Method of analyzing brain wave

Description: TECHNICAL FIELD [Detailed description of the invention]

【0001】

[Technical field to which the invention belongs]

The present invention relates to an electroencephalogram analysis method for quantitatively evaluating biological information by calculating the ratio of predetermined frequency bands of electroencephalogram signals.

【0002】

[Conventional technology]

Conventional methods used in fields such as clinical medicine to obtain biological information from EEG signals follow the empirical classification of signal waveforms that graphically represent changes in signal strength over time, and are characteristic of, for example, certain diseases. The focus is on visually finding the waveform pattern.

【0003】

On the other hand, spectral analysis of signals has been attempted as a method of obtaining biological information by numerical analysis of electroencephalogram signals. For example, in the case of brain waves, the main frequency components are roughly classified into delta waves (less than 4 Hz), theta waves (4 to 8 Hz), α waves (8 to 13 Hz), and β waves (13 Hz or more). The delta wave appears in a deeply relaxed state such as during deep sleep, theta wave appears in a deeply relaxed state such as during meditation, the α wave appears in a mentally relaxed state such as when the eyes are closed, and the β wave appears in a state of high tension when the eyes are opened. In Japanese Patent Application Laid-Open No. 5-300890, an attempt is made to evaluate the biological information of a subject by calculating the signal intensity of each frequency band from the result of spectral analysis and comparing between these bands.

【0004】

Further, as an example of attempting to evaluate biological information by further performing arithmetic processing on the result of spectrum analysis, Japanese Patent Application Laid-Open No. 6-261873 has power in the frequency band of 8 to 11 Hz and power in the frequency band of 11 to 14 Hz. An example of calculating the degree of relaxation by calculating the ratio with the power is disclosed.

【0005】

[Problems to be Solved by the Invention]

However, in the above-mentioned conventional example, when the signal of each frequency band is evaluated by the signal waveform, the evaluation procedure depends on the experience, and the evaluation is limited to qualitative information.

【0006】

In addition, when the spectrum of a signal is analyzed and the threshold value of the amplitude value is set for evaluation, an amplitude gradual increase / decrease phenomenon called Waxing & Waning is generally observed in brain waves. Therefore, in the evaluation of each frequency band, the signal is evaluated. It is difficult to determine whether the time variation of the amplitude of the subject is due to a change in the mental state of the subject or due to general Waxing & Waning.

【0007】

In addition, in these two standard methods, since the signals in each frequency band are evaluated separately, it is difficult to evaluate the information that correlates with each other in each frequency band, and the information that can be evaluated from there. Finds typical symptoms of the disease or only obtains highly simplified biometric information such as relaxation and tension.

【0008】

Further, in the case of an example in which the result of the spectrum analysis is further subjected to arithmetic processing to try to evaluate the biological information, the spectrum analysis is performed on the brain wave data for the entire measurement time to calculate the power value ratio. Therefore, the calculated evaluation value becomes an average value in the entire measurement time, and it is impossible to capture the fluctuation of the biological information of the subject within the measurement time. In this case, since the target frequency band is limited to the α wave band, only extremely simplified biological information such as relaxation and tension can be obtained.

【0009】

As described above, these conventional methods cannot be used for measuring information on higher-order functions of living organisms, quantifying biological information, and measuring time changes of biological information, which have been increasing in demand in recent years.

【0010】

In view of the above circumstances, the inventors of the present invention have examined in detail the problems of the prior art, and as a result, the limitations of the prior art are (1) trying to evaluate each frequency component individually, or 8 frequency bands. This is due to the fact that it is limited to ~ 14Hz, (2) the characteristic Waxing & Waning of the brain wave signal is not processed, and (3) the fluctuation of the frequency spectrum within the measurement time is not captured. I knew.

【0011】

Furthermore, as a result of repeated studies focusing on Waxing & Waning in each frequency band of the brain wave, the inventors of the present invention have found that this phenomenon occurs relatively synchronously between each frequency band.

【0012】

EEG is thought to be a relatively gentle waveform formed by accumulating postsynaptic potentials at many synapses. In the brain, various sensory information from the periphery is projected to each sensory area of the cerebrum via the thalamus, and it is speculated that the rhythm of brain waves is formed because the periodic suppression circuit in the thalamus works at that time. Has been done.

【0013】

Therefore, the electroencephalogram that can be directly observed is the electric potential generated in the cerebral cortex portion, and it can be considered that the movement of the brain stem such as the thalamus is reflected in the waveform change.

【0014】

Here, it can be considered that the time variation in each frequency band of the brain wave has a correlation between the respective bands with respect to human biological information.

【0015】

An object of the present invention is to solve the above-mentioned problems, calculate the average power value for each of two or more types of filtered frequency bands, and calculate the ratio of the average power value for each of the two predetermined combinations. By doing so, it becomes possible to capture biological information obtained from interrelated frequency bands in a complex manner, and to provide an electroencephalogram analysis method that can more easily evaluate the advanced mental state of humans. It is in.

【0016】

[Means for solving problems]

The brain wave analysis method according to the present invention for achieving the above object is a step of filtering a brain wave signal into two or more kinds of predetermined bands and a step of calculating an average power value in the band from a signal composed of the above bands. It is characterized by having a step of calculating the ratio of each of two predetermined combinations of the average power values for each band calculated in the step.

【0017】

BEST MODE FOR CARRYING OUT THE INVENTION

The present invention will be described in detail based on the illustrated embodiments. As shown in FIG. 1, the embodiment of the present invention includes a step of extracting two or more kinds of arbitrary bands of time-series biological signals in step 1, a step of calculating an average power value in step 2, and an arbitrary step 3. It consists of a step of calculating the ratio for each combination of and the step 4 of evaluating the biological information.

【0018】

FIG. 2 shows a block circuit configuration diagram of the processing device, and arithmetic control including the CPU and memory via the biological amplifier 2, the A / D conversion unit 3, and the data holding unit 4 that amplify the output biological signal from the brain wave measuring device. It is connected to device 5. The arithmetic control device 5 is connected to an external storage unit 6, a display unit 7, and a printing unit 8.

【0019】

When measuring the electroencephalogram of the subject, as shown in FIG. 3, a plurality of electrodes 9 are attached to the head of the subject S via the paste 10. The mounting site of the electrode 9 follows the standard method of the International Electroencephalography Society (10/20 method). The electroencephalogram signal shown in FIG. 4 detected by these electrodes 9 is amplified to a predetermined level by the preamplifier and the main amplifier 2, converted into a digital signal by the A / D converter 3, and recorded in the data holding unit 4. .. The sampling frequency in this A / D conversion process was set to 2.4 KHz in this embodiment.

【0020】

Subsequently, the arithmetic control device 5 performs a band filtering operation corresponding to step 1 in FIG. 1 on the digital signal recorded in the data holding unit 4. In the present embodiment, in order to calculate α / β as an example, for example, α wave: 8 to 13 Hz and β wave: 13 to 18 Hz are set as the frequency bands to be extracted, and each frequency band is provided. A time-series digital signal can be obtained.

【0021】

Here, the electroencephalogram signal converted into the digital signal extracted in each frequency band is shown as follows.

【0022】

Alpha wave: X_α= X_α₁+ X_α₂+ X_α₃+ ...... + X_α_n (t = 1,2,3 ... n) Beta: X_β= X_β₁+ X_β₂+ X_β₃+ ...... + X_β_n (t = 1,2,3 ... n) [0023]

Next, the time series digital signal X of each obtained frequency band_α, X_βOn the other hand, the arithmetic control device 5 calculates the average power value in each frequency band.

【0024】

FIG. 5 is an explanatory diagram illustrating the processing process in the arithmetic control device 5 with respect to the algorithm for calculating the average power value in the arithmetic control device 5. First, the power spectra of the filtered electroencephalogram signal data sequences of α wave and β wave shown in the above equation are calculated by FFT (Fast Fourier Transform). Subsequently, the power values are added in the calculated power spectrum and averaged in each frequency band to obtain the average power value corresponding to step 2 in FIG.

【0025】

Next, as step 3 in FIG. 1, the ratio α / β of the average power values of the α wave and the β wave calculated in this way is calculated. Subsequently, the ratio of the average power values between the frequency bands obtained by the arithmetic control device 5 is stored in the external storage unit 6 and displayed on the display unit 7 or printed by the printing unit 8 as needed. Evaluate the biometric information of the subject corresponding to step 4 in FIG.

【0026】

In this evaluation, when the changes in α / β with respect to various activations are examined, it can be found that the smaller this value is, the more active the thinking activity of the subject is. In the present embodiment, the subject is given activation of three types of (1) rest with eyes closed, (2) low-difficulty calculation task, and (3) high-difficulty calculation task, and is described. Along the process, α / β was calculated for the electroencephalogram measured at the central frontal part (CH, Fz) of the measurement position, and the result of α / β displayed on the display unit 7 was obtained in each activation. , (1) 6.8, (2) 2.5, (3) 1.3. Here, the activation given to the subject is a complicated task in the order of (1) <(2) <(3), and naturally the cerebral cortex of the subject also has a higher degree of activation accordingly. It turns out to be.

【0027】

Looking at this result, the values of α / β are in the order of (1) <(2) <(3), and as the work becomes more complicated, that is, the thinking activity of the subject becomes more complicated. Therefore, it is shown that the numerical value of α / β becomes lower. In other words, by calculating the ratio of the average power values for each frequency band of the brain wave by the apparatus according to the present embodiment, the activation status of the cerebral cortex of the subject can be quantitatively determined. It is possible to measure biological information such as psychological and physiological reactions reflected in this.

【0028】

Next, the second embodiment will be described. In this second embodiment, the frequency bands to be filtered are theta wave (4 to 8 Hz) and β wave (13 to 18 Hz), and the constituent device and the calculation process except that θ / β of both is calculated. Are all the same as in the first embodiment.

【0029】

In the evaluation of θ / β, when the changes in the values for various activations are examined, it can be seen that the larger the θ / β, the higher the concentration of the subject. In the present embodiment, the subject is given three types of activations: (1) resting with eyes closed, (2) executing the calculation task while listening to music, and (3) executing the calculation task. According to the processing process described, θ / β is calculated for the brain wave measured at the central frontal part (CH.Fz) of the measurement position. As a result, the results of θ / β displayed on the display unit 7 were (1) 1.2, (2) 2.1, and (3) 3.3 in each activation.

【0030】

Here, the activation given to the subject is set as the content that increases the concentration of the subject in the order of (1) <(2) <(3), and the value of θ / β is also (1). The order is <(2) <(3), indicating that the value of θ / β increases as the subject's concentration increases.

【0031】

In this way, by calculating the ratio of the average power values for each frequency band of the brain waves as in the previous embodiment, the activation status of the cerebral cortex of the subject can be quantitatively determined. , It becomes possible to measure biological information such as psychological and physiological reactions reflected in this.

【0032】

Subsequently, a third embodiment will be described. This third embodiment has the same configuration as the processing apparatus of the first embodiment shown in FIG. 2, and is the ratio of the average power values of each frequency band in the arithmetic control device 5 of FIG. Only the calculation process of and the evaluation of biological information by α / β are different from the first embodiment.

【0033】

Therefore, regarding the present embodiment, the processing process after the calculation process of the ratio of the average power value of each frequency band different from the first embodiment will be described, and the processing process before this is the first embodiment. It is omitted because it is the same as. As for the activation given to the subject, (3) a highly difficult calculation task in the first embodiment is set.

【0034】

FIG. 6 is a schematic representation of this calculation process. First, in the process of calculating the average power value in each frequency band from the signal of each frequency band obtained by filtering the brain wave signal, an arbitrary calculation is performed in advance. The time interval is set, and the FFT is applied to the data string corresponding to the time width to calculate the power spectrum. In FIG. 6, the detailed diagram of the calculation process is shown only for the α wave band. The processing process for other frequency bands is the same as the processing process for the α wave in FIG.

【0035】

Further, the power value is added in the obtained power spectrum and averaged in the frequency band to obtain the average power value. Then, the ratio of the average power values of the α wave and the β wave calculated in this way is obtained, and α / β is calculated.

【0036】

Subsequently, as shown in FIG. 6, the power spectrum calculated from the same number of data strings as the above calculation process shifted by the number of data corresponding to the predetermined time width set in advance ... Repeat in the same way for α / β time series data.

【0037】

In this embodiment, the preset time width is set to 3 seconds, which corresponds to 7200 pieces of data. By continuing the above calculation process, a time-varying sequence of the ratio of the average power values in each frequency band can be obtained. The calculated time-varying ratio is stored in the external storage unit 6 and displayed on the display unit 7 or printed by the printing unit 8 as necessary, and the evaluator evaluates the biometric information of the subject. ..

【0038】

FIG. 7 shows the analysis results displayed on the display unit 7 in the present embodiment. Further, FIG. 8 shows the time change of the average power value of each of the α wave and β wave used in the calculation of α / β in the analysis process in the present embodiment.

【0039】

First, looking at FIG. 8, it can be seen that the time changes of the power average values of the α wave and the β wave are partially synchronized with each other. That is, it is considered that this is due to the general Waxing & Waning phenomenon, and it can be imitated that it is a property different from the time change of the thinking activity of the subject.

【0040】

Looking at Fig. 7, since the Waxing & Waning of α wave and β wave are offset by calculating α / β, the time change of α / β in Fig. 7 is truly the time of the subject's thinking activity. It is thought to indicate a change. That is, it can be determined that the thinking activity of the subject in the present embodiment was activated after about 15 seconds, 35 seconds, and 42 seconds from the time change of α / β in FIG. 7.

【0041】

As described above, according to the present embodiment, Waxing & Waning that occurs synchronously between each frequency band by calculating the ratio of each predetermined combination of two types of time-series average power values for each frequency band. It is possible to absorb the influence of Waxing & Waning and capture the time fluctuation of the human mental state.

【0042】

Subsequently, the fourth embodiment shown in FIGS. 9 and 10 will be described. In this fourth embodiment, the frequency bands to be filtered are theta wave (4 to 8 Hz) and β wave (13 to 18 Hz), and θ / β of both is calculated and given to the subject. The components and the calculation process are all the same as those in the third embodiment, except that the activation is different. The activation given to the subject sets the calculation task of (3) in the second embodiment.

【0043】

FIG. 9 shows the analysis result displayed on the display unit 7. Further, FIG. 10 shows the time change of the average power value of each of the θ wave and β wave used for calculating θ / β in the analysis process in the present embodiment.

【0044】

Looking at FIG. 10, it can be seen that the time changes of the power average values of the θ wave and the β wave are partially synchronized with each other. That is, it is considered that this is due to the general Waxing & Waning phenomenon, and it can be imitated that it is a property different from the time change of the thinking activity of the subject.

【0045】

Looking at FIG. 9, since the Waxing & Waning of theta wave and β wave are offset by calculating θ / β, the time change of θ / β in FIG. 9 is truly the time of the subject's concentration. It is thought to indicate a change. That is, it can be determined that the concentration of the subject in the present embodiment was activated about 30 seconds after the time change of θ / β in FIG.

【0046】

As described above, according to the present embodiment, Waxing & Waning that occurs synchronously between each frequency band by calculating the ratio of each predetermined combination of two types of time-series average power values for each frequency band. It is possible to absorb the effects of Waxing & Waning and capture changes in human mental status.

【0047】

FIG. 11 is a block circuit configuration diagram of the fifth embodiment, in which the device according to the third embodiment is applied to a subject who performs document proofreading work for a certain period of time, and further, the measurement result is applied to the subject. It is a device that controls the target to be stimulated by returning to. With respect to the configuration diagram of FIG. 2, the output of the arithmetic control device 5 is connected to the massage chair 12 via the control device 11.

【0048】

In the present embodiment, the subject decides to proofread the documents for 10 minutes. Further, in FIG. 11, a massage chair 12 is installed as a stimulating device for stimulating the subject. The control device 11 controls the operation of the massage chair 12 in response to a control signal from the arithmetic control device 5. FIG. 12 shows a graph of the time change of α / β in this embodiment.

【0049】

Here, a threshold value for α / β is set in advance in the arithmetic control device 5, and the following provisions are provided for the massage chair 12 on which the subject sits as a stimulator according to the calculated relationship with α / β. Send a control signal. α / β <0.9: Stop 0.9 α / β <1.2: Low speed operation 1.2 α / β: Fast operation [0050]

As a result, when α / β rises, that is, when complicated thinking activity decreases due to the influence of fatigue, etc., the subject will be massaged by the massage chair 12, and it will be possible to reduce fatigue, resulting in complexity. You can get a recovery of thinking activity. In addition, when the massage chair 12 is continuously operated for a long period of time, the subject can choose to take a rest as appropriate in consideration of the decrease in his / her thinking activity.

【0051】

Note that FIG. 13 shows a graph of the time change of θ / β in this case.

【0052】

In the present embodiment, the massage chair 12 is used as the stimulator, but other devices such as a low-frequency treatment device that give a useful stimulus to the living body can also be used. As described above, according to the present embodiment, it is possible to realize a real-time control system by utilizing the time change of biological information.

【0053】

As described above, according to the first to sixth embodiments, the average power value is calculated for each of two or more predetermined frequency bands filtered from the brain wave, and the average power value is calculated for each of the two predetermined combinations. By calculating the ratio, it becomes possible to capture the biometric information obtained from the interrelated frequency bands in a complex manner, and it is possible to evaluate the advanced mental state of human beings.

【0054】

Further, by calculating the ratio of the average power value for each combination of the two predetermined values for each frequency band, it is possible to absorb the Waxing & Waning that occurs synchronously between the frequency bands. This makes it possible to eliminate the effects of Waxing & Waning and capture the temporal fluctuations of the human mental state.

【0055】

It is also possible to realize a real-time control system by utilizing the time change of these biological information.

【0056】

[Effect of the invention]

As described above, the electroencephalogram analysis method according to the present invention calculates the average power value in each of two or more predetermined frequency bands filtered from the brain wave, and the average power value is calculated for each of the two predetermined combinations. By calculating the ratio, it becomes possible to capture the biometric information obtained from the interrelated frequency bands in a complex manner, and it is possible to evaluate the advanced mental state of human beings.

【0057】

Further, the brain wave analysis method according to the present invention is, for example, objective and quantitative measurement (sensitivity evaluation) of biological reaction to a product or work, measurement of biological reaction such as comfort / discomfort to the environment in which the living body is placed, or biological reaction of the living body. It can be used for clinical / research, etc. for measuring psychological / physiological conditions. It can also be used as a method or device for controlling a living body or an object that stimulates a living body by returning these measurement results.

【0058】

Further, by calculating the ratio of the average power value for each frequency band for each of the two predetermined combinations, it is possible to absorb the Waxing & Waning that occurs synchronously between the frequency bands. This makes it possible to eliminate the effects of Waxing & Waning and capture the temporal fluctuations of the human mental state.

[Simple explanation of drawings]

[Figure 1]

It is explanatory drawing of the processing process.

[Figure 2]

It is a block circuit block diagram of the processing apparatus of 1st Embodiment.

[Fig. 3]

It is explanatory drawing of the measurement method of an electroencephalogram.

[Fig. 4]

It is a graph figure of the measured electroencephalogram signal.

[Fig. 5]

It is explanatory drawing of the calculation process of α / β in 1st Embodiment.

[Fig. 6]

It is explanatory drawing of the calculation process of α / β in the 3rd Embodiment.

[Fig. 7]

It is a graph of the time change of α / β in the third embodiment.

[Fig. 8]

It is a graph of the time change of the average power value of α wave and β wave in the 3rd Embodiment.

[Fig. 9]

It is a graph of the time change of θ / β in the 4th embodiment.

[Fig. 10]

It is a graph of the time change of the average power value of theta wave and β wave in the 4th embodiment.

[Fig. 11]

It is a block circuit block diagram of the processing apparatus of 5th Embodiment.

[Fig. 12]

It is a graph of the time change of α / β in the fifth embodiment.

[Fig. 13]

It is a graph of the time change of θ / β in the sixth embodiment.

[Explanation of symbols]

1 EEG measuring device 2 Pre-main amplifier 3 A / D converter 4 Data retention unit 5 Arithmetic control device 6 External storage 7 Display 8 Printing department 9 electrodes 10 paste 11 Control unit 12 Massage Cheer