WO2015083787A1

WO2015083787A1 - Biological state determination device and computer program

Info

Publication number: WO2015083787A1
Application number: PCT/JP2014/082101
Authority: WO
Inventors: 藤田　悦則; 小倉　由美; 竜一内川; 堀川　正博
Original assignee: 株式会社デルタツーリング
Priority date: 2013-12-07
Filing date: 2014-12-04
Publication date: 2015-06-11
Also published as: JP2015112117A

Abstract

　To specify and detect a change in a biological state based on a disruption in a biological rhythm. The present invention has a configuration whereby it is determined on the basis of a frequency-gradient time-series waveform, and preferably a frequency-gradient time-series waveform obtained using a zero crossing point, whether or not a function adjustment signal that has a frequency below the changeover frequency of a cardiovascular fluctuation characteristic continues at least for a predetermined time. A disruption in the circadian clock, i.e., the biological rhythm, is clearly reflected in a long-period frequency component (function adjustment signal). In particular, the disruption has a strong effect on a frequency-gradient time-series waveform obtained using a zero crossing point. The disruption is therefore suitable for detecting a specific biological phenomenon emergence period brought about by a disruption in the biological rhythm such as jet lag.

Description

Biological state determination device and computer program

The present invention relates to a biological state determination apparatus and a computer program for determining a human state using a biological signal.

The present applicant obtains a time series waveform of a frequency from a time series waveform of a biological signal which is mainly a wave of the cardiovascular system collected from a human upper body in Patent Document 1 and Patent Document 2, and the frequency gradient. An apparatus having a means for determining a human state by obtaining a time series waveform of these and performing frequency analysis on these waveforms is disclosed. In Patent Document 1, in frequency analysis, power spectra of respective frequencies corresponding to a function adjustment signal, a fatigue reception signal, and an activity adjustment signal belonging to a predetermined ULF band (very low frequency band) to a VLF band (very low frequency band). Ask for. And a person's state is judged from the time series change of each power spectrum. Since the fatigue acceptance signal indicates the degree of progress of fatigue in the normal activity state, in addition to this, by comparing the dominant degree of the power spectrum of the function adjustment signal and the activity adjustment signal, the human condition (relaxed state, fatigue) Status, sympathetic dominant state, parasympathetic dominant state, etc.).

Patent Document 2 uses a function adjustment signal, fatigue acceptance signal, and activity adjustment signal belonging to the ULF band (very low frequency band) to the VLF band (very low frequency band) as in Patent Document 1, but in Patent Document 2, The distribution ratio of each frequency component when the sum of the power spectrum values of the frequency components corresponding to the three signals is set to 100 is obtained in a time series, and the human state is determined using the time series change of the distribution ratio. .

The technology of

Patent Document

1 or 2 is based on the following knowledge. That is, human constancy is maintained with fluctuations, and the frequency bands are in the ULF band and the VLF band. On the other hand, in atrial fibrillation, which is one of heart diseases, the frequency at which the characteristics of fluctuations in the cardiovascular system are switched is said to be 0.0033 Hz. By detecting fluctuations in the vicinity of 0.0033 Hz, homeostasis is obtained. Information on maintenance is obtained (see Non-Patent Document 1). The frequency bands below 0.0033 Hz and below 0.0053 Hz are mainly related to body temperature regulation, and the frequency band from 0.01 to 0.04 Hz is said to be related to autonomic nerve control. Yes. Then, a frequency-gradient time series waveform for calculating these low-frequency fluctuations inherent in the biological signal is actually obtained and subjected to frequency analysis. As a result, the frequencies near 0.0017 Hz and 0.0033 Hz are lower than 0.0033 Hz. It was confirmed that there were fluctuations in the frequency band centered on 0.0035 Hz and, in addition to these two, fluctuations in the frequency band centered on 0.0053 Hz.

The 0.0035 Hz signal (fatigue acceptance signal) is a fluctuation for maintaining homeostasis in response to externally input stress, and is a signal indicating the progress of fatigue in a normal activity state. The .0053 Hz signal (activity adjustment signal) is a signal in which the degree of influence due to the control of endocrine hormones during activity appears, and the 0.0017 Hz signal (function adjustment signal) lower than 0.0033 Hz is These signals are used to control body modulation and functional degradation, and these three frequency band signals interact with each other and act as a body temperature regulation function. Therefore, it is possible to determine the state of a person by using the time series change and distribution rate of the power spectrum of these signals.

JP 2011-167362 A JP 2012-179202 A

The means shown in

Patent Documents

1 and 2 adopt a pulse wave (Aortic Pulse Wave (APW)) that is a vibration generated on the body surface of a human back as a biological signal and is not restrained. It is excellent as a means for detecting and obtaining biological information during driving. However, the techniques shown in

Patent Documents

1 and 2 are mainly intended to detect a sleep onset sign phenomenon, an imminent sleep phenomenon, and the like that come as a result of fatigue progressing due to various operations such as driving.

On the other hand, sleep and awakening are circadian rhythms with a period of about 24 hours (circadian rhythms), circadian rhythms with a period of about 12 hours (circusedian rhythms), super-day rhythms with a period of about 2 hours (ultradian rhythms), etc. It is regulated by biological rhythm. These biological rhythms are engraved by a biological clock, which is reset by being exposed to light every morning and then engraves the biological rhythm described above. However, the biological rhythm is disturbed (so-called jet lag) due to, for example, movement by airplane between regions having a time difference of several hours or more. In addition, disturbance of biological rhythm may occur due to overnight work or the like. However, even in such a state in which the biological rhythm is disturbed, for example, at dawn all night, if the wake-up continues even after the normal wake-up time, a phenomenon of drowsiness occurs. This is because sleep and wakefulness are controlled by the body clock, and attention must be paid to normal activities and work, especially when driving, despite this state.
If you can objectively capture the appearance of the above-mentioned biological condition due to disturbance of biological rhythm represented by jet lag, you can suspend work for a while or give leave until the cause of jet lag is resolved Is possible.

The techniques of

Patent Documents

1 and 2 are effective in detecting changes in the biological state such as a sleep onset symptom and an imminent sleep phenomenon accompanying the progress of fatigue. Without distinguishing between these changes, detection is performed in the change of the biological state accompanying the progress of fatigue. That is, there is no specific determination method for detecting a change in the biological state based on the disturbance of the biological rhythm separately from the change in the biological state accompanying the progress of fatigue.

This invention is made in view of the above, and makes it a subject to provide the technique which can identify and detect the change of the biological state based on disturbance of a biological rhythm.

As a result of intensive studies to solve the above problems, the present inventor has focused on the following points. That is, normal sleepiness accompanying the progress of fatigue occurs as a result of cooperation with the homeostasis mechanism as well as control by the body clock. In obtaining the time-series waveform of the gradient of the frequency of the biological signal for determining the biological state of the person, the applicant of the present invention uses a method using the peak point of the time-series waveform of the biological signal and a method using the zero-cross point as described in

Patent Documents

1 and 2 above. Have already proposed. Since the time-series waveform of the frequency gradient obtained using the peak point is a biological signal corresponding to the heart rate, it reflects the control result by the homeostasis mechanism. Therefore, in the case of the technique using the peak point, it is considered that the influence of the disturbance of the biological clock, that is, the biological rhythm is small. Therefore, the present inventor paid attention to the time-series waveform of the frequency gradient using the zero cross point, and in particular, when the disturbance of the biological rhythm occurs in the long-period component, a phenomenon different from the normal progress of fatigue And the present invention has been completed.

That is, the biological state determination device of the present invention is a biological state determination device that determines a biological state by analyzing a biological signal collected by the biological signal measurement device,
After obtaining the time series waveform of the frequency from the time series waveform of the biological signal, the frequency gradient time series waveform calculating means for calculating the time series waveform of the frequency by sliding the time series waveform of the frequency,
From the frequency gradient time series waveform obtained by the frequency gradient time series waveform calculation means, a function adjustment signal having a frequency lower than the frequency at which the fluctuation characteristics of the cardiovascular system are switched, a fatigue acceptance signal having a frequency higher than the function adjustment signal, And a distribution ratio calculation means for extracting each frequency component belonging to the VLF band from the ULF band corresponding to the activity adjustment signal having a frequency higher than that of the fatigue acceptance signal, and obtaining each distribution ratio of these frequency components in time series,
In the distribution ratio calculating means, when the distribution ratio of the function adjustment signal is higher than the distribution ratio of the fatigue acceptance signal and the activity adjustment signal for a predetermined time, a biological phenomenon caused by disturbance of biological rhythm And determining means for determining the appearance period.
The determination means is a time zone in which the distribution ratio of the function adjustment signal is high, and a time zone in which the order of the distribution ratio of the function adjustment signal, the fatigue acceptance signal, and the activity adjustment signal is the same continues for a predetermined time. In addition, it is preferable to determine that the biological phenomenon appears due to the disturbance of the biological rhythm.
The frequency gradient time-series waveform calculating means preferably has means for obtaining a time-series waveform of frequencies using a zero cross point in the time-series waveform of the biological signal.

The computer program of the present invention is a computer program that causes a computer as a biological state determination device to execute a procedure for analyzing a biological signal collected by a biological signal measurement device and determining a biological state.
After obtaining the time series waveform of the frequency from the time series waveform of the biological signal, the frequency time series waveform calculating procedure for calculating the time series waveform of the frequency by sliding calculation of the time series waveform of the frequency,
From the frequency gradient time series waveform obtained by the frequency gradient time series waveform calculation procedure, a function adjustment signal having a frequency lower than the frequency at which the fluctuation characteristics of the cardiovascular system are switched, a fatigue acceptance signal having a frequency higher than the function adjustment signal, And a distribution ratio calculation procedure for extracting each frequency component belonging to the VLF band from the ULF band corresponding to the activity adjustment signal having a frequency higher than that of the fatigue acceptance signal, and obtaining each distribution ratio of these frequency components in time series,
In the distribution ratio calculation procedure, when the distribution ratio of the function adjustment signal is higher than the distribution ratio of the fatigue acceptance signal and the activity adjustment signal for a predetermined time, a biological phenomenon caused by disturbance of biological rhythm A determination procedure for determining the appearance period is executed.
The determination procedure is a time zone in which the distribution rate of the function adjustment signal is high, and a time zone in which the order of the distribution rate of the function adjustment signal, the fatigue acceptance signal, and the activity adjustment signal is the same continues for a predetermined time. In addition, it is preferable to determine that the biological phenomenon appears due to the disturbance of the biological rhythm.
In the frequency gradient time series waveform calculation procedure, it is preferable to obtain a time series waveform of a frequency using a zero cross point in the time series waveform of the biological signal.

The present invention obtains whether or not a function adjustment signal having a frequency lower than the frequency at which the fluctuation characteristics of the cardiovascular system are switched continues for a predetermined time or more using a time-series waveform of the frequency gradient, preferably a zero cross point. In this case, the determination is made in the time-series waveform of the slope of the frequency. As described above, the disturbance of the biological clock, that is, biological rhythm, appears prominently in the long-period frequency component (function adjustment signal), and particularly affects the time-graded waveform of the frequency gradient using the zero cross point. It is suitable for detecting a specific biological phenomenon appearance period caused by disturbance of biological rhythm such as blurring.

FIG. 1 is a perspective view showing an example of a back body surface pulse wave measuring device for measuring a back body surface pulse wave used in an embodiment of the present invention. FIG. 2 is a diagram schematically showing the configuration of the biological state estimation apparatus according to one embodiment of the present invention. FIG. 3 shows an example of a frequency gradient time-series waveform in the experimental example, where (a) shows the data on the first day of return and (b) shows the data in the normal state. FIG. 4 shows an example of a time-series waveform of the distribution rate in the experimental example, where (a) shows the data on the first day of return and (b) shows the data in the normal state. FIG. 5 shows a t-test comparing the post-return and normal conditions for the duration in which the distribution rate of the function adjustment signal 0.0017 Hz is the highest and the distribution order of the distribution rates of the three frequency components remains unchanged. It is the figure which showed the result. FIG. 6A shows a time-series waveform of a frequency gradient according to another example, FIG. 6B shows a time-series waveform of the distribution rate of FIG. 6A, and FIG. 6C shows a drowsy driving warning device. It is the figure which showed the output result.

Hereinafter, the present invention will be described in more detail based on the embodiments of the present invention shown in the drawings. Examples of the biological signal collected in the present invention include fingertip volume pulse wave, back body surface pulse wave (APW), and the like, and preferably back body surface pulse wave (APW). The dorsal body surface wave (APW) is a vibration generated from the motion of the heart and aorta detected from the back of the upper body of a person. It includes elasticity information and elasticity information based on blood pressure. The signal waveform associated with heart rate variability includes sympathetic and parasympathetic nervous system activity information (parasympathetic activity information including the compensation of sympathetic nerves), and the signal waveform associated with aortic oscillation is sympathetic. Contains information on neural activity.

A biological signal measuring device for collecting a biological signal can use a fingertip plethysmograph if it is a fingertip plethysmogram, and if it is a back body surface pulse wave (APW), for example, a pressure sensor Although it is possible to use, a waveguide type sensor used in a drowsy driving warning device (Sleep Buster (registered trademark)) manufactured by Delta Touring Co., Ltd. can be preferably used. FIG. 1 shows a schematic configuration of a back body surface pulse wave measuring apparatus 1 comprising this waveguide type sensor.

The back body surface pulse wave measuring device 1 includes a core pad 11 made of a plate-like bead foam, and a tertiary placed in two through-holes 11a formed in the core pad 11 with a portion corresponding to the spine interposed therebetween. The original three-dimensional knitted fabric 12, a sensor 13 attached to the three-dimensional three-dimensional knitted fabric 12, and

films

14 and 15 disposed on both sides of the three-dimensional three-dimensional knitted fabric 12 are configured. Further, plate-

like foams

16 and 17 made of bead foam are laminated on the front and back surfaces of the core pad 11. The back body surface pulse wave measuring device 1 is used, for example, attached to a seat back of a vehicle seat or attached in the vicinity corresponding to the back of a bed. When the back body surface pulse wave measuring device 1 is pressed by a person's back, the vibration of the body surface due to a biological signal causes membrane vibration on the core pad 11 and the

films

14 and 15 via one plate-like foam 16. Then, string vibration is generated in the connecting yarn of the three-dimensional solid knitted fabric 12, and film vibration is generated in the other plate-like foam 17 to be propagated. The back body surface pulse wave measuring device 1 has a function of substantially amplifying a weak biological signal by such membrane vibration and string vibration, and the biological signal is reliably detected by the sensor 13.

Next, the configuration of the biological state determination device 100 of the present embodiment will be described with reference to FIG. The biological state determination device 100 includes a frequency gradient time series waveform calculation unit 110, a distribution rate calculation unit 120, a determination unit 130, and the like, and the back portion obtained from the sensor 13 of the back body surface pulse wave measurement device 1 by them. Body surface pulse wave (APW) is analyzed. The biological state determination apparatus 100 includes a computer (including a microcomputer), and causes a storage unit of the computer to execute a frequency gradient time-series waveform calculation procedure that functions as the frequency gradient time-series waveform calculation unit 110, thereby distributing the distribution rate. A computer program for executing the distribution ratio calculation procedure that functions as the calculation means 120 and for executing the determination procedure that functions as the determination means 130 is set. The computer program can be provided by being stored in a recording medium such as a flexible disk, hard disk, CD-ROM, MO (magneto-optical disk), DVD-ROM, or memory card, or transmitted through a communication line. Is possible.

The frequency gradient time series waveform calculation means 110 is a time series waveform (hereinafter referred to as “original waveform”) of the back body surface pulse wave (APW) obtained from the sensor 13 of the back body surface pulse wave measuring device 1. The waveform includes the waveform after filtering components that are not used for analysis of body movements, etc.)), and after calculating the frequency time-series waveform, sliding the frequency time-series waveform to calculate the slope of the frequency Find the time series waveform.

As a method of obtaining a time-series waveform of the frequency gradient, as disclosed in

Patent Documents

1 and 2, a point (zero-cross point) where the back body surface pulse wave (APW) switches from positive to negative in the time-series waveform is disclosed. Two methods, a method to be used (zero cross method) and a method to obtain a time series waveform using a local maximum value (peak point) by smoothing and differentiating the time series waveform of the back body surface pulse wave (APW) (peak detection method) There is.

In the zero cross method, when the zero cross point is obtained, it is divided every 5 seconds, for example, and the reciprocal of the time interval between the zero cross points of the time series waveform included in the 5 second is obtained as the individual frequency f. The average value of the individual frequency f is adopted as the value of the frequency F for 5 seconds. Then, by plotting the frequency F obtained every 5 seconds in time series, a time series waveform of frequency fluctuation is obtained.

In the peak detection method, the maximum value of the original waveform of the back body surface pulse wave (APW) is obtained by, for example, the smoothing differential method using Savitzky and Golay. Next, for example, the local maximum value is divided every 5 seconds, the reciprocal of the time interval between the local maximum values of the time-series waveform included in the 5 seconds is obtained as the individual frequency f, and the average value of the individual frequency f in the 5 seconds is calculated This is adopted as the value of the frequency F for 5 seconds. Then, by plotting the frequency F obtained every 5 seconds in time series, a time series waveform of frequency fluctuation is obtained.

The frequency gradient time-series waveform computing means 110 has a predetermined overlap time (for example, 18 seconds) and a predetermined time width (for example, 180 seconds) from the time-series waveform of the frequency fluctuation obtained by the zero cross method or the peak detection method. A time window is set, a frequency gradient is obtained for each time window by the method of least squares, and a time series waveform of the gradient is output. This calculation (movement calculation) is sequentially repeated to output a time series change in the APW frequency slope as a frequency slope time series waveform.

The dorsal body surface wave (APW) is a biological signal mainly including the state of control of the heart, which is the central system, that is, the state of sympathetic innervation of the artery, and the appearance information of the sympathetic nervous system and the parasympathetic nervous system. The frequency gradient time series waveform obtained by the zero-cross method is related to the state of control of the heart and reflects the appearance of the sympathetic nerve, but the frequency slope time series waveform obtained by the peak detection method. Is more related to heart rate variability. Therefore, in the case of the technique using the peak detection method, it is considered that the influence on the disturbance of the biological clock, that is, biological rhythm, is small, and it is necessary to detect the appearance period of a specific biological phenomenon caused by the disturbance of biological rhythm such as jet lag. It is preferable to obtain a frequency gradient time series waveform using the zero cross method.

The distribution rate calculating means 120 first analyzes the frequency inclination time series waveforms obtained from the frequency inclination time series waveform calculating means 110, respectively, and from the above 0.0033 Hz which is a frequency at which the fluctuation characteristics of the cardiovascular system are switched. Each frequency component belonging to the VLF band is extracted from the ULF band corresponding to the lower frequency function adjustment signal, the fatigue acceptance signal having a higher frequency than the function adjustment signal, and the activity adjustment signal having a higher frequency than the fatigue acceptance signal. Next, the distribution ratios of these frequency components are obtained in time series. That is, the ratio of each frequency component when the sum of the power spectrum values of the three frequency components is 1 is obtained as a distribution rate in time series.

In this embodiment, a frequency component of 0.0017 Hz is used as the function adjustment signal, a frequency component of 0.0035 Hz is used as the fatigue acceptance signal, and a frequency component of 0.0053 Hz is used as the activity adjustment signal. The use of the components is appropriate as described above in the section “Background Art”. The frequency component of each signal can be adjusted according to individual differences, etc., the function adjustment signal is less than 0.0033 Hz, preferably 0.001 to 0.0027 Hz, and the fatigue acceptance signal is 0. In the range of 002 to 0.0052 Hz, the activity adjustment signal can be adjusted in the range of 0.004 to 0.007 Hz.

In the distribution ratio calculation means 120, the determination means 130 causes the disturbance of the biological rhythm when the distribution ratio of the function adjustment signal is higher than the distribution ratio of the fatigue acceptance signal and the activity adjustment signal for a predetermined time. It is determined that the biological phenomenon appears. As described above, the function adjustment signal is used as a signal for controlling body modulation and function deterioration, and therefore, the disturbance of the biological clock, that is, biological rhythm is easily reflected.

Preferably, in the time zone in which the distribution ratio of the function adjustment signal is high, the determination unit 130 determines that the time zone in which the order of the distribution ratio of the function adjustment signal, the fatigue acceptance signal, and the activity adjustment signal is the same is a predetermined time. When continuing, it determines with the biological phenomenon appearance period which causes disturbance of biological rhythm. In other words, the fact that there is no change in the order of the signals is considered to indicate a state in which the biological fluctuations between them are small, that is, a so-called vacant state.

(Experimental example)
In order to verify the validity of the determination method of the present invention, the present applicant uses a person who has returned from abroad as a test subject and uses the back body surface pulse wave measuring device 1 in the seat back of the driver's seat in a state of jet lag. A running experiment was carried out in which a test car was run with the mounted car. A case of a representative subject will be described.

This test subject is a male in his 50s. April 2013: Germany (8 hours time difference), June 2013: Germany (8 hours time difference), July 2013: USA (14 hours time difference), 2013 9 Month: Measurements were taken from the first day after returning from Germany (8 hours time difference) to the fourth day after returning. The total number of measurements is 19 times. And in the normal state where the same subject is aware that there is no sleepiness or fatigue and the arousal level is high, the same running experiment was performed 20 times and compared with the measurement result.
The relationship between the number of travels and travel time is shown in the following table.

In the analysis, the frequency gradient time series waveform calculation means 110 calculates the frequency for 5 seconds by the zero cross method, calculates the frequency gradient time series waveform by sliding calculation with a time width of 180 seconds and an overlap time of 18 seconds, and calculates the distribution ratio. In the means 120, frequency analysis is performed on the frequency gradient time series waveform by the zero cross method, and the time series of the distribution ratio of the function adjustment signal (0.0017 Hz), the fatigue acceptance signal (0.0035 Hz), and the activity adjustment signal (0.0053 Hz). The waveform was obtained. Representative examples of the results (comparison between the first day of return and normal conditions) are shown in FIGS.

FIG. 3 shows the frequency gradient time-series waveform obtained by the frequency gradient time-series waveform calculating means 110, and the waveform on the first day of returning to Japan is longer than the normal state.

Referring to the distribution rate of FIG. 4, on the first day of return, the distribution rate of 00017 Hz is the highest, and the state where the order of the distribution rates of the three frequency components does not change is characterized by continuing for a predetermined time. That is, the time zone in which 0.0017 Hz, 0.0035 Hz, and 0.0053 Hz appear in the order of higher distribution rate continues from about 15 minutes to about 32 minutes after the start of measurement. On the other hand, in the normal state, there is no time zone in which 0.0017 Hz continues at the highest distribution rate for 10 minutes or more, or the order of each frequency component remains constant and unchanged for 10 minutes or more. The distribution rate of each frequency component changes drastically.

Table 2 summarizes the durations with the highest distribution rate of 0.0017 Hz and no change in the order of the distribution rate heights of the three frequency components.

From Table 2, it can be seen that the above duration time is generally longer for 4 days of return compared to normal conditions. In addition, comparing the first day of return to the fourth day of return, the above duration is the longest on the first day of return, and the above duration is gradually shortened from the second day of return, the third day of return, and the fourth day of return. The tendency to become was seen.

Fig. 5 shows the average values and standard deviations of the above durations, divided into four days of return and normal conditions. The t test was p = 0.03 (<0.05), and a significant difference was observed for the duration.

Next, using Bayesian estimation, the distribution rate of 0.0017 Hz is the highest, and based on the duration without any change in the order of the distribution rate heights of the three frequency components, “after returning home” (here 4 after returning home) Probability estimated to be within a day). Table 3 shows the results of Bayesian estimation.

According to Table 3, the distribution rate of 0.0017 Hz is the highest, and the longer the duration without change in the order of the distribution rate heights of the three frequency components, the higher the probability of being estimated “after returning home”. Recognize.

As described above, the distribution rate of 0.0017 Hz, which is the function adjustment signal, is the highest, and the living body rhythm disturbance is caused by the length of the duration without change in the order of the distribution rate height of the three frequency components. It turns out that the phenomenon appearance period can be estimated.

Fig. 6 shows typical results when a man in his 50s, same as above, conducted a driving experiment similar to the above on November 1, 2013: the first day after returning from the United States (14 hours time difference). It is a figure. (A) is a frequency gradient time series waveform obtained by using the zero cross method and the peak detection method, respectively, and (b) is three frequency components obtained from the frequency gradient time series waveform using the zero cross method of (a). It is a time series waveform of the distribution rate.

As shown in FIG. 6B, 0.0017 Hz increases from around 21 minutes after the start of measurement, and the distribution rate increases in the order of 0.0017 Hz, 0.0035 Hz, and 0.0053 Hz from 21 minutes to 25 minutes. It can be seen that there is no change. In the vicinity of 25 minutes after the start of measurement, the order of 0.0035 Hz and 0.0053 Hz is switched, but thereafter, the same state continues from around 26 minutes to over 35 minutes. Accordingly, it is possible to estimate a biological phenomenon appearance period that is caused by disturbance of biological rhythm for about 21 to 25 minutes and about 26 to 35 minutes.

FIG. 6 (c) is an output result of a sleep driving warning device “Sleep Buster (registered trademark)” manufactured by Delta Touring Co., Ltd., which was measured at the same time. According to this output result, drowsiness reaches a warning level in the vicinity of 20 minutes when the distribution rate of 0.0017 Hz started to increase and in the vicinity of 25 minutes when the distribution rate of 0.0035 Hz and 0.0053 Hz changed. It has been determined. Also, a warning sound for inducing wakefulness is output in the vicinity of 27.5 minutes and 30 minutes in the middle of a state where the distribution ratio of 0.0017 Hz is high and the distribution ratio height of each frequency component is not changed. Yes (when the triangle is marked). Therefore, the distribution rate of 0.0017 Hz, which is the function adjustment signal, is the highest, and the appearance of the biological phenomenon caused by the disturbance of the biological rhythm due to the length of the duration without change in the order of the distribution rate height of the three frequency components The determination of the period coincides with the timing when sleepiness occurs, and it can be said that the determination is appropriate in that sense.

DESCRIPTION OF SYMBOLS 1 Back body surface pulse wave measuring apparatus 11 Core pad 12 Three-dimensional solid knitted fabric 13 Sensor 100 Living body state determination apparatus 110 Frequency inclination time series waveform calculation means 120 Distribution rate calculation means 130 Determination means

Claims

A biological state determination device that analyzes a biological signal collected by a biological signal measurement device and determines a biological state,
After obtaining the time series waveform of the frequency from the time series waveform of the biological signal, the frequency gradient time series waveform calculating means for calculating the time series waveform of the frequency by sliding the time series waveform of the frequency,
From the frequency gradient time series waveform obtained by the frequency gradient time series waveform calculation means, a function adjustment signal having a frequency lower than the frequency at which the fluctuation characteristics of the cardiovascular system are switched, a fatigue acceptance signal having a frequency higher than the function adjustment signal, And a distribution ratio calculation means for extracting each frequency component belonging to the VLF band from the ULF band corresponding to the activity adjustment signal having a frequency higher than that of the fatigue acceptance signal, and obtaining each distribution ratio of these frequency components in time series,
In the distribution ratio calculating means, when the distribution ratio of the function adjustment signal is higher than the distribution ratio of the fatigue acceptance signal and the activity adjustment signal for a predetermined time, a biological phenomenon caused by disturbance of biological rhythm A biological state determination apparatus comprising: determination means for determining an appearance period.
The determination means is a time zone in which the distribution ratio of the function adjustment signal is high, and a time zone in which the order of the distribution ratio of the function adjustment signal, the fatigue acceptance signal, and the activity adjustment signal is the same continues for a predetermined time. The biological state determination device according to claim 1, wherein the biological state appearance period is determined to be caused by disturbance of the biological rhythm.
3. The biological state determination device according to claim 1 or 2, wherein the frequency gradient time series waveform calculating means includes means for obtaining a time series waveform of a frequency using a zero cross point in the time series waveform of the biological signal.
A computer program for causing a computer as a biological state determination device to execute a procedure for analyzing a biological signal collected by a biological signal measurement device and determining a biological state,
After obtaining the time series waveform of the frequency from the time series waveform of the biological signal, the frequency time series waveform calculating procedure for calculating the time series waveform of the frequency by sliding calculation of the time series waveform of the frequency,
From the frequency gradient time series waveform obtained by the frequency gradient time series waveform calculation procedure, a function adjustment signal having a frequency lower than the frequency at which the fluctuation characteristics of the cardiovascular system are switched, a fatigue acceptance signal having a frequency higher than the function adjustment signal, And a distribution ratio calculation procedure for extracting each frequency component belonging to the VLF band from the ULF band corresponding to the activity adjustment signal having a frequency higher than that of the fatigue acceptance signal, and obtaining each distribution ratio of these frequency components in time series,
In the distribution ratio calculation procedure, when the distribution ratio of the function adjustment signal is higher than the distribution ratio of the fatigue acceptance signal and the activity adjustment signal for a predetermined time, a biological phenomenon caused by disturbance of biological rhythm A computer program for executing a determination procedure for determining an appearance period.
The determination procedure is a time zone in which the distribution rate of the function adjustment signal is high, and a time zone in which the order of the distribution rate of the function adjustment signal, the fatigue acceptance signal, and the activity adjustment signal is the same continues for a predetermined time. The computer program according to claim 4, wherein the computer program determines that the biological phenomenon appearance period is caused by disturbance of the biological rhythm.
6. The computer program according to claim 4, wherein the frequency gradient time-series waveform calculation procedure obtains a time-series waveform of frequency using a zero cross point in the time-series waveform of the biological signal.