deviation value) Z1 in the data group 1 and the Z score in the data group 2 of the index value (index value of the stress evaluation target) calculated in step 403 based on the evaluation target brain potential data. Z2 is calculated. When the index value of the stress evaluation target is X, Z1 and Z2 are respectively expressed as Z1 = (X-AVE1) / SD1 and Z2 = (X-AVE2) / SD2.

  The electronic device 120 evaluates the subject's stress state from the combination of the sizes of Z1 and Z2. In this case, the closer the Z1 is to 0, the greater the subject's stress, and the closer Z2 is to 0, the less the subject's stress. For example, the electronic device 120 determines the subject's stress state in a plurality of stages and percentages, and displays the determination result on the display unit 122. By setting it as such a structure, in this embodiment, a test subject's stress state is evaluated compared with the stress state at the time of the stress of other test subjects, and a rest. This makes it possible to perform a quantitative stress evaluation.

  In another example of this embodiment, the reference index value may be only AVE1 and SD1, or only AVE2 and SV2. In this case, the electronic device 120 evaluates the subject's stress state from the size of Z1 or Z2. For example, when the electronic device 120 evaluates the stress state of the subject from the magnitude of Z2, if | Z2 | ≦ 0.25, the stress level is “0”, and if 0.25 <| Z2 | ≦ 0.52, the stress level is “1”. , 0.52 <| Z2 | ≦ 0.84, stress level “2”, 0.84 <| Z2 | ≦ 1.28, stress level “3”, and 1.28 <| Z2 |, stress level “4”. Or the like.

  In another example of the present embodiment, the reference index value may be only AVE1 and AVE2. In this case, the electronic device 120 evaluates the stress state of the subject from the sizes of X-AVE1 and X-AVE2. However, it is not limited to these illustrations.

  In another example, the stress evaluation device 100 (electronic device 120) evaluates the stress state without acquiring the reference index value in advance.

  In this case, the electronic device 120 uses the stress evaluation device 100 for a predetermined number of times (for example, five times), that is, only after the stress evaluation device 100 calculates the index value for a predetermined number of times. A reference index value is generated from the index value calculated based on the index value. The reference index value is an index value calculated, for example, five times immediately before the stress evaluation.

  The electronic device 120 evaluates the stress state of the subject by comparing the index value of the stress evaluation target with the index value calculated five times immediately before. For example, when the index value gradually increases, it can be evaluated that the stress state is increasing. By setting it as such a structure, in this embodiment, a test subject's stress state is evaluated compared with the said test subject's past stress state. Thereby, it becomes possible to evaluate the degree of increase or relaxation of the stress of the subject using the stress evaluation apparatus 100.

  In another example of the present embodiment, the reference index value is, for example, an average value and a standard deviation in the data group 3 in a part or all of the index values calculated before calculating the index value to be subjected to stress evaluation. . The electronic device 120 evaluates the stress state of the subject from the magnitude of the Z score in the data group 3 of the index value to be stress evaluated.

[Example]
The following experimental result demonstrates that the stress state can be evaluated using the stress evaluation apparatus 100 according to the first embodiment of the present invention.

  In this experiment, for each of the 20 subjects, the states of resting eyes 1 (120 s), task 1 (380 s), resting eyes 2 (120 s), task 2 (380 s), and resting eyes 3 (120 s) sequentially. The brain potential signal in each state was obtained. At this time, 21 electrodes shown in FIG. 2 were placed on the scalp for the subject, and brain potential signals were acquired from the 21 electrodes. The electrode used in this experiment is equivalent to the electrode 111 in the stress evaluation apparatus 100.

  Here, tasks 1 and 2 are states in which the subject is forced to read out obscure kanji characters in front of the observer (stress state). It is the state (rest state) which has opened and is made to rest.

  Note that the acquired brain potential signal (especially the brain potential signal acquired from the frontal electrode) is mixed with excessive biological noise other than brain waves due to blinking, etc. These noises were removed, and a frequency band of 0 to 50 Hz was further extracted.

  Here, the analysis of the brain potential signal at one certain electrode will be described. In the following, one electrode is arranged at the site F7, but the same applies to the electrodes arranged at other sites. In each of the above five states, for each subject, a power spectrum is calculated by performing a discrete Fourier transform on the brain potential signal acquired from the electrode and calculating the square (power) of each discrete Fourier coefficient. did.

  Next, a value (power) obtained by subtracting the power of resting eye 1 from the power of task 1 of each subject is calculated at each frequency, and the average value and standard deviation of the calculated 20 subjects are calculated at each frequency. did. For the resting eyes 2, task 2, and resting eyes 3, the values obtained by subtracting the power of the resting eyes 1 from the respective powers are calculated at the respective frequencies in the same manner as in the task 1, and the 20 subjects having the calculated values are calculated. Average values and standard deviations were calculated at each frequency. The value obtained by subtracting the power of the resting open eye 1 from the power of each of the task 1, resting open eye 2, task 2, and resting open eye 3 is used to set the first resting open eye 1 as the baseline in the measurement of this experiment. It is.

  FIG. 7 is a diagram showing an average value and standard deviation of 20 subjects for each frequency of power in the four states (task 1, task 2, resting open eye 2, resting open eye 3) calculated as described above. FIG. 7 plots the average values and displays the standard deviation with error bars. From FIG. 7, it can be confirmed that there is a large difference between the stress state and the rest state at 5 Hz or less.

  Next, the difference between the power of tasks 1 and 2 (stress state) and the power of resting eyes 2 and 3 (rest state) is divided by the standard deviation so that the difference between the stress state and the rest state can be compared between the electrodes. Standardized. Specifically, a value obtained by subtracting the average value of the resting eyes 2 and 3 from the average value of the tasks 1 and 2 in each subject is calculated at each frequency, and the average value of the 20 subjects of the calculated values is calculated. Standard deviation was calculated at each frequency. Next, for each frequency, standardization was performed by dividing the average value calculated at each frequency by the standard deviation calculated at each frequency.

  FIG. 8 is a diagram showing a power spectrum in which the difference between the stress state power and the rest state power is standardized as described above. Also in FIG. 7, it can be confirmed that there is a large difference between the stress state and the rest state at 5 to 6 Hz or less.

  In this experiment, the above analysis was performed on all electrodes. FIG. 9 shows the calculated values obtained by subtracting the power of the resting eye 1 from the power of the task 1 in each subject for each of the 21 electrodes shown in FIG. It is a figure (topography) which shows the average value of 20 persons. FIG. 10 is a diagram showing the power spectrum of FIG. 7 for the 21 electrodes shown in FIG. 2 for each frequency and electrode arrangement position. In each figure, numerical values such as 1.56 and 3.13 indicate 1.56 Hz, 3.13 Hz, etc., and the topography color has a larger value as it is displayed in white, and a smaller value as it is displayed in black. .

  As can be seen from FIGS. 9 and 10, there is a significant difference between the stress state and the resting state within the front radius of the low frequency band such as 1.56 Hz, particularly within the radius of 30 mm in the vicinity of F7 and F7. ing. Therefore, it can be considered from this experiment that the stress state can be evaluated using the stress evaluation apparatus 100 of the first embodiment.

  Next, the effect of the stress evaluation apparatus 100 according to the first embodiment will be described. In this embodiment, a power spectrum is calculated from a brain potential signal acquired from one electrode 111 attached to the forehead, and the power of a wide-band brain wave (for example, 4 to 20 Hz) including a β wave region from a θ wave is calculated. The subject's stress state is evaluated by calculating the ratio of the power of the electroencephalogram in the low frequency band (for example, 1 to 4 Hz) including the δ wave to the total value. Thereby, when a test subject wants to evaluate a stress state, what is necessary is just to attach one electrode to the forehead which can attach an electrode rather than a back head, Therefore It becomes possible to reduce a burden on a test subject more. Moreover, it becomes possible to evaluate stress quantitatively.

[Second Embodiment]
One technical feature of the second embodiment of the present invention is to use the dNAT method disclosed in International Application No. PCT / JP2016 / 057041 as a brain function evaluation method for observing the deep state of the brain. . By acquiring the intensity of the δ wave that represents the suppression of the frontal self-reward system generated by the three electrodes placed on the frontal region and analyzing it using the dNAT method, the brain activity associated with stress is more accurately determined. It becomes possible to capture. A specific configuration and the like will be described below.

[Device Overview]
Since the schematic configuration diagram of the stress evaluation apparatus 100 according to the second embodiment of the present invention is the same as that of the stress evaluation apparatus 100 according to the first embodiment, differences will be mainly described. The brain potential sensor 110 includes three electrodes 111 and a communication unit (not shown) that transmits a brain potential signal measured by the electrodes 111 to the electronic device 120. The communication unit transmits the brain potential signal acquired from each of the three electrodes 111 and the signal obtained from the reference electrode to the electronic device 120, and the electronic device 120 transmits the signal between each of the three electrodes 111 and the reference electrode. The difference is calculated and used as input of three brain potential signals. Alternatively, the communication unit transmits three signals of the difference between each of the three electrodes 111 and the reference electrode to the electronic device 120 as a brain potential signal.

  In the present embodiment, since three electrodes for observing δ waves in the deep frontal lobe are used, three electrodes 111 are arranged on the frontal region. Preferably, the three electrodes are attached to the sites of Fp1, Fp2, and F8 in the international 10-20 method. For example, as shown in FIG. 1, the brain potential sensor 110 is a headgear-type brain potential sensor in which electrodes are arranged in advance so that the electrodes come into contact with the parts Fp1, Fp2, and F8 when the subject wears the head. is there.

  FIG. 11 is a schematic configuration diagram of a stress evaluation apparatus 100 according to another example of the second embodiment. The stress evaluation apparatus 100 includes a head mounting portion 113 including three electrodes 111 and a reference electrode 112, a 3ch amplifier / band filter 130 connected to the three electrodes 111 via a signal cable, a 3ch amplifier / band filter 130, and a signal. And an electronic device 120 connected by a cable.

  The reference electrode 112 is an electrode for measuring a reference potential, used as a dead electrode, and preferably a clip electrode for connecting the earlobe. The reference electrode 112 is connected to the 3ch amplifier / band filter 130.

  The three electrodes 111 are fixed by a fixing tool 114. The head mounting portion 113 includes a fixture 114 that fixes the three electrodes 111. The head mounting part 113 may be, for example, a boomerang-shaped plastic mounting part cut out from a helmet, or may be a headgear-shaped mounting part as shown in FIG. The head mounting portion 113 is preferably arranged such that when the subject wears the head mounting portion 113, the three electrodes abut on the Fp1, Fp2, and F8 sites in the International 10-20 method. Yes. The electrode 111 is preferably a porous fiber electrode containing physiological saline, and the upper portion of the electrode 111 is constituted by a metal cylinder for connecting a conductive wire.

  FIG. 12 is a schematic external view of a hat-mounted electrode of the stress evaluation apparatus 100 according to another example of the second embodiment. FIG. 13 is a schematic external view of a conductive rubber electrode for measuring a reference potential. The head mounting portion 113 is obtained by attaching three measurement electrodes 111 to a mesh hat. The electrode 111 is connected to a shielded cable 116 connected to the preamplifier 115, and porous conductive rubber containing saline is preferably used.

  The preamplifier 115 has the function of an amplifier of the 3ch amplifier / bandpass filter 130 and is connected to the electronic device 120 via the bandpass filter. The reference electrode 112 is a conductive rubber electrode 117 that is electrically connected to the preamplifier 115, thereby eliminating the need for an earlobe connection clip electrode. Here, a metal film 118 is installed between the circumferential conductive rubber electrode 117 and the cap in order to equalize the potential of the conductive rubber and to reduce the contact resistance when the cable from the preamplifier 115 is connected. Is done.

  As described above, the stress evaluation apparatus 100 according to the second embodiment acquires a brain potential signal obtained by extracting a δ wave band (1 to 4 Hz) from the frontal region (preferably Fp1, Fp2, and F8). A triple correlation value and an index value (dNAT value) are calculated from the brain potential signal. The stress evaluation apparatus 100 evaluates the stress state using the calculated triple correlation value and the index value. Next, the measurement principle will be described, and subsequently, the information processing of the stress evaluation apparatus 100 executed for calculating the triple correlation value and the index value will be described.

[Measurement principle]
In the measurement in this embodiment, an equivalent dipole power source is assumed in the deep brain. Here, a case is considered where the potential distribution measurement for analyzing the dipole potential activity is limited to electrodes arranged at three different locations on the scalp. When there is a power supply in the deep brain, this phase relationship is evaluated based on the fact that there is a strong phase relationship among the potential waveforms observed at these three electrodes. In this way, the temporal behavior of the equivalent dipole power source assumed in the deep brain is approximately estimated. Compared to seismic waves, the seismic waves with epicenters on the surface layer vary greatly from observation point to observation point. For seismic waves with deep epicenters, seismometers placed at close distances have almost the same amplitude and phase. This phenomenon is equivalent to the observation of the P wave.

  In the measurement according to the present embodiment, since the potential waveform appearing on the surface based on the activity of the deep brain is substantially in phase on the surface that is a short distance away, only data with the same sign of the three potentials is added. Define the method. In other words, correlation data can be extracted by using only data with the same code as a calculation target. However, all data can also be the target of calculation.

  As specific information processing, first, when three potential signals are inputted, signals having the same sign as the three potentials are selected. In one example, an earlobe that does not directly reflect cortical activity is used as the reference potential when determining the sign of the potential, but when the direct current component is blocked by a bandpass filter or a digital filter, the time average for each electrode is used. Determine the sign of positive or negative.

Subsequently, a triple correlation value is calculated. The triple correlation value is expressed as τ1 and τ2 with respect to the potential signal of one electrode when the low frequency band potential signals from the three electrodes are respectively EVA (t), EVB (t), and EVC (t). Use product with time-shifted signal. Formula 1 shown below is one example of the triple correlation value St. Here, T is a target time for calculating the triple correlation value, Δt is a data sampling period of each potential signal, N is a constant for normalization, and is, for example, the number of calculations of a product of three signals. .

  Here, the relationship between the triple correlation plot in the delay parameter space obtained by the above calculation and the behavior of the equivalent dipole power source in the deep brain will be described using a spherical model made of a uniform medium. In the following, for convenience of explanation, the names of each part of the sphere model are compared to the earth and described as the North Pole (NP), the South Pole (SP), the equator, and the like.

  Since the activity of the deep brain is equivalently observed on the surface of the brain so that there is a minute current source in the deep part, the minute current source is assumed in the direction from the south pole to the north pole at the center of the sphere. As shown in FIG. 14, the potential distribution generated by the current source on the sphere surface is + in the northern hemisphere,-in the southern hemisphere, and zero on the equator. In addition, this current source rotates clockwise in a period T seconds within a plane including points P1 and P2 having different longitudes of 180 degrees on the equator and NP and SP. The spherical surface potential distribution at each time point changes every 90 degrees of rotation angle as shown in FIG. 15, FIG. 16, and FIG. Three electrodes A, B, and C are arranged on the vertices of triangles parallel to the planes P1, NP, P2, and SP on the surface of the sphere. For the potential waveform measured from each electrode, the correlation value is calculated by Equation 1, and the calculation result is plotted on the delay parameter space of FIG.

The time evolution of the potentials of the electrodes A, B, and C is as shown in the graph of FIG. 19, and each electrode changes with a sine wave having a period T in a relationship of the phase difference 1 / 3T. When the electrode A is taken as a reference, the values of τ ₁ and τ ₂ with which the signs of these electrodes are the same are 1/3 + k and 2/3 + k (k is an integer), respectively. A characteristic having a peak at the period T as shown in the plot is obtained. In addition, the position where one of the electrodes deviates from the peak by a half cycle does not match the sign of the electrode because one electrode always has the opposite phase to the other two electrodes. For this reason, values are not plotted at positions indicated by white circles.

  As described above, the rotation of the equivalent dipole power supply in the deep brain can be observed as a plot on the two-dimensional delay parameter space. FIG. 19 and the like describe a case where a single equivalent dipole power supply rotates smoothly in a spherical deep brain. However, when there are a plurality of dipoles or when the rotation is not smooth, the plots in FIG. 18 have individual cases satisfying the same sign distributed in a complicated manner and appear as fine irregularities in the delay parameter space.

[Information processing]
Here, it is assumed that the stress evaluation apparatus 100 of the second embodiment having a schematic configuration as shown in FIG. 1 is used.

  Assuming that the three electrodes attached to the head are EA, EB, and EC, the electronic device 120 uses the potential signals VA (t) and VB () as the difference between the brain potential signal acquired from each electrode and the reference electrode. t), VC (t) is acquired. Subsequently, the electronic device 120 extracts a specific frequency band (preferably a δ wave band) by a band pass filter such as a digital filter. The electronic device 120 performs information processing shown in the flowchart of FIG. 20 on the extracted potential signal.

  FIG. 20 is a flowchart showing information processing for calculating the triple correlation value S by the electronic apparatus 120 according to the present embodiment. FIG. 20 shows a flowchart of processing for calculating the triple correlation value Si (i = 1, 2,..., T) from i seconds to i + 1 seconds. This flowchart can be changed without departing from the spirit of the present flowchart.

When three signals are input in step 2001, in step 2002, each potential of each electrode is divided by the standard deviation (σ _A, σ _B, σ _C ) and normalized (EVA (t) = VA (t) / σ _A , EVB (t) = VB (t) / σ _B , EVC (t) = VC (t) / σ _C ). This normalization process is preferably performed every second, but is not limited thereto. The above three signals to the electrodes E _A, electrode E _B is .tau.1, electrode E _C has a time lag of .tau.2.

  The frequency extraction process described above may be performed after the normalization process. Moreover, it is preferable to perform noise processing before the normalization processing. Noise processing, for example, 1) Excluding segments of ± 100 μV or more 2) Excluding flat potentials (when the potential is constant for 25 msec or more) 3) Excluding cases where a potential within ± 1 μV continues for 1 second or more, It consists of the process.

  Subsequently, in step 2003, the signs of the three signals are all positive (EVA (t)> 0, EVB (t-τ1)> 0, EVC (t-τ2)> 0), or all negative (EVA (t) < Only the signal of 0, EVB (t−τ1) <0, EVC (t−τ2) <0) is processed.

  In step 2004, a triple correlation value (one element of the triple correlation value) is calculated by adding the products of three potential signals having a time lag. The triple correlation value is calculated by shifting by Δt seconds until t reaches t = i + 1 seconds (S2006, S2007). For example, assuming that the potential data sampling frequency is fs (Hz), when fs = 200 Hz, Δt = 1 / fs = 0.005 seconds and the product of three potential signals is calculated. In this flowchart, a triple correlation value is calculated, and the number N of times when three signals become positive or negative is obtained (S2005), and finally divided (S2008).

In steps 2003 to 2007, the triple correlation value Si is calculated by calculating the following equation 2 for t when all the codes of the three signals have the same sign.
(I = 1, 2,..., T, τ1 = Δt, 2Δt,..., 1 (second), τ2 = Δt, 2Δt,..., 1 (second))

In this way, Si is calculated every second up to the total data T seconds (S ₁ , S ₂ ,..., S _T ). T (seconds) is preferably 10 (seconds). As described above, the triple correlation value is not calculated at once for all data (T seconds), but is calculated every predetermined time, for example, every second. The finally calculated triple correlation value S is an average value of T triple correlation values Si.

  The triple correlation value S is also calculated for the time shifts τ1 and τ2 by shifting by Δt seconds. Possible values of τ1 and τ2 are a time of 1 second or less equal to an integer multiple of Δt, but the maximum value of these values is not limited to 1 second. The triple correlation value can also be calculated by Equation 2 without performing the code determination of the three signals.

  Further, the electronic device 120 is characterized in that two delay parameters (τ1, τ2) form a triple correlation value S calculated by shifting the delay times τ1, τ2 by Δt seconds, 2Δt seconds,. It has a function to plot in space. Thereby, a pseudo three-dimensional display of the triple correlation value distribution plotted on the feature space formed by the two delay parameters (τ1, τ2) can be performed.

  FIG. 21 is a pseudo three-dimensional display of a triple correlation value distribution based on a brain potential signal acquired from the subject A. In order to eliminate the influence of data having no correlation, a predetermined value of t, for example, In t = i + 1, only Si (τ1, τ2) in which EVA (t), EVB (t-τ1), and EVC (t-τ2) all have the same sign is plotted. By limiting the Si to be plotted in this way, noise can be removed and a pseudo three-dimensional display of the triple correlation value distribution can be shown with better accuracy.

  FIG. 22 is a pseudo three-dimensional display of a triple correlation value distribution based on a brain potential signal acquired from the subject B in the same manner as FIG. While the triple correlation distribution in the feature space in FIG. 21 is smooth, it can be confirmed that the triple correlation distribution in the feature space in FIG.

  Furthermore, the electronic device 120 has a function of calculating the index value SD using the pseudo three-dimensional display of the triple correlation value distribution. As shown in FIGS. 21 and 22, the tree-like distribution is regularly arranged in the data of the subject A in the two delay time parameter spaces, whereas the tree-like distribution is irregular in the data of the subject B. The nature is great. In order to express this difference quantitatively, as shown in FIG. 23, the coordinate axes are rotated so that the rows of trees are parallel to the τ1 and τ2 axes. FIG. 23 is a view of the three-dimensional display shown in FIG. 21 as viewed from above. The region where the three waveforms have the same sign is displayed in white, and the region where any one of the three signals has a different sign is represented in black. When such a display is made, it becomes a regular checkered pattern in the case of the subject A, whereas in the case of the subject B, it can be confirmed that the checkered pattern is disturbed as shown in FIG. An index quantifying this disturbance is an index value SD.

  As shown in FIGS. 23 and 24, the white square area has a space in the vertical and horizontal directions from the adjacent white square area. As shown in FIG. 25, the intervals are dxi (i = 1, 2,..., M) and dyj (j = 1, 2,..., N). The degree of the disturbance can be quantified by determining whether the white squares are arranged evenly in the τ1 direction and the τ2 direction, or whether the white squares are distorted in the directions of dxi and dyj.

Specifically, as shown in Equation 3 and Equation 4, m dxi standard deviations Std_dx and n dyj standard deviations Std_dy are calculated.

The index value SD is an average value of two standard deviations as shown in Equation 5.

  The stress evaluation apparatus 100 evaluates the stress state of the subject based on a value calculated by dividing the index value SD by the triple correlation value S. For example, it is determined that the subject's stress is greater as the calculated SD / S is smaller.

  In another example, the electronic device 120 has a function of calculating the index value Ss by quantifying the degree of fluctuation of the triple correlation value calculated by Equation 2 per second.

Here, the standard deviation of Equation 2 is set to std_Si, and 10 standard deviations up to i = 1, 2,. Further, the standard deviation std_S of the ten standard deviations and the average value ave_S of the ten standard deviations are calculated.

The index value Ss is a ratio between the standard deviation and the average value as shown in Expression 9.

  Next, functions and effects of the stress evaluation apparatus 100 according to the second embodiment will be described. In this embodiment, a subject's stress state is evaluated by calculating a triple correlation value and an index value from brain potential signals acquired from three electrodes 111 attached to the frontal region. As a result, when the subject wants to evaluate the stress state, it is only necessary to attach three electrodes 111 to the forehead where the electrodes are easier to attach than the occipital region, so the burden on the subject can be further reduced. Moreover, it becomes possible to evaluate stress quantitatively.

  Each Example described above is an illustration for explaining the present invention, and the present invention is not limited to these Examples. As long as no contradiction arises, the examples can be combined as appropriate and applied to any embodiment of the present invention. That is, the present invention can be implemented in various forms without departing from the gist thereof.

DESCRIPTION OF SYMBOLS 100 Stress evaluation apparatus 110 Brain potential sensor 111 Electrode 112 Reference electrode 113 Head mounting part 114 Fixing tool 115 Preamplifier 116 Shield cable 117 Conductive rubber electrode 118 Metal film 120 Electronic device 121 Processing part 122 Display part 123 Input part 124 Storage part 125 Communication unit 126 Bus 130 3ch amplifier / band filter 301 Signal acquisition means 302 Calculation means

Claims (6)

A stress evaluation device for evaluating a subject's stress state,
Signal acquisition means for acquiring a brain potential signal from one electrode attached to the frontal portion of the subject;
A power spectrum is calculated from the brain potential signal acquired within a predetermined time by the signal acquisition means, and the total value of the power of each frequency within the first frequency band including the δ wave band is calculated from the first frequency band. An index value for stress state evaluation is determined by calculating a ratio to a total value of power of each frequency in a second frequency band that includes a high frequency band and is different from the first frequency band, and the index value And a calculation means for evaluating the stress state of the subject based on a reference index value that is a preset index value,
A stress evaluation apparatus comprising: The reference index value is the average value and standard deviation of the index value at rest and stress determined based on brain potential signals at rest and stress of a plurality of subjects,
The calculation means calculates the Z score of the index value determined based on the brain potential signal of the subject using the average value and the standard deviation at rest and stress, respectively. The stress evaluation apparatus according to claim 1, wherein the stress state of the subject is evaluated from a combination of sizes. The reference index value is a plurality of the index values calculated in the past based on the brain potential signal of the subject,
The computing means evaluates the stress state by comparing the index value determined based on the brain potential signal of the subject with a plurality of the index values previously determined based on the brain potential signal of the subject. The stress evaluation apparatus according to claim 1.   The stress evaluation apparatus according to any one of claims 1 to 3, wherein the first frequency band is 1 to 4 Hz and the second frequency band is 4 to 20 Hz.   The said signal acquisition means acquires a brain potential signal from one electrode attached within the site | part of F7 in the said subject's international 10-20 method, or the radius within 30 mm of this site | part. The stress evaluation apparatus described in 1. A stress evaluation method for evaluating a subject's stress state,
Obtaining a brain potential signal from one electrode attached to the forehead of the subject;
A step of calculating a power spectrum from the brain potential signal acquired within a predetermined time by the signal acquisition means; and a first frequency band of a total value of powers of the respective frequencies in the first frequency band including the δ wave band Determining an index value for stress condition evaluation by calculating a ratio to a total value of power of each frequency in a second frequency band that includes a higher frequency band and is different from the first frequency band;
Evaluating the subject's stress state based on the index value and a reference index value that is a preset index value;
A stress evaluation method.