JP2009089829A - Biological state estimating device, program, and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a biological state estimating device capable of estimating biological state with a high precision even in a condition in which the estimation of the biological state with a high precision is difficult such as while driving. <P>SOLUTION: In the step 120, electrocardiographs and pulse waves are measured. In the step 130, it is determined whether or not electrocardiogram signals are well taken. In the step 140, it is determined whether pulse wave signals are well taken. In the step 160, the pulse wave signals are analyzed and the values of parameters (such as a, d, or others of acceleration pulse waves) used in the equation (1) are calculated out because only the pulse wave signals are well taken. In the step 170, the values of the parameters are applied to the equation (1) and blood pressures are estimated. In the step 180, the electrocardiogram signals and the approximate pulse wave signals are analyzed and the values of the parameters (PTT, HR) used in the equation (2) are calculated out because only the electrocardiogram signals are well taken. In the step 200, the values of the parameters are applied to the equation (2) and the blood pressures are estimated. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a biological state estimation device, a program, and a recording medium that are mounted on a vehicle, for example, and can estimate a biological state such as blood pressure of a driver without using a cuff, for example.

  Conventionally, for example, when measuring blood pressure, both the auscultation method and the oscillometric method require tightening with a cuff, the device becomes large, the subject has suffered, and continuous blood pressure measurement. There were problems such as being unable to.

On the other hand, in recent years, a measurement method for calculating blood pressure using a pulse wave velocity and a pulse wave feature amount has been studied (see Patent Documents 1 to 11). For example, volume pulse waves can be measured using light, so that the apparatus can be miniaturized, the pain of the measurement subject can be eliminated, and continuous blood pressure measurement can be performed.
JP-A-10-295656 Japanese Patent Laid-Open No. 10-295657 Japanese Patent Laid-Open No. 11-318837 JP-T-2001-504362 Special table 2003-555 gazette Special table 2003-527149 gazette Japanese Patent Laid-Open No. 2001-8907 JP 2006-263354 A JP 2006-6897 A JP 2007-7075 A JP 2007-7077 A

  However, even the techniques described in the above cited references have not been able to sufficiently consider personal characteristics, measurement environments, and the like, and there has been a problem that biological conditions such as blood pressure cannot be estimated with sufficient accuracy.

  In particular, when driving a vehicle, factors such as body movements (ie, disturbances that hinder the estimation of the living body) that occur during driving increase, so there is sufficient information for estimating a biological state such as blood pressure. As a result, it may be difficult to estimate the biological state with high accuracy.

  The present invention has been made in view of the above problems. For example, in a situation where it is difficult to estimate a biological state with high accuracy, such as during driving, the biological state estimation capable of estimating the biological state with high accuracy is possible. An object is to provide an apparatus, a program, and a recording medium.

  (1) The invention according to claim 1 is the biological state estimation device that estimates the state of the living body using at least the pulse wave signal among the electrocardiographic signal and the pulse wave signal detected from the living body. Measuring means for measuring at least the pulse wave signal of the signal and the pulse wave signal, and calculating means for analyzing at least the pulse wave signal of the measured signal and calculating a feature amount of the analyzed signal; A plurality of estimation means for estimating the state of the living body based on a predetermined algorithm using the feature amount, and which estimation means of the plurality of estimation means is used to estimate the state of the living body. Determination means for determining based on a predetermined determination condition.

  The present invention includes a plurality of estimation means for estimating a biological state using feature quantities of an electrocardiogram signal and a pulse wave signal, that is, estimation means for estimating a biological condition based on a predetermined algorithm using the feature quantities. ing.

  In the present invention, at least a pulse wave signal is measured out of an electrocardiogram signal and a pulse wave signal, and at least the pulse wave signal is analyzed among the measured signals to calculate a feature quantity of the electrocardiogram signal and the pulse wave signal. Further, based on a predetermined determination condition, it is determined which of the plurality of estimation means is used to estimate the state of the living body. Then, based on the algorithm of the estimation means selected by this determination, the state of the living body is estimated using the feature amount (necessary for estimation of the living body).

  In other words, the present invention has a plurality of estimating means for estimating the state of the living body, and for example, an optimal estimating means for appropriately estimating the living body state according to the state of an electrocardiogram signal, a pulse wave signal, or the like. Select. Therefore, even in a situation where it is difficult to estimate the biological state with high accuracy, such as during driving, the biological state can be estimated with high accuracy.

  Here, the feature amount is an index indicating the state of each signal, and by obtaining the feature amount, it is possible to know what state the signal is in (such as a waveform feature). For example, if the pulse wave height is used as the feature amount of the pulse wave signal, it is possible to grasp how much the signal level is.

(2) The invention of claim 2 is characterized in that the state of the living body is blood pressure.
The present invention exemplifies a living body state to be estimated. That is, according to the present invention, blood pressure can be estimated with high accuracy during driving or the like.

  (3) In the invention of claim 3, the feature quantity of the electrocardiogram signal or the feature quantity of the pulse wave signal used for the estimation means is PTT, pulse wave AI, pulse wave amplitude, acceleration pulse wave feature quantity, It includes at least one kind of feature quantity of the pulse wave signal among the heartbeat interval and the heart rate.

The present invention exemplifies the feature quantity of the electrocardiogram signal and the feature quantity of the pulse wave signal used for the estimation of the biological state in the estimation means.
Here, as shown in FIG. 3, the PTT (pulse wave propagation time) is a time difference between an electrocardiogram signal and a pulse wave signal, and can be obtained as a time difference between an R wave of the electrocardiogram and a pulse wave measured with a finger. it can.

  As shown in FIG. 4, the pulse wave AI (Augmentation Index) is a ratio (P2 / P1) of the magnitude of the reflected wave (P2) and the traveling wave (P1) in the pulse wave. Wave or pressure pulse wave).

Further, the velocity pulse wave can be obtained by first-order differentiation of the pulse wave signal, and the acceleration pulse wave can be obtained by second-order differentiation of the pulse wave signal.
As the feature amount of the acceleration pulse wave, a wave (a positive initial contraction wave), b wave (a negative initial contraction wave), c wave (an intermediate contraction re-rising wave), and a d wave indicating the peak of the wave along the time axis. (Late systolic re-falling wave), e wave (expanded initial positive wave), f wave (expanded initial negative wave), and the like. The feature quantities a to f of this acceleration pulse wave are the magnitude (amplitude) of the peak of each wave. ).

Further, the pulse wave height indicates the height (width) of the pulse wave from a predetermined reference line.
Of the feature quantities, the PTT can be obtained from the electrocardiogram signal and the pulse wave signal, and the pulse wave AI, acceleration pulse wave, and pulse wave amplitude (and hence the pulse wave height) are obtained from the pulse wave signal. The pulse interval and heart rate can be obtained from an electrocardiogram signal or a pulse wave signal.

(4) The invention of claim 4 is characterized in that the determination means selects the estimation means based on a feature quantity of the electrocardiogram signal or a feature quantity of the pulse wave signal.
The present invention exemplifies determination means. In the present invention, the optimum estimation means can be selected based on the feature quantity of the electrocardiogram signal or pulse wave signal.

  In other words, the electrocardiogram signal and pulse wave signal corresponded to differences between living bodies (for example, differences between groups such as gender differences and age differences, or differences due to individual differences), and living body conditions (for example, the degree of blood pressure). Therefore, the state of the living body can be estimated with high accuracy by selecting a different algorithm (an arithmetic expression for estimating the state of the living body) according to the feature quantity of the electrocardiogram signal or the pulse wave signal. .

  (5) In the invention of claim 5, the feature quantity of the electrocardiogram signal or the feature quantity of the pulse wave signal used for the determination means is the fluctuation of the baseline of the pulse wave signal, the amplitude of the pulse wave signal (pulse wave amplitude). And at least one of a feature quantity of an acceleration pulse wave, an amplitude of an electrocardiogram signal (electrocardiogram amplitude), a heartbeat interval, and a heart rate.

  The present invention exemplifies feature quantities of an electrocardiogram signal and a pulse wave signal used for determination means. That is, the optimal estimation means can be selected from the fluctuation of the baseline of the pulse wave signal, the pulse wave amplitude, the feature amount of the acceleration pulse wave, the electrocardiogram amplitude, the heartbeat interval, the heart rate, and the like.

Here, the fluctuation of the baseline of the pulse wave signal indicates the fluctuation state (amplitude) of the line (base line) connecting the medians of both the maximum and minimum peaks in one cycle of the pulse wave.
(6) The invention according to claim 6 is characterized in that the determination means selects the estimation means based on a feature quantity of the electrocardiogram signal or a variance of the feature quantity of the pulse wave signal.

  In the determination means, the determination may be made by using the characteristic amount of the electrocardiogram signal or the characteristic amount of the pulse wave signal as it is, but the determination is performed more accurately by using statistical variance (in each characteristic amount). Can do. For example, when the pulse wave amplitude is taken and the variance of the pulse wave amplitude is larger than the reference value, it can be understood that it is not appropriate to estimate the living body using the pulse wave signal. An estimation means for estimating a living body using an electric signal can be selected.

(7) The invention according to claim 7 is characterized in that the determination means selects the estimation means based on personal information of the living body.
In the present invention, since a preferable estimation unit is selected based on personal information indicating the characteristics of the living body, the biological state can be accurately estimated by the estimation unit.

(8) The invention according to claim 8 is characterized in that the personal information is at least one of age, sex, height, weight, body fat, and disease information.
The present invention exemplifies personal information. In other words, different estimation means are set in advance according to such personal information, and in actual estimation, the biological state is accurately estimated by selecting an estimation means corresponding to each personal information. be able to.

  Here, in the case of age, for example, stratified above or below a predetermined age, in the case of gender, stratified by gender, in the case of height, for example, stratified above or below a predetermined height, in the case of weight For example, in the case of body fat, the stratification is based on the presence or absence of a specific disease such as heart disease. Is possible.

(9) The invention according to claim 9 is characterized in that the determination means selects the estimation means based on a measurement state of each signal.
In the present invention, since a preferable estimation means is selected based on the measurement situation, it is possible to accurately estimate the biological state by the estimation means.

  (10) In the invention of claim 10, the measurement state is at least one of a driving state or a stopping state, a vehicle traveling state, a one-handed or two-handed state, and a body movement state. It is characterized by that.

The present invention exemplifies the measurement situation.
(11) The invention according to claim 11 is characterized in that the determination means selects the estimation means based on the measurement environment of the living body.

In the present invention, since a preferable estimation unit is selected based on the measurement environment, the biological state can be accurately estimated by the estimation unit.
(12) In the invention of claim 12, the measurement environment is at least one of temperature, humidity, and solar radiation.

The present invention exemplifies a measurement environment.
(13) The invention of claim 13 is a program for realizing the function of the biological state estimating apparatus according to any one of claims 1 to 12.

  Therefore, by executing this program with a microcomputer or the like, it is possible to estimate a biological state such as blood pressure using the above-described feature amount or the like and using a predetermined estimation means (calculation formula).

(14) The invention of claim 14 is a computer-readable recording medium on which the program of claim 13 is recorded.
Therefore, the biological state can be estimated using the program recorded on this recording medium as described above.

Next, the best mode (embodiment) of the present invention will be described.
[First Embodiment]
In this embodiment, a biological state estimation device that is mounted on an automobile and measures the blood pressure of a driver will be described.

a) First, the system configuration of the biological state estimation apparatus of this embodiment will be described.
As shown in FIG. 1, in the present embodiment, a biological state estimation device 1 mounted on an automobile, a notification device 3 that notifies information to a driver, etc., and a manual input unit 5 that manually inputs data. The pulse wave sensor 9 attached to the steering 7 and a pair of electrodes 11 and 13 attached to the steering 7 are provided.

  The biological state estimation device 1 is an electronic control device centered on a well-known microcomputer, and calculates blood pressure and controls the notification device 3 based on signals from the pulse wave sensor 9 and the electrodes 11 and 13. Do.

The notification device 3 includes a display 15 such as a liquid crystal that displays blood pressure and the like, and a speaker 17 that outputs the contents thereof by voice or the like.
The manual input unit 5 is an input device such as a keyboard, a numeric keypad, or a remote controller capable of inputting individual body characteristic information such as weight, height, age, and sex manually. Note that data may be input using the display screen of the display 15 as a touch panel. Further, instead of the manual input unit 5, information may be read from a memory such as a card storing various data.

  The pulse wave sensor 9 is an optical sensor provided with a known light emitting element (LED) or light receiving element (PD). For example, the pulse wave sensor 9 irradiates light on a fingertip of a driver and uses the reflected wave to make a pulse wave. (Volume pulse wave) can be detected. Therefore, a pulse wave signal used for blood pressure calculation described later can be obtained from the pulse wave sensor 9.

  The pair of electrodes 11 and 13 are arranged on the left and right of the steering wheel 7 so as to come into contact with the left and right hands of the driver, respectively. These electrodes 11 and 13 are used as electrodes of an electrocardiograph that applies a voltage to obtain an electrocardiographic signal. Here, both the electrodes 11 and 13 and the biological state estimation apparatus 1 fulfill | perform the function of an electrocardiograph. Therefore, an electrocardiographic signal used for blood pressure calculation described later can be obtained using the electrodes 11 and 13.

In addition, an electric current is sent between a pair of electrodes 11 and 13, and thereby impedance is obtained, and body fat can be obtained from the impedance and body weight.
b) Next, the functions of the biological state estimating apparatus and the like of this embodiment will be described in more detail with reference to block diagrams.

  As shown in FIG. 2, the living body state estimation apparatus 1 of the present embodiment includes an electrocardiogram signal acquisition unit 25, a pulse wave signal acquisition unit 27, an electrocardiogram signal analysis unit 31, and electrocardiogram and pulse wave signal analysis. A unit 33, a pulse wave signal analysis unit 35, and a blood pressure calculation unit 37 are provided.

Among these, the electrocardiogram signal acquisition unit 25 measures electrical excitement accompanying the activity of the heart as a potential difference (electrocardiogram signal) between the electrodes 11 and 13.
The pulse wave signal acquisition unit 27 drives the pulse wave sensor 9 to acquire a pulse wave signal.

The electrocardiogram signal analysis unit 31 analyzes the electrocardiogram signal and calculates, for example, a heart rate and a heart rate interval (HR).
As shown in FIG. 3, the electrocardiogram and pulse wave signal analysis unit 33 uses the electrocardiogram signal and the pulse wave signal to obtain a pulse wave propagation time (PTT) that is a delay time of the pulse wave signal with respect to the electrocardiogram signal. Is.

  As shown in FIG. 4, the pulse wave signal analysis unit 35 analyzes the pulse wave signal, performs first-order differentiation (velocity pulse wave), second-order differentiation (acceleration pulse wave), and the like, and features in each differentiation (For example, velocity pulse wave a1 to k1, acceleration pulse wave a to f, etc.) and pulse wave AI (volume AI) are calculated.

The blood pressure calculation unit 37 calculates blood pressure based on a predetermined calculation formula using a feature amount such as PTT, velocity pulse wave and acceleration pulse wave, volume AI, and the like.
c) Next, an arithmetic expression used for calculating blood pressure will be described.

In the present embodiment, a plurality of arithmetic expressions are stored as arithmetic expressions for calculating blood pressure in the blood pressure calculator 37, and which arithmetic expression is used is selected according to a predetermined condition.
Specifically, (i) The electrocardiogram signal is not taken well, but the pulse wave signal is taken well, (ii) The electrocardiogram signal is taken well, but the pulse wave signal is not taken well , (Iii) distinguish between three types of conditions when both an electrocardiogram signal and a pulse wave signal are obtained, and (iii) when both an electrocardiogram signal and a pulse wave signal are obtained firmly, A distinction is made between two types of conditions: (iiia) the case where the pulse wave signal indicates the younger generation and (iiib) the case where the older generation is indicated.

  As shown in FIG. 5A, for example, whether or not the ECG signal is successfully obtained is that the peak interval or amplitude value (or its variance) of the ECG signal deviates from a predetermined normal range. It can be judged by whether or not. In other words, when it deviates from the normal range, it is considered that the reliability of the electrocardiogram signal is low, and thus it can be understood that this electrocardiogram signal cannot be used for blood pressure estimation.

  Whether or not the pulse wave signal is successfully obtained can be determined based on whether or not the fluctuation of the baseline of the pulse wave is larger than the amplitude of the pulse wave, as shown in FIG. 5B. In other words, if the fluctuation of the baseline of the pulse wave becomes larger than the amplitude of the pulse wave, it is considered that the reliability of the pulse wave signal is low, so this pulse wave signal may not be used for blood pressure estimation. I understand. Hereinafter, (i) to (iiib) will be sequentially described.

(i) As shown in FIG. 5 (a), the calculation formula of blood pressure when the electrocardiogram signal is not taken well but the pulse wave signal is taken well. Here, the blood pressure at rest (the blood pressure used as a reference: BP ₀ ) and acceleration pulse wave feature values a and d obtained from the pulse wave signal are used to obtain a blood pressure (estimated blood pressure: BP) by, for example, the following equation (1). As the resting blood pressure (BP ₀ ), for example, the blood pressure estimated when the vehicle is stopped can be used, but a value obtained in advance through experiments or the like may be used. Here, a ₀ and d ₀ are the values of the feature values a and d of the acceleration pulse wave when the blood pressure is obtained.

In the following formulas, Greek letters such as α, β, etc. are used as coefficients, but the coefficient values in each formula can be obtained by experiment in advance, and the coefficient values in each formula are usually the same even if the letters are the same. Is different.

BP = BP ₀ + α · (a−a ₀ ) + β · (d−d ₀ ) +... (1)
(Α and β are coefficients)

(ii) As shown in FIG. 5B, the calculation formula when the electrocardiogram signal is successfully acquired but the pulse wave signal is not successfully acquired. Here, the blood pressure at rest (BP ₀ ), PTT, Using the heart rate interval (HR) obtained from the electrocardiogram signal, the blood pressure (BP) is obtained by the following equation (2), for example. Here, PTT ₀ and d ₀ are values of the pulse wave propagation velocity PTT and the acceleration pulse wave feature amount d when blood pressure is obtained.

As shown in FIG. 3, the PTT is obtained from an electrocardiogram signal and a pulse wave signal. The shape of the pulse wave in FIG. 5B is the pulse wave in FIG. 5A. Although it is not clearer than the shape, the degree of fluctuation in synchronization with the heartbeat can be recognized, so that PTT can be calculated. It is also possible to use a heart rate instead of the heart rate interval.

BP = BP ₀ + α · (PTT−PTT ₀ ) + β · (d−d ₀ ) + ··· (2)
(Α and β are coefficients)

(iii) As shown in FIG. 5C, the blood pressure calculation formula when both the electrocardiogram signal and the pulse wave signal are successfully obtained. In this case, the pulse wave signal is analyzed, and the pulse wave Distinguishes between types and elderly types (stratified).

  Specifically, the second order differentiation of the pulse wave signal is taken to obtain the acceleration pulse wave feature quantities a, b, c, d, and e. Then, it is determined whether or not {(b−c−d−e) / a} is equal to or less than a predetermined determination value (h), for example, (−0.5) or less. If not, it is determined as an elderly type, and an arithmetic expression is selected as follows.

(iiia) In the case of the younger type, the blood pressure (BP) is obtained by the following equation (3), for example, using the PTT, the feature amount d of the acceleration pulse wave, and the body weight (Wei). Note that the weight, which is personal information, may be omitted.

_{BP = α y · PTT + β} y · d + γ y · Wei + ··· ·· (3)
(Α _y , β _y , γ _y are coefficients)

(iiib) In the case of the elderly type, the blood pressure (BP) is obtained by, for example, the following equation (3) using the PTT, the feature quantity d of the acceleration pulse wave, and the body weight (Wei). Note that the weight, which is personal information, may be omitted. In addition, the value of a coefficient differs between Formula (3) and Formula (4).

BP = α _o · PTT + β _o · d + γ _o · Wei + (4)
(Α _o , β _o and γ _o are coefficients)

d) Next, calculation processing performed in the blood pressure measurement device 1 will be described.

  As shown in the flowchart of FIG. 6, in step (S) 100, it is determined whether or not to use personal information. For example, it may be displayed on the display 15 whether or not personal information is used, and the driver's input may be prompted. If an affirmative determination is made here, the process proceeds to step 110, while if a negative determination is made, the process proceeds to step 120.

In step 120, electrocardiogram and pulse wave are measured.
In the following step 130, it is determined whether or not the electrocardiogram signal is successfully obtained, that is, whether or not the electrocardiogram signal is abnormal. If an affirmative determination is made here, the process proceeds to step 140, while if a negative determination is made, the process proceeds to step 150.

  In step 140, it is determined whether or not the pulse wave signal is successfully obtained, that is, whether or not the pulse wave signal is abnormal. If an affirmative determination is made here, the process proceeds to step 120. If a negative determination is made, the process proceeds to step 160.

In step 160, since only the pulse wave signal is successfully obtained, the pulse wave signal is analyzed, and the values of parameters (acceleration pulse wave feature amounts a, d, etc.) used in equation (1) are calculated.
In the subsequent step 170, the value of the parameter is applied to the equation (1) to estimate the blood pressure, and the process is temporarily terminated.

  On the other hand, in step 150, where the negative determination is made in step 130, it is determined whether or not the pulse wave signal is successfully obtained, that is, whether or not the pulse wave signal is abnormal. If an affirmative determination is made here, the process proceeds to step 180, whereas if a negative determination is made, the process proceeds to step 190.

  In step 180, since only the electrocardiogram signal is successfully obtained (the pulse wave signal has an approximate waveform), the electrocardiogram signal and the approximate pulse wave signal are analyzed, and the parameters (2) used in equation (2) ( PTT, HR) values are calculated.

In the following step 200, the value of the parameter is applied to the equation (2) to estimate the blood pressure, and the process is temporarily terminated.
In Step 190, which is determined to be negative in Step 150 and proceeds, the electrocardiogram signal and the pulse wave signal are in good condition, and the pulse wave type is determined here.

  Specifically, the feature values a, b, c, d, and e of the acceleration pulse wave are used, and depending on whether {(b−c−d−e) / a} is equal to or less than the determination value (h), It is determined whether the wave signal is a young type or an old type. If it is determined that the type is young, the process proceeds to step 210. If it is determined that the type is an elderly group, the process proceeds to step 220.

In step 210, the values of parameters (PTT, d, etc.) used in the younger group type equation (3) are calculated.
In the subsequent step 220, the value of the parameter is applied to the equation (3) to estimate the blood pressure, and the process is temporarily terminated.

On the other hand, in step 230, values of parameters (PTT, d, etc.) used for the elderly type (4) are calculated.
In the next step 240, the value of the parameter is applied to the equation (4) to estimate the blood pressure, and the process is temporarily terminated.

e) Next, Experimental Example 1 in which the effect of the present embodiment has been confirmed will be described.
Here, for the subjects (150 people) who have successfully acquired both the electrocardiogram signal and the pulse wave signal, the pulse wave type is classified into a young type and an elderly type using the features of acceleration pulse wave ( The blood pressure was estimated using arithmetic expressions corresponding to each type. In addition, blood pressure was actually measured using a cuff.

  The result is shown in FIG. 7 (a), where the vertical axis indicates blood pressure estimated by the method of the present embodiment, and the horizontal axis indicates that measured using a cuff (actual blood pressure). In the figure, the data obtained by the younger type expression (3) is indicated by x, and the data obtained by the elderly type (4) is indicated by ◯.

  FIG. 7A shows that the correlation coefficient (r) between the estimated blood pressure and the actually measured blood pressure is 0.89 (both types of data are used), and the correlation is high. Also, the standard deviation (σ) of the error is as small as 7.8 mmHg. Thereby, it turns out that blood pressure can be estimated accurately.

In addition, as a comparative example, an experiment was also performed in the case where stratification by acceleration pulse waves was not performed.
In this experiment, blood pressure was estimated using the following formula (5). In addition, the value of a coefficient differs between this Formula (5), said Formula (3), and Formula (4).

BP = α · PTT + β · d + γ · Wei + (5)
(Α, β and γ are coefficients)

The result is shown in FIG. 7B. In the comparative example in which no stratification was performed, the correlation coefficient between the estimated blood pressure and the measured blood pressure was 0.83, and the standard deviation of the error was 9.6 mmHg. It can be seen that the accuracy is low.

  f) As described above, in this embodiment, it is determined whether the electrocardiogram signal or the pulse wave signal is successfully obtained, and the arithmetic expressions (1) and (2) for estimating the blood pressure according to the state of each signal are obtained. Selected. In addition, when both the electrocardiogram signal and the pulse wave signal are obtained, stratification is further performed using the feature quantity of the acceleration pulse wave, and calculation formulas (3) and (4) for estimating the blood pressure are selected. ing.

Therefore, in this embodiment, since the blood pressure is estimated using an optimal arithmetic expression according to the measurement state of the living body, a remarkable effect that high measurement accuracy is obtained can be achieved.
In addition to the above-mentioned formulas (1) to (4), for example, when an electrocardiogram signal and a pulse wave signal can be obtained successfully, the following formula (6) using, for example, AI or PA (pulse wave amplitude) of the pulse wave: ) And blood pressure can be estimated using an arithmetic expression such as (7).

Here, ctime in the following formula (6) represents the time from the rise of the pulse wave to the feature quantity c of the acceleration pulse wave. Further, PA ₀ and HR _{0 in} the following formula (7) are PA and HR at rest, respectively.

BP = α · AI + β · a + γ · ctime + δ · HR + (6)
(Α, β, γ and δ are coefficients)

BP = BP ₀ + α · (PA / PA ₀ ) + β · (HR−HR ₀ ) +... (7)
(Α and β are coefficients)

[Second Embodiment]
Next, the second embodiment will be described, but the description of the same contents as the first embodiment will be omitted.

Since the hardware configuration is the same as that of the first embodiment, different contents will be described.
In the present embodiment, an arithmetic expression used for blood pressure estimation is selected (stratified) based on personal information.

Here, the following formulas (8) and (9) similar to the above formulas (3) and (4) are selected depending on whether the age is less than 40 years or over 40 years. Note that the values of the coefficients in the equations (8) and (9) are different.

_{BP = α y · PTT + β} y · d + γ y · Wei + ··· ·· (8)
(Α _y , β _y , γ _y are coefficients)

BP = α _o · PTT + β _o · d + γ _o · Wei + (9)
(Α _o , β _o and γ _o are coefficients)

Specifically, when the manual input unit 5 has an input that the age is less than 40 years old, the formula (8) for the younger generation type is selected, and when there is an input that is 40 years old or older. The elderly type (9) was selected.

  Then, in the same manner as in Experimental Example 1, blood pressure was estimated by distinguishing the subjects (150 persons) who successfully obtained both the electrocardiogram signal and the pulse wave signal by age. In addition, blood pressure was actually measured using a cuff.

The result is shown in FIG. In the figure, the data under 40 and the data over 40 are indicated by different marks.
FIG. 8 shows that the correlation coefficient (r) between the estimated blood pressure and the actually measured blood pressure is 0.87 (both types of data are used), and the correlation is high. That is, it can be seen that the blood pressure can be estimated with high accuracy.

  In addition, since the effect of stratification according to age (that is, the effect of improving the accuracy of blood pressure estimation) is large, it is possible to estimate blood pressure without using the weight parameter in the above formulas (8) and (9). is there.

In the present embodiment, the same effects as in the first embodiment can be obtained.
In addition, here, stratification according to age is given as an example, but as personal information for stratification, gender, height, weight, body fat, or disease information can be adopted, and further, two or more of them are combined In addition, more precise stratification may be performed.

  For example, in the case of men and women, there is a statistically significant difference in physique, and the difference in physique affects blood pressure, so blood pressure is estimated using a different formula rather than estimating the blood pressure using the same formula. A more accurate value can be obtained by estimating.

Similarly, it has been confirmed by studies by the present inventors that height, weight, and body fat are correlated with blood pressure.
Regarding disease information, if there is a heart disease or arterial stenosis, the pulse waveform is greatly different from that of a person without a disease. Therefore, the estimation accuracy can be increased by stratifying according to the site of the disease and the degree of the disease.

Each arithmetic expression can be obtained by experiments or the like.
[Third Embodiment]
Next, the third embodiment will be described, but the description of the same contents as the first embodiment will be omitted.

Since the hardware configuration is the same as that of the first embodiment, different contents will be described.
In the present embodiment, an arithmetic expression used for blood pressure estimation is selected (stratified) based on acceleration pulse waves (which distinguish between young and old) and personal information (weight).

For example, a coefficient (light weight α _{yl to} γ _yl at young age, weight α _{yh to} γ _yh at young age, weight α _{yh to} γ _yh at young age, old age, y (o), light weight (l), weight (h) 4 types of formulas (10) to (13) with different weights α _{ol to} γ _ol and older weights α _{oh to} γ _oh ) are prepared, and calculation to be used according to the combination of young, old, light, and weight Select an expression. Whether it is young or old is determined from the acceleration pulse wave, and whether it is light or heavy is determined from the input data.

BP = α _yl · PTT + β _yl · d + γ _yl · Wei + · · + (10)
(Α _yl , β _yl , and γ _yl are coefficients)

BP = α _yh · PTT + β _yh · d + γ _yh · Wei + ·· + (11)
(Α _yh , β _yh , γ _yh are coefficients)

BP = _αol · PTT + _βol · d + _γol · Wei + ·· + (12)
(Α _ol , β _ol , γ _ol are coefficients)

BP = α _oh · PTT + β _oh · d + γ _oh · Wei + · · · · · · (13)
(Α _oh , β _oh , and γ _oh are coefficients)

Then, in the same manner as in Experimental Example 1, blood pressure was estimated by distinguishing the subjects (150 persons) who successfully obtained both the electrocardiogram signal and the pulse wave signal by the four types of age group and body weight. In addition, blood pressure was actually measured using a cuff.

The result is shown in FIG. In addition, VA small of the figure shows young, and VA large shows old. FIG. 9 shows that the correlation coefficient (r) between the estimated blood pressure and the actually measured blood pressure is 0.91 (both types of data are used), and the correlation is extremely high. That is, it can be seen that the blood pressure can be estimated with high accuracy.
[Fourth Embodiment]
Next, the fourth embodiment will be described, but the description of the same contents as the first embodiment will be omitted.

Since the hardware configuration is the same as that of the first embodiment, different contents will be described.
In the present embodiment, an arithmetic expression used for blood pressure estimation is selected (stratified) based on a measurement situation (body motion).

Specifically, as shown in FIG. 10, the driver 41 is photographed by the camera 41, and the image is analyzed to analyze the movement of the hand and the movement of the body part other than the hand.
Then, the body movement status is divided into four types as follows, and an arithmetic expression to be used in each state is selected.

a) When there are many movements of the hand When there are many movements of the hand, it is expected that the electrocardiogram signal cannot be taken well. Therefore, in this case, the following formula (14) similar to the above formula (1) when the above-described electrocardiogram signal is not successfully obtained is adopted. Here, a ₀ and d ₀ are values of the feature values a and d of the acceleration pulse wave when the resting blood pressure BP ₀ is obtained.

BP = BP ₀ + α · (a−a ₀ ) + β · (d−d ₀ ) +... (14)
(Α and β are coefficients)

b) When there is little movement of the hand, but the body (torso part) is moving When there is a lot of movement of the body, it is expected that the pulse wave will have a large baseline fluctuation and the pulse wave signal will not be good. . Therefore, in this case, the following formula (15) similar to the above formula (2) when the above-described pulse wave signal is not successfully obtained is adopted. Here, PTT ₀ and d ₀ are values of the pulse wave propagation velocity PTT and the acceleration pulse wave feature value d when the resting blood pressure BP ₀ is obtained.

BP = BP ₀ + α · (PTT−PTT ₀ ) + β · (d−d ₀ ) + ··· (15)
(Α and β are coefficients)

c) When there is little body movement (movement of hand and torso, etc.) It is expected that both an electrocardiogram signal and a pulse wave signal can be obtained well. Therefore, in this case, when both pulse wave signals can be successfully obtained, the following equation (16) is adopted. In addition, like the said Formula (3) or Formula (4), you may stratify with a young group and an elderly group.

BP = α · PTT + β · d + γ · Wei + (16)
(Α, β and γ are coefficients)

d) When there is a lot of body movement (movement of hand and torso, etc.) In this case, it is expected that neither an electrocardiogram signal nor a pulse wave signal can be obtained well. Therefore, in that case, blood pressure is not estimated.

In the present embodiment, the same effects as in the first embodiment can be obtained.
[Fifth Embodiment]
Next, the fifth embodiment will be described, but the description of the same contents as the first embodiment will be omitted.

Since the hardware configuration is the same as that of the first embodiment, different contents will be described.
In the present embodiment, an arithmetic expression used for blood pressure estimation is selected (stratified) based on other measurement situations (whether driving or stopping).

  a) For example, when driving or stopping, there is a tendency that noise (disturbance) is more likely to appear on the electrocardiogram signal or pulse wave signal due to the influence of body movement or vibration of the vehicle during driving than when stopping. It is conceivable to switch the calculation formula depending on whether the vehicle is driving or stopped.

For example, the following formula (17) can be selected during driving, and the following formula (18) can be selected while stopping. In other words, since the reliability of the electrocardiogram signal and pulse wave signal is considered to be low during driving, the weight of the electrocardiogram signal and pulse wave signal is reduced by adding BP ₀ measured while the vehicle is stopped to the arithmetic expression. . On the other hand, when the vehicle is stopped, the electrocardiogram signal or the pulse wave signal is considered to be highly reliable, so the blood pressure is estimated by increasing the weight of the electrocardiogram signal or the pulse wave signal. Since the parameters are the same as described above, the description thereof is omitted (the same applies hereinafter).
(driving)
BP = BP ₀ + α (PTT-PTT ₀ ) + β (d-d ₀ ) + (17)
(Α and β are coefficients)
(Stopped)
BP = α · PTT + β · d + γ · Wei + (18)
(Α, β and γ are coefficients)

In the present embodiment, the same effects as in the first embodiment can be obtained.

  As other measurement situations, for example, the running situation of the vehicle can be adopted. However, for example, when the vehicle is running on a curve or suddenly accelerates or decelerates, it can be considered that body movement becomes large. Therefore, in the situation where it is expected that the body motion will increase and the reliability of the pulse wave signal and the like will decrease, the equation (17) corresponding to the driving is adopted, otherwise the vehicle stops. You may make it select the said Formula (18) corresponding to inside.

Furthermore, it is determined from the image whether the operation is one-handed or two-handed, and in the case of one-handed operation, since an electrocardiogram signal cannot be obtained, the above formula (1) when only a pulse wave signal is obtained can be employed.
[Sixth Embodiment]
Next, the sixth embodiment will be described, but the description of the same contents as the first embodiment will be omitted.

Since the hardware configuration is the same as that of the first embodiment, different contents will be described.
In the present embodiment, an arithmetic expression used for blood pressure estimation is selected (stratified) based on a measurement environment (temperature, humidity, solar radiation).

a) In the case of solar radiation Since the sunlight is much stronger than the light from the pulse wave sensor 9, as shown in FIG. 12, when there is solar radiation, a large noise may be added to the pulse wave signal. In FIG. 12, the output of the pulse wave sensor 9 is displayed in a reversed manner (for easy viewing).

Therefore, when the sunlight is strong, the following formula (19) is adopted. This expression (19) is an arithmetic expression mainly using the resting blood pressure and the characteristic amount of the electrocardiogram signal.

BP = BP ₀ + α · (PTT−PTT ₀ ) + β · (HR−HR ₀ ) + ···· (19)
(Α and β are coefficients)

On the other hand, when the sunlight is weak, the pulse wave signal can be obtained well, so the following equation (20) is adopted. This expression (20) is an arithmetic expression using a normal pulse wave signal.

BP = α · PTT + β · d + γ · Wei + (20)
(Α, β and γ are coefficients)

Thereby, it becomes difficult to receive the influence of solar radiation, and it can always estimate a blood pressure accurately.

b) In the case of temperature In general, when the temperature is low and cold, the capillaries on the surface of the human body are throttled, so that the pulse wave signal becomes small and unstable as shown in FIG. In FIG. 13 (a), the output of the pulse wave sensor 9 is displayed with its polarity reversed (for easy viewing).

Therefore, when the temperature is lower (than the reference value), the following formula (21) is adopted. This expression (21) is an arithmetic expression mainly using the resting blood pressure and the characteristic amount of the electrocardiogram signal.

BP = BP ₀ + α (PTT-PTT ₀ ) + β (d-d ₀ ) + (21)
(Α and β are coefficients)

On the other hand, when the temperature is high, the pulse wave signal can be obtained well, so the following equation (22) is adopted. This expression (22) is an arithmetic expression using a normal pulse wave signal.

BP = α · PTT + β · d + γ · Wei + (22)
(Α, β and γ are coefficients)

Thereby, it becomes difficult to be influenced by the temperature, and the blood pressure can always be estimated accurately.

c) Humidity In general, on a dry day, the impedance between the driver's hand and the steering electrode becomes high, and the electrocardiogram signal may not be measured well as shown in FIG. The vertical axis in FIG. 14 indicates the output voltage of the electrocardiogram signal when the impedance is different.

Therefore, when the humidity is lower (lower than the reference value), the following formula (23) when the electrocardiogram signal cannot be obtained successfully is adopted. This expression (23) is an arithmetic expression mainly using the resting blood pressure and the characteristic amount of the pulse wave signal.

BP = BP ₀ + α · (a−a ₀ ) + β · (d−d ₀ ) + ··· (23)
(Α and β are coefficients)

On the other hand, when the humidity is high, an electrocardiogram signal can be obtained well, so the following equation (24) is adopted. This expression (24) is an arithmetic expression mainly using a resting blood pressure and an electrocardiogram signal.

BP = BP ₀ + α (PTT−PTT ₀ ) + β (d−d ₀ ) + (24)
(Α and β are coefficients)

In addition, this invention is not limited to the said embodiment at all, and it cannot be overemphasized that it can implement with a various aspect in the range which does not deviate from this invention.

  (1) For example, young people and elderly people may be classified into estimation formulas used when an electrocardiogram signal cannot be obtained well (or when a pulse wave signal cannot be obtained well). In this case, the following formula (25) is used for the younger group, and the following formula (26) is used for the older group. Note that the subscript y of α and β indicates the younger generation, and o indicates the older generation.

BP = BP ₀ + α _y · (a−a ₀ ) + β _y · (d−d ₀ ) +... (25)
(Α _y and β _y are coefficients)

BP = BP ₀ + α _o (a−a ₀ ) + β _o (d−d ₀ ) + (26)
(Α _o and β _o are coefficients)
(2) When an electrocardiogram signal cannot be obtained successfully, the blood pressure can be estimated using only the pulse wave without using BP ₀ as shown in the following equation (27), for example.

BP = α · a + β · d + γ · ctime + (27)
(Α, β and γ are coefficients)

(3) Furthermore, the function of the above-described biological state estimation apparatus can be realized by processing executed by a computer program, and this program can be recorded on a recording medium.

  That is, the function for realizing the above-described program in the computer system can be provided as a program that is activated on the computer system side, for example. In the case of such a program, for example, the program is recorded on a computer-readable recording medium such as a flexible disk, a magneto-optical disk, a CD-ROM, a DVD, and a hard disk, and is used by being loaded into a computer system and started as necessary. be able to. In addition, the program may be recorded as a computer-readable recording medium such as a ROM or a backup RAM, and the ROM or the backup RAM may be incorporated into a computer system.

It is explanatory drawing which shows schematic structure of the biological condition estimation apparatus arrange | positioned in the vehicle interior of 1st Embodiment. It is a block diagram which shows the function of a biological condition estimation apparatus. It is a graph which shows an electrocardiogram signal and a pulse wave signal. It is a graph which shows a pulse wave signal and the signal which differentiated it. It is a graph which shows the electrocardiogram signal and pulse wave signal which change according to a measurement environment. It is a flowchart which shows the arithmetic processing of 1st Embodiment. It is a graph which shows the correlation with the actual value using a cuff, and the calculated value by the biological condition estimation apparatus. It is a graph which shows the correlation of the estimated blood pressure in 2nd Embodiment, and measured blood pressure. It is a graph which shows the correlation of the estimated blood pressure in 3rd Embodiment, and measured blood pressure. It is explanatory drawing which shows the method of detecting the body movement in 4th Embodiment. In 5th Embodiment, it is a graph which shows the change of the parameter during driving | running | working and the case where it does not stratify and the case where it stratifies. It is a graph which shows the output of the pulse wave sensor which changes with solar radiation. (A) is a graph which shows the pulse wave signal which changes with temperature, (b) is a graph which shows the 2nd-order differential value. It is a graph which shows the impedance which fluctuates with humidity.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Living body state estimation apparatus 3 ... Notification apparatus 7 ... Steering 5 ... Manual input part 9 ... Pulse wave sensor 11, 13 ... Electrode

Claims (14)

Among the electrocardiogram signals and pulse wave signals detected from the living body, at least the pulse wave signal is used to estimate the state of the living body.
Of the electrocardiogram signal and the pulse wave signal, measuring means for measuring at least the pulse wave signal;
Among the measured signals, at least the pulse wave signal is analyzed, and calculation means for calculating the characteristic amount of the analyzed signal;
A plurality of estimation means for estimating the state of the living body based on a predetermined algorithm using the feature amount;
A determination unit that determines which of the plurality of estimation units is used to estimate the state of the living body based on a predetermined determination condition;
A biological state estimation device comprising:   The biological state estimation apparatus according to claim 1, wherein the biological state is blood pressure.   The feature quantity of the electrocardiogram signal or the feature quantity of the pulse wave signal used for the estimation means is at least one of PTT, pulse wave AI, pulse wave amplitude, acceleration pulse wave feature quantity, heart rate interval, and heart rate. The living body state estimation apparatus according to claim 1, wherein the biological state estimation apparatus includes one type of feature amount of a pulse wave signal.   The biological state estimation apparatus according to claim 1, wherein the determination unit selects the estimation unit based on a feature amount of the electrocardiogram signal or a feature amount of the pulse wave signal. .   The feature quantity of the electrocardiogram signal or the feature quantity of the pulse wave signal used for the determination means is the fluctuation of the baseline of the pulse wave signal, the amplitude of the pulse wave signal, the feature quantity of the acceleration pulse wave, the amplitude of the electrocardiogram signal, the heartbeat The biological state estimation device according to claim 4, wherein the biological state estimation device is at least one of an interval and a heart rate.   The biological state estimation apparatus according to claim 4 or 5, wherein the determination unit selects the estimation unit based on a feature amount of the electrocardiogram signal or a variance of the feature amount of the pulse wave signal.   The biological state estimation apparatus according to claim 1, wherein the determination unit selects the estimation unit based on personal information of the biological body.   8. The biological state estimating apparatus according to claim 7, wherein the personal information is at least one of age, sex, height, weight, body fat, and disease information.   The biological state estimation apparatus according to claim 1, wherein the determination unit selects the estimation unit based on a measurement state of each signal.   10. The measurement state according to claim 9, wherein the measurement state is at least one of a driving state or a stopping state, a vehicle traveling state, a one-handed or two-handed driving state, and a body movement state. Biological state estimation device.   The biological state estimation apparatus according to claim 1, wherein the determination unit selects the estimation unit based on a measurement environment of the biological body.   The biological state estimation apparatus according to claim 11, wherein the measurement environment is at least one of temperature, humidity, and solar radiation.   The program for implement | achieving the function of the biological condition estimation apparatus in any one of the said Claims 1-12.   A computer-readable recording medium on which the program according to claim 13 is recorded.