JP6836264B2 - Biological condition estimation device, biological condition estimation method, computer program and recording medium - Google Patents

Description

The present invention relates to a technique for estimating the state of a living body by using a biological signal obtained from the back of a person.

In Patent Documents 1 and 2, the present inventors propose a technique for analyzing a human condition by detecting a vibration generated on the body surface of the back in the upper body of a human by a biological signal measuring device. The biological signals generated from the movement of the heart and aorta detected from the back of a person are pressure vibrations generated from the movement of the heart and aorta, and information on the systole and diastole of the ventricles and the blood vessel wall that serves as an auxiliary pump for circulation. It contains elasticity information and reflected wave information. That is, it is a biological signal including a back body surface pulse wave (Aortic Pulse Wave (APW)) in the vicinity of 1 Hz generated on the back surface from the movement of the heart and the aorta. The signal waveform associated with heart rate variability includes information on the nerve activity of the sympathetic nervous system and the parasympathetic nervous system, and the signal waveform associated with the rocking of the aorta contains information on the sympathetic nerve activity.

In Patent Document 1, the applicant has a means for obtaining a frequency time series waveform from APW time series data, further obtaining a time series waveform of frequency gradient and a time series waveform of frequency fluctuation, and performing frequency analysis of these. The device is disclosed. At the time of frequency analysis, it is also disclosed that the power spectrum of each frequency corresponding to the predetermined function adjustment signal, fatigue reception signal and activity adjustment signal is obtained, and the human state is determined from the time series change of each power spectrum. ing.

Further, in Patent Document 2, the applicant applies frequency analysis of APW time series data, obtains a regression line in relation to logarithmic power spectral density and logarithmic frequency, and determines a person's state from the shape of the regression line. Is disclosed.

Japanese Unexamined Patent Publication No. 2011-167362 Japanese Unexamined Patent Publication No. 2012-179202

Of the above, Patent Document 2 proposes a method of estimating a person's state from APW time-series data without obtaining a frequency gradient time-series waveform, and among APW, fluctuations that maintain human homeostasis. Signals in the frequency band of 0.001 to 0.04 Hz including the above are analyzed. Then, as described above, the fluctuation waveform obtained from the log-log axis display of the power spectral density is further divided into a plurality of frequency bands, a regression line is obtained for each of the divided frequency bands, and the slope of the regression line of each division is obtained. On the other hand, points are given based on a certain standard, and the judgment is made by considering the total points of those points and the number of break points between the regression lines of each division. This is because the determination of the state of Patent Document 2 determines various states such as fatigue state, illness and other disorders, functional recovery process state, drunkenness state due to alcohol intake, and transition of changes in those states. Because it is a thing, it analyzes a wide range of frequency bands in detail.

Therefore, the technique of Patent Document 2 is excellent in that the state of a person can be comprehensively determined from various aspects, but there is a problem that the load on the arithmetic processing unit of the computer and the amount of memory used are relatively large. there were.

On the other hand, for example, in dental practice where it is difficult to convey the intention during treatment while causing pain and discomfort to external stimuli, how much the patient feels the reaction to those external stimuli, that is, externally. If it is possible to objectively grasp the tactile sensitivity to a stimulus, it is expected that the burden on the patient will be further reduced and the treatment will be more appropriate. Of course, an objective grasp of pain and discomfort due to external stimuli may be necessary not only in dental practice but also in other medical practices, and in sports and health guidance.

The present invention has been made in view of the above, and a technique capable of estimating the tactile sensitivity to an external stimulus and reducing the load on the computer as compared with the conventional technique. The challenge is to provide.

In order to solve the above problems, the biological state estimation device of the present invention is a biological state estimation device that estimates a biological state by using a biological signal obtained from a biological signal measuring device that is in contact with the back of a person. The time series data of the biological signal is frequency-analyzed, and a frequency analysis means that outputs a fluctuation waveform showing the relationship between the logarithmic power spectrum density of 0.01 to 0.2 Hz and the logarithmic frequency and a regression line are obtained for the fluctuation waveform. At the same time, it is characterized by having a regression line analysis means for obtaining the inclination of the regression line and a tactile sensitivity estimating means for estimating the tactile sensitivity to an external stimulus as the biological state based on the inclination of the regression line.

A correlation data storage unit for storing correlation data between the inclination of the regression line measured in advance and the tactile sensitivity is provided, and the tactile sensitivity estimation means accesses the correlation data storage unit to access the correlation data storage unit to analyze the regression line. It is preferable that the tactile sensitivity is estimated by collating the slope of the regression line of the analysis target obtained in the above.
The tactile sensitivity estimating means stores the slope of the regression line in the normal state before the external stimulus is applied as reference data in the reference data storage unit, and the analysis target obtained by the regression line analysis means. It is also preferable to have a configuration in which the tactile sensitivity is estimated by comparing the slope of the regression line with the reference data.
The biological signal measuring device is provided on the backrest of the medical chair, and the frequency analysis means frequency-analyzes the biological signal obtained from the back of the patient sitting in the medical chair and estimates the tactile sensitivity. It is preferable to further include a display monitor that outputs the tactile sensitivity of the patient estimated by the means.

The biological state estimation method of the present invention is a biological state estimation method for estimating a biological state using a biological signal obtained from a biological signal measuring device abutting on the back of a person, and is time-series data of the biological signal. Is frequency-analyzed, a fluctuation waveform showing the relationship between the logarithmic power spectral density of 0.01 to 0.2 Hz and the logarithmic frequency is output, a regression line is obtained for the fluctuation waveform, and the slope of the regression line is obtained. It is characterized in that the tactile sensitivity to an external stimulus is estimated as the biological state by the slope of the regression line.

Accessing the correlation data storage unit that stores the correlation data between the slope of the regression line measured in advance and the tactile sensitivity, collating the slope of the regression line to be analyzed with the correlation data, and estimating the tactile sensitivity. Is preferable.
The slope of the regression line in the normal state before the external stimulus is applied is stored in the reference data storage unit as reference data, and the slope of the regression line to be analyzed is compared with the reference data. It is also preferable to estimate the tactile sensitivity.

The computer program of the present invention is a computer program that causes a computer as a biological state estimation device to analyze a biological signal obtained from a biological signal measuring device that is in contact with the back of a person and execute a procedure for estimating a biological state. Then, the time series data of the biometric signal is frequency-analyzed, a procedure for outputting a fluctuation waveform showing the relationship between the logarithmic power spectrum density of 0.01 to 0.2 Hz and the logarithmic frequency, and a regression line for the fluctuation waveform are obtained. At the same time, a procedure for obtaining the inclination of the regression line and a procedure for estimating the tactile sensitivity to an external stimulus as the biological state based on the inclination of the regression line are executed.

In the procedure for estimating the tactile sensitivity, the correlation data storage unit that stores the correlation data between the inclination of the regression line measured in advance and the tactile sensitivity is accessed, and the inclination of the regression line to be analyzed is collated with the correlation data. It is preferable to estimate the tactile sensitivity.
In the procedure for estimating the tactile sensitivity, the slope of the regression line in the normal state before the external stimulus is applied is stored in the reference data storage unit as reference data, and the slope of the regression line to be analyzed is stored. It is also preferable to estimate the tactile sensitivity in comparison with the reference data.
The present invention also claims 8 to 10 for causing a computer as a biological state estimation device to analyze a biological signal obtained from a biological signal measuring device abutting on the back of a person and execute a procedure for estimating a biological state. Provided is a computer-readable recording medium on which the computer program according to any one of 1 is recorded.

The present invention frequency-analyzes a biological signal (APW) obtained from a biological signal measuring device abutting on the back of a person, and shows a fluctuation showing the relationship between the logarithmic power spectral density of 0.01 to 0.2 Hz and the logarithmic frequency. The waveform is output, a regression line is obtained for this fluctuation waveform, and the tactile sensitivity to an external stimulus is estimated from the slope of the regression line. The frequency band of 0.01 to 0.2 Hz reflects the state of the sympathetic nervous system, which is enhanced by feeling pain and discomfort in response to external stimuli, and by narrowing down to that frequency band, a person can externally stimulate. You can know the tactile sensitivity you are feeling. Therefore, in dental treatment and the like, it is possible to grasp how much pain and discomfort the patient feels with respect to the treatment action during the treatment, and a more appropriate treatment action can be expected. Further, since the present invention limits the frequency band to be analyzed to those necessary for estimating the tactile sensitivity, the load on the arithmetic processing unit of the computer is small and the amount of memory used can be small. In addition, when determining the fluctuation waveform, the regression line drawn by the fluctuation waveform is unified and the judgment is made using the slope of the regression line. Therefore, in this respect as well, the load on the computer is higher than that of the conventional biological state estimation device. Can greatly contribute to the reduction of the above, and the output of the estimation result will be faster.

FIG. 1 (a) is an exploded view showing an example of a biological signal measuring device for measuring a back body surface pulse wave used in one embodiment of the present invention, and FIG. 1 (b) is a cross section of a main part thereof. It is a figure. FIG. 2 is a diagram schematically showing a configuration of a biological state estimation device according to an embodiment of the present invention. FIG. 3 is a diagram showing the relationship between treatment intensity and body movement in the experimental example. FIG. 4 is a diagram showing the relationship between the treatment intensity and the sympathetic nerve activity in the experimental example. FIG. 5 is a diagram showing the relationship between the treatment intensity and the slope of the regression line of the heart rate variability spectrum (fluctuation waveform) in the experimental example. FIG. 6A is a diagram showing the fluctuation waveform of subject A and the slope of the regression line in the experimental example, and FIG. 6B is a diagram showing the fluctuation waveform of subject B and the slope of the regression line in the experimental example. It is a figure. 7 (a) to 7 (e) are diagrams showing the relationship of the slopes of the regression lines of the frequency spectra (fluctuation waveforms) of the heart rate variability waveforms of all the subjects obtained by different frequency bands to be analyzed.

Hereinafter, the present invention will be described in more detail based on the embodiments of the present invention shown in the drawings. The biological signal collected in the present invention is a biological signal collected from the back. Since this biological signal is detected from the back of the upper body of a person, it is sound / vibration information generated from the movement of the heart and aorta, and information on the systole and diastole of the ventricle and the blood vessel wall that serves as an auxiliary pump for blood circulation. It includes elastic information of blood pressure, elastic information of blood pressure, and information of reflected waves, that is, back body surface pulse wave (APW) and pseudo heart sound information. It also contains information on the neural activity of the sympathetic nervous system, which is enhanced when a change in tactile sensitivity to an external stimulus, that is, pain or discomfort is felt.

As the biological signal measuring device for collecting biological signals, for example, a pressure sensor can be used, but it is preferably used in a sleep driving warning device (Sleep Buster (registered trademark)) manufactured by Delta Touring Co., Ltd. The biological signal measuring device 1 used is used. FIG. 1 shows a schematic configuration of the biological signal measuring device 1. This biological signal measuring device 1 can be used by being incorporated in the backrest of a chair, and can collect biological signals without restraining fingers.

Briefly explaining the biological signal measuring device 1, as shown in FIGS. 1A and 1B, the first layer 11, the second layer 12, and the third layer 13 are laminated in this order from the upper layer side. The first layer 11 having a layered structure and made of a three-dimensional three-dimensional knitted fabric or the like is used by being positioned on the human body side, which is a target for detecting a biological signal. Therefore, the sound / vibration information of the heart / vascular system including the biological signal from the back of the trunk of the human body, particularly the biological sound (direct trunk sound or bioacoustic signal) generated by the vibration of the ventricles, atrium, and large blood vessels. (Back body surface pulse wave (including APW)) is first propagated to the first layer 11 which is a biological signal input system. The second layer 12 functions as a resonance layer that emphasizes biological signals propagated from the first layer 11, particularly sounds and vibrations of the heart and vascular system by a resonance phenomenon or a beat phenomenon, and is a housing 121 made of bead foam or the like. , A three-dimensional three-dimensional knitted fabric 122 that functions as a natural oscillator, and a film 123 that causes membrane vibration. A microphone sensor 14 is arranged in the second layer 12 to detect sound / vibration information. The third layer 13 is laminated on the opposite side of the first layer 11 via the second layer 12, and reduces sound / vibration input from the outside.

Next, the configuration of the biological state estimation device 100 of the present embodiment will be described with reference to FIG. The biological state estimation device 100 includes a frequency analysis means 200, a regression line analysis means 300, and a tactile sensitivity estimation means 400. The biological state estimation device 100 is composed of a computer (including a microcomputer and the like), and stores a computer program that executes a procedure for causing the computer to function as a frequency analysis means 200, a regression linear analysis means 300, a tactile sensitivity estimation means 400, and the like. It is remembered in the department. Further, the biological state estimation device 100 includes a frequency analysis circuit, a regression line analysis circuit, and a regression line analysis circuit, which are electronic circuits in which the frequency analysis means 200, the regression line analysis means 300, the tactile sensitivity estimation means 400, and the like are operated by a computer program in a predetermined procedure. It can also be configured as a tactile sensitivity estimation circuit or the like. In the following description, a configuration represented by adding "means" other than the frequency analysis means 200, the regression line analysis means 300, and the tactile sensitivity estimation means 400 can also be configured as an electronic circuit component. Of course.

Further, the computer program may be stored in a recording medium. By using this recording medium, for example, the program can be installed on the computer. Here, the recording medium in which the above program is stored may be a non-transient recording medium. Non-transient recording media are not particularly limited, and examples thereof include recording media such as flexible disks, hard disks, CD-ROMs, MOs (magneto-optical disks), DVD-ROMs, and memory cards. It is also possible to transmit the program to the computer through a communication line and install it.

The frequency analysis means 200 frequency-analyzes the time-series waveform of the back body surface pulse wave (APW) in the vicinity of 1 Hz obtained by filtering the back sound / vibration information obtained from the sensor 14 of the biological signal measuring device 1, and 0.01 to 0.01 to A fluctuation waveform showing the relationship between the logarithmic power spectral density of 0.2 Hz and the logarithmic frequency is output. The dorsal body surface pulse wave (APW) is a biological signal that mainly includes the control of the heart, which is the central system, that is, the sympathetic innervation of arteries, and the appearance information of the sympathetic nervous system and the parasympathetic nervous system. It is a signal. It is preferable to use APW because sympathetic nerve activity is enhanced when pain or discomfort due to an external stimulus is felt. Among them, the frequency band of 0.01 to 0.2 Hz is set as an analysis target, and a log-log axis display is performed. It is preferable to do so. As in the experimental example described later, this frequency band has a high correlation with the dental treatment intensity (usually, the higher the treatment intensity, the stronger the pain and discomfort, and the higher the tactile sensitivity), and the tactile sensation to external stimuli. Suitable for estimating sensitivity. Generally, it is said that the degree of appearance of the sympathetic nervous system and the parasympathetic nervous system associated with these pain sensations is included in the range of 0.01 to 0.04 Hz. This is because noise increases at 0.04 Hz or higher, but some noise is included even at around 0.04 Hz. Therefore, in order to eliminate variations, it is desirable to divide the analysis into a range of 0.01 to 0.03 Hz.
On the other hand, when making a judgment during dental treatment, it is desirable to output the estimation result in a short time, for example, about 5 minutes or less. In addition, when measured during awakening rather than during sleep, as in dental treatment, information on the autonomic nervous system is also included in relatively high frequency bands. In this sense, it is preferable to use a frequency band in the range of 0.01 to 0.2 Hz as an analysis target for obtaining a fluctuation waveform, instead of using 0.03 Hz or 0.04 Hz as the upper limit. In addition, in order to grasp the trend of the biological state globally, the slope of the section is obtained by dividing the data of the biological signal for several seconds, and the slope is sequentially obtained by slide calculation to form the so-called slope time series. The method of obtaining the waveform is suitable, but the slope of the fluctuation waveform obtained from the data for 5 minutes in the range of 0.01 to 0.2 Hz corresponds to the slope of the slope time series waveform for about 30 minutes. In this respect as well, it is preferable to analyze the frequency band of 0.01 to 0.2 Hz of APW as in the present embodiment in order to make a more accurate determination in a short time.

The regression line analysis means 300 obtains a regression line by the least squares method for the fluctuation waveform obtained by the frequency analysis means 200, and then obtains the slope of the regression line.

The tactile sensitivity estimation means 400 estimates the tactile sensitivity to an external stimulus from the slope of the regression line obtained by the regression line analysis means 300. For example, it is preferable to estimate the tactile sensitivity by comparing the slope of the regression line with the slope of -1, that is, the slope of the 1 / f fluctuation. Specifically, when the slope of the regression line is less than -1 (absolute value is greater than 1), it is presumed that the patient strongly feels pain due to an external stimulus, that is, the tactile sensitivity is high, and the regression is performed. When the slope of the straight line is greater than -1 (absolute value is less than 1), it is presumed that the patient does not feel much pain due to external stimuli, that is, the tactile sensitivity is low.

Regarding the correlation between the slope of the regression line and the tactile sensitivity, for example, a plurality of data relating to these relationships are collected in advance and stored in the correlation data storage unit 510 formed in the storage unit of the computer. For example, as described above, when the slope of the regression line is greater than -1, "tactile sensitivity: high", and when the slope of the regression line is less than -1, "tactile sensitivity: low". Create a database according to the format. Of course, the method of constructing the database is arbitrary, and the slope of the regression line and the tactile sensitivity can be further subdivided and corresponded. Then, when estimating the state from the slope of the regression line to be analyzed, the tactile sensitivity estimation means 400 accesses the correlation data storage unit 510 and detects the tactile sensitivity corresponding to the slope of the regression line. .. The correlation data stored in advance in the correlation data storage unit 510 may be a large number of data of different people, or may be a collection of a plurality of personal data of people to be determined.

Further, the slope of the regression line in the normal state before the external stimulus is applied is stored in the reference data storage unit 520 as the reference data, and the tactile sensitivity is estimated by comparison with the reference data. it can. For example, when estimating the tactile sensitivity during dental treatment, the slope of the regression line in the normal state before the start of dental treatment is obtained and stored as reference data. For example, the slope -0.8 is stored. Then, when estimating the tactile sensitivity of the patient, the magnitude of the inclination is determined with reference to −0.8, and the tactile sensitivity is estimated. In this way, when there is a situation where you want to know the tactile sensitivity, for example, an action such as dental treatment, you can know the level of pain or discomfort of the patient more accurately by using the state immediately before that as a reference. it can.

According to the present embodiment, by attaching the biological signal measuring device 1 to the backrest of a chair for dental treatment or a chair for medical treatment such as a chair used in otolaryngology, a person may suffer pain due to an external stimulus. It is possible to know the index (tactile sensitivity) that roughly corresponds to the level of discomfort. In particular, it is suitable for a chair for dental treatment, in which pain is relatively frequently felt during treatment, and can contribute to more appropriate treatment for patients.

It is preferable that the biological state estimation device 100 is provided with a display monitor 110 installed within a range that a doctor can see, such as a table attached to a medical chair. In this case, the computer program for displaying the estimation result of the tactile sensitivity estimation means 400 on the display monitor 110 is activated, and the display monitor 110 is made to output the estimation result of the tactile sensitivity estimation means 400. For example, the horizontal axis shows the treatment time, and the vertical axis shows the tactile sensitivity at the stage of "high, low" or "1, 2, 3 ...", and the doctor looks at the display monitor 110. , The level of pain and discomfort felt by the patient can be easily inferred without appealing by raising the hand of the patient.

Further, according to the present embodiment, the frequency band to be analyzed is limited to 0.01 to 0.2 Hz as described above, which is necessary for estimating the tactile sensitivity. Therefore, the load on the arithmetic processing unit of the computer is small and the amount of memory used can be small. Further, since only one regression line is drawn by the regression line analysis means 300 on the fluctuation waveform and only the slope thereof is determined, the load on the computer is reduced as compared with the case where a wider frequency band is analyzed. , Can contribute to the improvement of calculation processing speed.

(Experimental example)
In dental practice, treatment actions that are considered to have a low level of pain or discomfort and treatment actions that are considered to be high are classified as treatment intensity, and the treatment intensity is compared with the analysis results obtained by the biological condition estimation device 100. It was.

(1) Measurement method APW was measured during dental treatment for patients who visited the dental clinic. There were 17 subjects (14 males, 3 females, average age 59 ± 15.5 years). The purpose and content of this experiment were explained to the subject by a doctor, and the measurement was performed after obtaining consent. APW installed the biological signal measuring device 1 (sleep driving warning device (Sleep Buster (registered trademark)) manufactured by Delta Touring Co., Ltd.) on the backrest of the chair for dental treatment and performed the measurement. The time is from the start of medical treatment to the end of medical treatment.

(2) Analysis method The appearance rate of body movement, the degree of appearance of autonomic nerve activity, and the frequency spectrum of the heart rate variability waveform at the time of medical treatment are calculated from APW and compared with the treatment intensity considered by the doctor. The treatment intensity is empirically quantified by the doctor who performs the medical treatment on a scale of 10 for each treatment content.

(3) Results and discussion Fig. 3 shows the relationship between treatment intensity and body movement appearance rate. When the treatment intensity was high or when scaling / tooth surface cleaning was performed, the appearance rate of body movement tended to be high. Comparing the body movements of the group with high anxiety and the group with low anxiety about dental treatment, the group with high anxiety has more body movements in the limbs. In other words, when the treatment intensity is high, mental stress such as tension, anxiety, and fear increases, and it is considered that physical activity tends to increase. On the other hand, it is considered that scaling and tooth surface cleaning, which have low treatment intensity, increased body movement due to the influence of mechanical treatment with high-frequency vibration such as tartar removal and brushing.

FIG. 4 shows the relationship between the treatment intensity and the sympathetic nerve enhancement rate at the time of medical treatment. The higher the treatment intensity, the higher the sympathetic hyperactivity rate tends to be. Infiltration anesthesia is used because tooth extraction, incision, and abutment tooth formation, which have high treatment intensity, place a heavy physical burden. Since infiltration anesthesia causes the most pain and psychological stress in dental procedures, it is considered that the activity of the sympathetic nervous system is enhanced when the treatment intensity is high. Therefore, it can be said that the activity of the sympathetic nervous system is enhanced when the level of pain or stress (tactile sensitivity) is increased.

Cleaning the tooth surface has the effect of relaxing the patient. Scaling exerts acute stress and causes an increase in sympathetic nerve activity, but at the same time activates parasympathetic nerve activity in an attempt to maintain the balance of the body. Therefore, it is considered that the rate of increase in sympathetic nerve activity of scaling and tooth surface cleaning was widely distributed in 1 to 33%. Since root canal treatment is relatively minimally invasive, it is considered that the rate of increase in sympathetic nerve activity was low. On the other hand, although the prosthetic treatment has a low therapeutic intensity, it is presumed that the sympathetic nerve activity was enhanced because the tooth cutting and filling treatment tended to cause discomfort. This can also be grasped as a sensation similar to pain.

FIG. 5 shows the relationship between the treatment intensity and the slope of the frequency spectrum of the heart rate variability waveform calculated from the body surface pulse wave (slope of the fluctuation waveform) classified by the state of the autonomic nervous system. FIG. 6 shows the frequency spectra of heart rate variability waveforms of subject A (52-year-old man) who received scaling and tooth brushing instruction (treatment intensity 1) and subject B (59-year-old man) who received tooth extraction (treatment intensity 5). The thick line in the figure shows the regression line of the spectrum (fluctuation waveform). The slope of the regression line of the spectrum tended to be smaller than -1 (larger absolute value) when the treatment intensity was high, and larger than -1 (smaller absolute value) when the treatment intensity was low. That is, a high correlation was observed between the treatment intensity and the slope of the regression line with 1 / f as the boundary (correlation coefficient R = −0.59). From this, it can be seen that the case where the level of pain with low treatment intensity is low and the case where the level of pain with high treatment intensity is high can be discriminated by this inclination.

The parasympathetic dominant state means that the active state of the parasympathetic nervous system occupies 40% or more of the consultation time, and the sympathetic / parasympathetic activated state is a state in which the parasympathetic nervous system is activated as well as the sympathetic nervous system is enhanced. Is shown. In this division, the average value of the slope of the regression line of the spectrum (fluctuation waveform) in the parasympathetic dominant state is -0.066 ± 0.2, and in the sympathetic / parasympathetic activated state is -0.88 ± 0.26. It was. As a result of the t-test, no significant difference was observed at p = 0.05, but the slope of the spectrum tended to be larger in the negative direction in the sympathetic / parasympathetic activated state. This is consistent with the finding that the gradient of 1 / f fluctuation of heart rate variability becomes deeper with the suppression of parasympathetic nerve activity. From the above results, it was suggested that the relationship between treatment intensity and autonomic nervous activity state, that is, the tactile sensitivity, which is the level of pain and discomfort to external stimuli, could be estimated by using the fluctuation characteristics of heart rate variability.

7 (a) to 7 (e) show the inclination of the frequency spectrum of the heart rate variability waveform calculated from the treatment intensity and the body surface pulse wave (inclination of the fluctuation waveform) by differentiating the frequency band to be analyzed by the frequency analysis means 200. ) Is shown by classifying the state of the autonomic nervous system. From this result, it can be seen that setting the frequency band to be analyzed to 0.01 to 0.2 Hz (FIG. 7 (b)) has the highest correlation.

1 Biological signal measuring device 11 Core pad 12 Spacer pad 13 Sensor 100 Biological state estimation device 200 Frequency analysis means 300 Regression linear analysis means 400 Tactile sensitivity estimation means 510 Correlation data storage unit 520 Reference data storage unit

Claims (11)

It is a biological state estimation device that estimates a biological state using a biological signal consisting of sound and vibration information of the heart and blood vessels obtained from a biological signal measuring device that comes into contact with the back of a person.
A frequency analysis means that frequency-analyzes the time-series data of the biological signal and outputs a fluctuation waveform showing the relationship between the logarithmic power spectral density of 0.01 to 0.2 Hz and the logarithmic frequency.
A regression line analysis means for obtaining a regression line for the fluctuation waveform and a slope of the regression line,
A biological state estimation device comprising a tactile sensitivity estimating means for estimating the tactile sensitivity to an external stimulus as the biological state based on the inclination of the regression line. It is provided with a correlation data storage unit that stores correlation data between the slope of the regression line measured in advance and the tactile sensitivity.
The living body according to claim 1, wherein the tactile sensitivity estimating means accesses the correlation data storage unit, collates the inclination of the regression line of the analysis target obtained by the regression line analysis means, and estimates the tactile sensitivity. State estimator. The tactile sensitivity estimating means stores the slope of the regression line in the normal state before the external stimulus is applied as reference data in the reference data storage unit, and the analysis target obtained by the regression line analysis means. The biological state estimation device according to claim 1, wherein the tactile sensitivity is estimated by comparing the inclination of the regression line with the reference data. The biological signal measuring device is provided on the backrest of a medical chair.
It said frequency analyzing means, and a frequency analysis on the biological signal obtained from the back of a patient seated in the medical chair,
The biological state estimation device according to any one of claims 1 to 3, further comprising a display monitor that outputs the tactile sensitivity of the patient estimated by the tactile sensitivity estimating means. It is a biological state estimation method that estimates a biological state using a biological signal consisting of sound and vibration information of the heart and blood vessels obtained from a biological signal measuring device that comes into contact with the back of a person.
The time series data of the biological signal is frequency-analyzed, and a fluctuation waveform showing the relationship between the logarithmic power spectral density of 0.01 to 0.2 Hz and the logarithmic frequency is output.
Find the regression line for the fluctuation waveform and find the slope of the regression line.
A biological state estimation method characterized in that the tactile sensitivity to an external stimulus is estimated as the biological state based on the slope of the regression line. A request for estimating the tactile sensitivity by accessing a correlation data storage unit that stores correlation data between the inclination of the regression line measured in advance and the tactile sensitivity, collating the inclination of the regression line to be analyzed with the correlation data. Item 5. The method for estimating a biological state according to Item 5. The slope of the regression line in the normal state before the external stimulus is applied is stored in the reference data storage unit as reference data, and the slope of the regression line to be analyzed is compared with the reference data. The biological state estimation method according to claim 5, wherein the tactile sensitivity is estimated. Have a computer as a biological state estimation device analyze a biological signal consisting of sound and vibration information of the heart and vascular system obtained from a biological signal measuring device that is in contact with the back of a person, and execute a procedure for estimating the biological state. It ’s a computer program
A procedure for frequency-analyzing the time-series data of the biological signal and outputting a fluctuation waveform showing the relationship between the logarithmic power spectral density of 0.01 to 0.2 Hz and the logarithmic frequency.
The procedure for obtaining the regression line for the fluctuation waveform and the slope of the regression line, and
A computer program that executes a procedure of estimating the tactile sensitivity to an external stimulus as the biological state based on the slope of the regression line. In the procedure for estimating the tactile sensitivity, the correlation data storage unit that stores the correlation data between the inclination of the regression line measured in advance and the tactile sensitivity is accessed, and the inclination of the regression line to be analyzed is collated with the correlation data. The computer program according to claim 8, wherein the tactile sensitivity is estimated. In the procedure for estimating the tactile sensitivity, the slope of the regression line in the normal state before the external stimulus is applied is stored in the reference data storage unit as reference data, and the slope of the regression line to be analyzed is stored. The computer program according to claim 8, wherein the tactile sensitivity is estimated by comparing with the reference data. Have a computer as a biological state estimation device analyze a biological signal consisting of sound and vibration information of the heart and vascular system obtained from a biological signal measuring device that is in contact with the back of a person, and execute a procedure for estimating the biological state. A computer-readable recording medium on which the computer program according to any one of claims 8 to 10 is recorded.