JPH09168517A - Heartbeat monitoring device and peripheral circulation monitoring device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a monitoring device which is easy to use and is independent of the operation type. SOLUTION: A heartbeat calculation means 76 calculates a prediction signal S'n based on linear prediction coefficients a1 , a2 ...aP calculated by a linear prediction coefficient calculation means 70, and a value Ico indicating a heartbeat condition of an organism is calculated based on a residual signal en which is a difference between the prediction signal S'n and a pressure pulse wave signal Sn . Amplitude of the residual signal en or a signal strength of frequency analytic value of the residual signal en indirectly represents shrinkage force of a heart muscle or heartbeat amount corresponding to a periodically changed pitch impulse. As only one pressure pulse wave sensor 46 is attached to wrist or toe of an organism to detect pressure pulse wave generated from arterys of peripherals such as radius artery, the dorsal artery of foot, etc., this device is easy to use and is independent of the operation type.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus for monitoring a cardiac output state and a peripheral circulation state of a living body by analyzing a pressure pulse wave of the living body using a linear prediction method.

[0002]

2. Description of the Related Art For example, in order to understand the condition of a living body during or after surgery, it is desired to monitor not only the blood pressure value and pulse rate but also the cardiac output state and peripheral circulation state of the living body. If the cardiac output state and the peripheral circulation state can be grasped, it becomes easy to diagnose the shock state of the living body or the depth of anesthesia at an early stage, for example.

[0003]

However, conventionally, there is no device for easily monitoring the cardiac output condition and the peripheral circulation condition, and it is difficult to apply the device easily. For example,
As a device for monitoring the cardiac output state, two pairs of electrodes wrapped around the body and neck are used to detect changes in impedance between the body and neck, and the cardiac output is based on the impedance. A device for monitoring quantity has been proposed (USP 4,437,469). However, in such a device, it is necessary to wrap the electrodes around the body and the neck, which makes mounting the electrodes complicated, and it may be impossible to mount the electrodes depending on the surgical site.

Further, for example, as a device for detecting the peripheral circulation state, a transmission type oxygen saturation sensor and a reflection type oxygen saturation sensor are provided at two places on the living body, and the transmission type oxygen saturation sensor and the reflection type oxygen saturation sensor are provided. A peripheral circulation detection device has been proposed which determines the peripheral circulation state based on the oxygen saturation measured by the oxygen saturation sensor (Japanese Patent Laid-Open No. 4-6).
1849). However, in such a device, it is necessary to attach two types of oxygen saturation sensors to the living body, and therefore the attachment becomes complicated, and it is difficult to use during hypothermic anesthesia in which capillaries of the epidermis contract. there were.

The present invention has been made in view of the above circumstances, and a first object of the present invention is to provide a cardiac output monitoring apparatus which is easy to use and is hardly affected by the type of surgery. To do. A second object is to provide a peripheral circulation state monitoring device which is easy to use and is hardly affected by the type of surgery.

[0006]

A first aspect of the present invention for achieving the above first object is to provide a heartbeat of a living body based on a pressure pulse wave detected from an artery of the living body. A cardiac output status monitoring device for monitoring the output status,
(a) a pressure pulse wave sensor that detects a pressure pulse wave generated from a peripheral artery of the living body, and outputs a pressure pulse wave signal that represents the pressure pulse wave, and (b) is output from the pressure pulse wave sensor. Linear prediction coefficient calculation to minimize the residual between the predicted value and the actual value predicted from the pressure pulse wave signal in the form of a linear combination of past sampled values of the pressure pulse wave signal. Means, and (c) a prediction signal is obtained from the linear prediction coefficient calculated by the linear prediction coefficient calculation means, and the cardiac output is calculated based on the residual signal which is the difference between the prediction signal and the pressure pulse wave signal. And a cardiac output state calculating means for calculating a value indicating the state.

[0007]

[Effect of the first invention] With this configuration, the cardiac output state calculating means obtains a prediction signal from the linear prediction coefficient calculated by the linear prediction coefficient calculating means, and the prediction signal and the pressure pulse wave signal are obtained. Since the value indicating the cardiac output state is calculated based on the residual signal that is the difference between the pressure pulse and the pressure pulse generated from peripheral arteries such as the radial artery and the dorsalis pedis artery for the living body. Only one pressure pulse wave sensor needs to be worn on the wrist or toe to detect waves. Therefore, it is not necessary to wind an electrode for detecting a change in impedance between the body and the neck around the body and the neck, which simplifies use and has the advantage that it is not easily affected by the type of surgery. is there.

[0008]

A second aspect of the present invention for achieving the above second object is to provide a peripheral circulation of a living body based on a pressure pulse wave detected from an artery of the living body. A peripheral circulatory condition monitoring device for monitoring a condition, comprising: (a) detecting a pressure pulse wave generated from an artery in a peripheral part of the living body, and outputting a pressure pulse wave signal representing the pressure pulse wave. Wave sensor, (b) linear prediction coefficient calculation means for calculating a linear prediction coefficient from the pressure pulse wave signal output from the pressure pulse wave sensor, and (c) linear prediction calculated by the linear prediction coefficient calculation means Peripheral circulation state calculating means for calculating a value indicating the peripheral circulation state based on the coefficient.

[0009]

[Effect of the second invention] In this way, the peripheral circulation state calculating means calculates the value indicating the peripheral circulation state based on the linear prediction coefficient calculated by the linear prediction coefficient calculating means. For a living body, only one pressure pulse wave sensor needs to be attached to the wrist or toe in order to detect the pressure pulse wave generated from peripheral arteries such as the radial artery and the dorsalis pedis artery. Therefore, it is not necessary to wind electrodes around the body and neck to detect the change in impedance between the body and neck, which simplifies the use and reduces hypothermia where the capillaries of the epidermis contract. Since the pressure pulse wave can be detected from the peripheral artery even during anesthesia, there is an advantage that it is hardly affected by the type of surgery.

[0010]

Another aspect of the present invention, preferably, the cardiac output state calculation means calculates a prediction value of the pressure pulse wave from the linear prediction coefficient calculated by the linear prediction coefficient calculation means. It includes a calculating means and a residual signal calculating means for calculating a residual signal by subtracting the predicted value calculated by the predicted value calculating means from the pressure pulse wave signal.

Further, preferably, the cardiac output state calculating means determines the amplitude of the residual signal, or performs the frequency analysis processing of the residual signal to obtain the signal strength of the frequency analysis value. A frequency analysis value determining means for determining is further provided, and an amplitude value of the residual signal, or a magnitude of the frequency analysis value, or a value indicating a cardiac output state that is a predetermined evaluation value having a linear or nonlinear relationship with the amplitude value. decide.

Further, preferably, the cardiac output state monitoring device further includes a cardiac output state display means for displaying a value indicating the cardiac output state calculated by the cardiac output state calculation means on a display. Including. This indicator updates and displays the value indicating the cardiac output state by a numerical value or a graph, or displays the value indicating the cardiac output state by a trend graph showing changes over time. By doing so, the value indicating the cardiac output state is displayed on the display, so that the medical staff can easily know the cardiac output state of the living body.

Further, preferably, the peripheral circulation state monitoring device further includes peripheral circulation state display means for displaying a value indicating the peripheral circulation state calculated by the peripheral circulation state calculation means on a display. The display updates and displays the value indicating the peripheral circulation state by a numerical value or a graph, or displays the value indicating the peripheral circulation state by a trend graph showing a change over time. In this way, the value indicating the peripheral circulation state is displayed on the display, so that the medical staff can easily know the peripheral circulation state of the living body.

Further, preferably, in the cardiac output condition monitoring device or the peripheral circulation condition monitoring device, the linear prediction coefficient calculating means calculates a PARCOR coefficient as the linear prediction coefficient. By doing this, PARC
Since the OR coefficient is an orthogonalized partial autocorrelation function, it is possible to know the cardiac output state or the peripheral circulation state with higher accuracy.

[0015]

DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be described below with reference to the drawings. FIG. 1 shows the configuration of a continuous blood pressure monitoring device 8 having a cardiac output monitoring function and a peripheral circulation monitoring function, which is an embodiment of the present invention.

In FIG. 1, a continuous blood pressure monitoring device 8 has a rubber bag in a cloth band-shaped bag, and for example, a patient's upper arm 1
2, a pressure sensor 14 connected to the cuff 10 via a pipe 20, and a switching valve 1
6 and an air pump 18. The switching valve 16 has three states: a pressure supply state that allows the pressure to be supplied to the cuff 10, a slow exhaust pressure state that gradually exhausts the cuff 10, and a rapid exhaust pressure state that rapidly exhausts the cuff 10. It is configured so that it can be switched to one of two states.

The pressure sensor 14 detects the pressure in the cuff 10 and outputs a pressure signal SP representing the pressure to the static pressure discrimination circuit 22.
And the pulse wave discrimination circuit 24. The static pressure discriminating circuit 22 includes a low-pass filter that passes only a signal component having a frequency equal to or lower than a predetermined frequency, discriminates the cuff pressure signal SK representing the static pressure included in the pressure signal SP, that is, the cuff pressure, and outputs the cuff pressure signal SK as A. The signal is supplied to the electronic control circuit 28 via the / D converter 26.

The pulse wave discriminating circuit 24 passes a signal in a frequency band constituting a cuff pulse wave which is a pressure vibration generated in the cuff 10 in synchronism with a heartbeat, but removes other frequency components. A cuff pulse wave signal M provided with a filter and discriminated from the pressure signal SP is supplied to the electronic control circuit 28 via the A / D converter 30.

The electronic control circuit 28 includes a CPU 29, R
The CPU 29 is composed of a so-called microcomputer including an OM 31, a RAM 33, and an I / O port (not shown), and the CPU 29 processes an input signal while using the storage function of the RAM 33 according to a program stored in the ROM 31 in advance. By executing, the drive signal is output from the I / O port to control the switching valve 16, the air pump 18, and the display 32.

The pressure pulse wave detection probe 34 is used for the cuff 10.
Upper arm 12 with or without
The wrist 42 on the downstream side of the artery is detachably attached to the wrist 42 by the wearing band 40 in a state where the open end of the housing 36 having a container shape faces the body surface 38. Inside the housing 36, a pressure pulse wave sensor 46 is provided via a diaphragm 44 so as to be relatively movable and protrudable from an open end of the housing 36, and a pressure chamber 48 is formed by the housing 36, the diaphragm 44, and the like. Have been. This pressure chamber 48
The inside, through the air pump 50 Kara pressure regulator valve 52, so that the pressure air is supplied, thereby, the pressure pulse wave sensor 46 is the body with a pressing force P _HD corresponding to the pressure in the pressure chamber 48 Pressed against surface 38.

The pressure pulse wave sensor 46 is constructed by arranging a large number of semiconductor pressure sensitive elements (not shown) on a pressing surface 54 of a semiconductor chip made of, for example, single crystal silicon, and the body of the wrist 42. Pressing onto the radial artery 56 of the surface 38 causes it to develop from the radial artery 56
A pressure oscillating wave, that is, a pressure pulse wave that is transmitted to the sensor is detected, and a pressure pulse wave signal S representing the pressure pulse wave is supplied to the electronic control circuit 28 via the A / D converter 58.

The CPU 29 of the electronic control circuit 28 is
According to a program stored in advance in the ROM 31, a drive signal is output to the air pump 50 and the pressure regulating valve 52 to adjust the pressure in the pressure chamber 48, that is, the pressing force of the pressure pulse wave sensor 46 on the skin. Thereby, when monitoring the blood pressure, the optimum pressing force P _HDP of the pressure pulse wave sensor 46 is determined based on the pressure pulse waves sequentially obtained in the pressure change process in the pressure chamber 48, and the optimum pressing force of the pressure pulse wave sensor 46 is determined. The pressure regulating valve 52 is controlled so as to maintain P _HDP .

FIG. 2 is a functional block diagram for explaining a main part of the control function of the electronic control circuit 28 in the continuous blood pressure monitoring device 8. In the figure, the blood pressure measuring means 62 is well known on the basis of the change in the magnitude of the pulse wave sampled by the pulse wave discriminating circuit 24 in the process of changing the compression pressure for gradually increasing or decreasing the compression pressure of the cuff 10. The patient's systolic blood pressure value SAP and diastolic blood pressure value DAP are measured by the oscillometric method (JIS T 1115).

The pressure pulse wave sensor 46 preferably detects the pressure pulse wave generated from the radial artery 56 of the wrist 42 by being pressed by the wrist 42 of the arm different from the arm on which the patient's cuff 10 is mounted. . Pressure pulse wave blood pressure correspondence determination means 64
Is a predetermined relationship for a predetermined patient between the magnitude P _S of the pressure pulse wave detected by the pressure pulse wave sensor 46 and the blood pressure value (monitored blood pressure value MBP) measured by the blood pressure measuring means 62. . This correspondence is shown in FIG. 6, for example, and is represented by the formula MBP = A · P _S + B. Here, A is a constant indicating the slope, and B is a constant indicating the intercept.

The monitoring blood pressure value determining means 66 determines the magnitude P _{S of the} pressure pulse wave detected by the pressure pulse wave sensor 46 from the corresponding relationship, that is, the maximum value (upper peak value) P _Smax and the minimum value (lower peak value). _Systolic blood pressure value MBP _SYS based on P _Smin
And the minimum blood pressure value MBP _DIA (monitor blood pressure value) are sequentially determined, and the determined monitoring blood pressure value MBP is continuously output to the display 32.

The cuff pressure control means 68 changes the compression pressure of the cuff 10 according to a well-known measurement procedure during the measurement period of the blood pressure measurement means 62 which is activated at a predetermined cycle for the calibration of the above relation. . For example, the cuff pressure control means 68 pressurizes the cuff 10 to a target pressure increase value set to about 180 mmHg, which is higher than the systolic blood pressure of the patient, and then at a speed of about 3 mmHg / sec in the measurement section in which the blood pressure measurement algorithm is executed. Slowly lower the pressure,
When the blood pressure measurement is completed, the pressure in the cuff 10 is released.

On the other hand, the linear prediction coefficient calculation means 70
Output from the wave sensor 46 and a predetermined sampling period
The pressure pulse wave signal S (that is,
C, S _nP, ... S_n-2, S_n-1), The current value S
_nPredicted value S '_nIs the form of a linear combination of past sampled values
(Linear Prediction;
 LP), the residual e_n(= S_n-S '
_n) Is minimized so that the linear prediction coefficient a₁, A_Two・ ・
・ A_PIs calculated.

[0028]

[Number 1] _{S 'n = - (a 1} S n-1 + a 2 S n-2 + ···
+ A _P S _nP )

The linear prediction coefficient a₁, A_Two... a
_PIs, for example, the sum of squares ε of the residuals shown in Equation 2.^TwoTo
In order to find the minimum value, the sum of squares ε^TwoLinear pre
Measurement coefficient a _iThe condition (δε^Two
/ Δa_i= 0). Sand
The first and second terms on the right side of Equation 3 have the same value
The expression expressing is not valid for each i (1 ≦ i ≦ p)
Therefore, it is represented by the matrix shown in Expression 4. This matrix
Is the linear prediction coefficient a₁, A_Two... a_PIs an unknown
Since it is a simultaneous linear equation of p × p, ΣS_niS
_nkIs given, the solution of this simultaneous linear equation is a
_iIs required. For example, from the pressure pulse wave signal data, ΣS
_niS_nkIs calculated and substituted into the above simultaneous linear equations.
One method is to substitute the autocorrelation of the pressure pulse wave signal S.
Method is used.

The autocorrelation function R _i of the pressure pulse wave signal S shown in Equation 5 is R _i = R _−i due to its symmetry, and S _ni and S
_{Since the} autocorrelation with _nk is given as a function of only the time difference (i−k) as shown in Expression 6, from this expression, the simultaneous linear equation of Expression 7 is shown in Expression 6 using the autocorrelation function. Equation 8 is expressed as a matrix.

Here, in a predetermined section of the pressure pulse wave signal S, assuming that the number of data in the section is N, the above autocorrelation function R
_i is obtained from Equation 8 based on the pressure pulse wave signal S, and from Equation 7 above, linear prediction coefficients a ₁ , a _2, ... A _P are obtained based on the autocorrelation function R _i . FIG. 3 is a block diagram showing the contents of the linear prediction coefficient calculation means 70. The autocorrelation means 72 receives the input pressure pulse wave signal S
The autocorrelation function R _i in the predetermined section of (t) is calculated by Equation 8
Is calculated based on the data of N pressure pulse wave signals in the predetermined section. “Z ⁻¹ ” described in the autocorrelation means 72 is a delay element and “x” is a multiplication element.
Then, the simultaneous linear equation calculation means 74 calculates the linear prediction coefficients a ₁ , a ₂ based on the autocorrelation function R _i calculated by the above autocorrelation means 72 from the simultaneous linear equations of Equation 7.
.. Calculate a _P.

[0032]

(Equation 2)

[0033]

(Equation 3)

[0034]

(Equation 4)

[0035]

(Equation 5)

[0036]

(Equation 6)

[0037]

(Equation 7)

[0038]

(Equation 8)

Further, in FIG. 2, the cardiac output state calculating means 76 calculates the prediction signal (prediction value) S from the linear prediction coefficients a ₁ , a ₂ ... A _P calculated by the linear prediction coefficient calculating means 70. ' _n is obtained, and the residual signal e _n (= S _n −) is the difference between the predicted signal S ′ _n and the actual pressure pulse wave signal S _n.
A value I _CO indicating the cardiac output state of the living body based on S ′ _n ).
Is calculated and displayed on the display 32. For example, the cardiac output state calculating means 76 calculates the linear prediction coefficients a ₁ , a ₂ ...
... on the basis of a _P, a predicted value calculating means 78 for calculating a predicted value S _'n of the pressure pulse wave signal, the actual pressure pulse wave signals predicted value calculated by the predictive value calculating unit 78 from the S _n S ' _n
By subtracting the residual signal e _n (= S _n −S ′ _n ).
And a residual signal calculating means 80 for calculating

The amplitude of the residual signal e _n or the residual signal thereof, which is the difference between S _n at a predetermined time and its predicted signal S ′ _n in a predetermined section of the pressure pulse wave signal S (t) which is a periodic signal. the signal strength of the frequency analysis value of e _n (pitch impulse signal power) would indicate indirectly the contractile force or cardiac output of the heart muscle that corresponds to cyclically varying pitch impulses. Therefore, the cardiac output state calculating means 76 is
Preferably, further includes an amplitude determining means, or frequency analysis value determining means for determining a signal strength of the frequency analysis value by performing a frequency analysis processing of the residual signal e _n to determine the amplitude of the residual signal e _n , the amplitude value of the residual signal e _n, or frequency analysis value of the magnitude, or a linear or value indicating a cardiac output state is a predetermined evaluation value in the non-linear relationship I
Determine _CO .

The cardiac output status display means 82 indicates a value I indicating the cardiac output status calculated by the cardiac output status calculation means 76.
_CO is displayed on the display 32. The display 32 sequentially updates and displays the value I _CO indicating the cardiac output state by a numerical value or a graph, or displays the value I _CO indicating the cardiac output state by a trend graph showing a change over time. .

Peripheral circulation state calculating means 84 includes linear predictive coefficients a ₁ and a calculated by linear predictive coefficient calculating means 70.
A value I _PE indicating the peripheral circulation state is calculated based on ₂ ... a _P and displayed on the display 32. For example, the peripheral circulation state calculation means 84 uses the linear prediction coefficients a ₁ , a ₂ ...
The size of the coefficient of a predetermined order including the typical first-order coefficient a ₁ of a _P is determined by the total value or average value thereof, and there is a linear or nonlinear relationship with the total value or average value. The value I _PE indicating the peripheral circulation state, which is a predetermined evaluation value, is determined.

The peripheral circulation state display means 86 causes the display 32 to display the value I _PE indicating the peripheral circulation state calculated by the peripheral circulation state calculation means 84. The display 32 sequentially updates and displays the value I _PE indicating the peripheral circulation state by a numerical value or a graph, or displays the value I _PE indicating the peripheral circulation state by a trend graph showing a change over time.

FIG. 4 is a flow chart for explaining the main part of the control operation of the electronic control circuit 28 in the continuous blood pressure monitoring device 8. FIG. 5 shows the cardiac output state and peripheral circulation state determination / output routine of FIG. It is a flow chart which shows in detail.

In step SA1 in FIG. 4 (hereinafter, steps will be omitted), the pressure in the pressure chamber 48 is gradually increased by controlling the air pump 50, and the pressure chamber 4 is increased.
The pressure in the pressure chamber 48 that maximizes the amplitude of the pressure pulse wave sequentially detected by the pressure pulse wave sensor 46 in the process of gradually increasing the pressure in 8, ie, the optimum pressing force P _HDP of the pressure pulse wave sensor 46 is determined. , The pressure in the pressure chamber 48 is the optimum pressing force P.
_By being held in _HDP , the pressing force of the pressure pulse wave sensor 46 is held at an optimum constant value.

Next, in SA2 to SA4 corresponding to the cuff pressure control means 68, the air pump 18 is controlled to control the pressure of the cuff 10 for blood pressure measurement. That is, first, after the pressurization of the cuff 10 is started in SA2, whether or not the pressure in the cuff 10 reaches a target cuff pressure (for example, 180 mmHg) set higher than the patient's expected systolic blood pressure value in SA3. Is judged. Initially, the determination of SA3 is denied and SA2 and subsequent steps are repeatedly executed. However, when the pressure of the cuff 10 reaches the target cuff pressure and the determination of SA3 is affirmed, at SA4,
The pressure of the cuff 10 is suitable for blood pressure measurement by stopping the air pump 18 and switching the switching valve 16 to the slow exhaust pressure state to lower the pressure in the cuff 10 at a predetermined slow speed. Speed eg 3 to 5 mmHg / sec
It can be lowered at a moderate speed.

Subsequently, at SA5, it is judged whether or not the cuff pulse wave signal M is input. If the determination of SA5 is negative, the above SA4 and subsequent steps are repeatedly executed.
When the determination of SA5 is affirmative, the blood pressure measuring means 6
The blood pressure measurement algorithm is executed in SA6 corresponding to 2. That is, the systolic blood pressure is determined in accordance with the well-known oscillometric blood pressure value determination algorithm based on the change in the amplitude of the pulse wave represented by the cuff pulse wave signal M that is sequentially obtained in the step of gradually reducing the pressure in the cuff 10 as described above. The value SAP,
A mean blood pressure value MAP and a diastolic blood pressure value DAP are determined.

At SA7, the systolic blood pressure value SAP, the mean blood pressure value MAP, and the diastolic blood pressure value DAP at SA6.
Is determined. If the determination at SA7 is negative, the steps from SA4 onward are repeatedly executed, but if the determination at S7 is affirmative, at SA8, the switching valve 16 is switched to the rapid exhaust pressure state to rapidly exhaust the pressure in the cuff 10. At the same time, the blood pressure value determined in SA6 is displayed on the display 32.

Next, the pressure pulse wave blood pressure correspondence relationship determining means 6
At SA9 corresponding to 4, the correspondence between the magnitude P _S of the pressure pulse wave signal S from the pressure pulse wave sensor 46 and the blood pressure values SAP and DAP by the cuff 10 measured at SA6 is obtained. That is, one pulse of the pressure pulse wave is read from the pressure pulse wave sensor 46, the maximum value P _Smax and the minimum value P _Smin of the pressure pulse wave are determined, and the maximum value P _Smax and the minimum value of the pressure pulse wave are determined. Cuff 10 with P _Smin and SA3
Blood pressure value SAP and minimum blood pressure value D measured by
Based on AP and the magnitude P of the pressure pulse wave signal S shown in FIG.
The correspondence between _S and the monitored blood pressure value MBP is determined.

When the pressure pulse wave blood pressure correspondence is determined as described above, the pressure pulse wave signal S input from the pressure pulse wave sensor 46 at a predetermined sampling cycle of, for example, several milliseconds is read at SA10. Be confused. And SA11
5, the cardiac output state and peripheral circulation state determination / output routine shown in FIG. 5 is executed based on the pressure pulse wave signal S.

At SB1 in FIG. 5, it is judged whether or not the pressure pulse wave signal S in a predetermined section set in advance is read.
If the determination in SB1 is negative, this routine is terminated and SA12 and subsequent steps in FIG. 4 are executed. That is, in SA12, a pair of upper peak and lower peak of the pressure pulse wave signal S is input, and it is determined whether or not the upper peak value and the lower peak value have been determined.

When the determination at SA12 is negative,
When SA10 and subsequent steps are repeatedly executed, but when the result is affirmative, in SA13 corresponding to the monitoring blood pressure value determining means 66, from the pressure pulse wave blood pressure correspondence relationship of FIG. Based on the maximum value P _Smax (upper peak value) and the minimum value P _Smin (lower peak value) of the pressure pulse wave S (t) from the pressure pulse wave sensor 46 in P _HDP, the systolic blood pressure value MBP _SYS and the diastolic blood pressure value MBP _DIA (monitor blood pressure value) is determined, and the determined monitor blood pressure value is displayed on the display 32 together with the continuous waveform of the pressure pulse wave.

However, if the determination at SB1 is affirmative in the routine of FIG. 5, the linear prediction coefficient calculation means 7 is used.
By executing SB2 to SB4 corresponding to 0, the pressure pulse wave signal S in a predetermined section that is output from the pressure pulse wave sensor 46 and is A / D converted at a predetermined sampling cycle.
(That is, S _nP , ... S _n-2 , S _n-1 )
A predicted value S _'n current values S _n, the form of a linear combination of the past sample values _{[S n = - (a 1 S} n-1 + a 2 S n-2 + ···
+ A _P S _nP )]
ction; LP), the residual e _n (= S _n
−S ′ _n ) is minimized so that the linear prediction coefficients a ₁ , a
₂ ... a _P is calculated.

First, S corresponding to the autocorrelation means 72.
In B2, the autocorrelation function R _i in the predetermined section of the input pressure pulse wave signal S (t) is calculated based on the data of N pressure pulse wave signals in the predetermined section from the above-mentioned formula 8.
Next, S corresponding to the simultaneous linear equation calculation means 74
In B3, the above SB2 is calculated from the simultaneous linear equations of the equation 7.
The linear prediction coefficients a ₁ , a ₂ ... A _P are calculated based on the autocorrelation function R _i calculated by Then, in SB4, the linear prediction coefficients a ₁ , a ₂ ... A _P calculated in SB3 are determined as the linear prediction coefficients in the current section and stored in a predetermined storage area in the RAM 33.

Next, the heartbeat output state calculating means 76 is paired.
By executing SB5 to SB7 corresponding to the above,
Linear prediction coefficient a determined in SB4₁, A_Two・ ・
・ A _PTo predicted signal (predicted value) S '_nAnd predict that
Signal S '_nAnd the actual pressure pulse wave signal S_nResidual difference that is the difference with
Issue e_n(= S_n-S '_n) The cardiac output of the living body based on
Value I indicating the status_COIs calculated and displayed on the display 32.
That is, first, SB5 corresponding to the predicted value calculation means 78
In the equation 1, the linear prediction coefficient a₁, A
_Two... a_PAnd the sump of the pressure pulse wave signal S (t) up to that point
Ring input value S _n-1, S_n-2・ ・ ・ S_nPAnd based on
Predicted value of pressure pulse wave signal S '_nIs calculated.

[0056] Then, in SB6 corresponding to the residual signal calculating unit 80, the residual signal e by subtracting the actual estimated value S _'n calculated by the predicted value calculation unit 78 from the pressure-pulse-wave signal S _{n n (= S n -S 'n} ) is calculated. Then, in SB7, or amplitude of the residual signal e _n is determined, or the signal intensity of the frequency analysis value by performing a frequency analysis processing of the residual signal e _n is determined, the residual signal e _n A magnitude of the amplitude value or the frequency analysis value, or a value I _CO indicating a cardiac output state, which is a predetermined evaluation value having a linear or non-linear relationship with the magnitude, is determined.

Next, the in SB8 corresponding to the peripheral circulation state calculation unit 84, based on the linear prediction coefficients a _1, a ₂ ··· a _P determined in the SB4, a value indicating a peripheral circulation state of a living body The I _PE is calculated and displayed on the display 32. For example, as the value I _PE that indicates the peripheral circulation state of a living body, the size of the predetermined order of the coefficients including the typical primary coefficients a ₁ of the linear prediction coefficients _{a 1, a 2 ··· a P} , total Alternatively, the average value is determined, and the total value or average value or a predetermined evaluation value having a linear or non-linear relationship with the average value is determined.

At SB9 corresponding to the cardiac output status display means 82 and peripheral circulation status display means 86, the value I _CO indicating the cardiac output status determined at SB7 is displayed on the display 32. The value I _PE indicating the peripheral circulation state determined in SB8 is displayed on the display 32.
Will be displayed. For example, in this SB9, the value I _CO indicating the cardiac output state and the value I _PE indicating the peripheral circulation state are obtained.
, Is displayed and updated sequentially by numerical values or graphs,
Alternatively, it is displayed by a trend graph showing changes over time.

As described above, according to the present embodiment, the linear prediction coefficient a ₁ calculated by SB5 corresponding to the linear prediction coefficient calculation means 70 by SB5 to SB7 corresponding to the cardiac output state calculation means 76, The predicted signal S ′ _n is obtained based on a ₂ ... A _P , and the cardiac output of the living body is calculated based on the residual signal e _n that is the difference between the predicted signal S ′ _n and the pressure pulse wave signal S _n. A value I _CO indicating the state is calculated. The amplitude of the residual signal e _n, or the signal strength of the frequency analysis values of the residual signal e _n (pitch impulse signal power), contractile force or cardiac output of the heart muscle that corresponds to cyclically varying pitch impulse Is considered to indirectly indicate. Therefore, for the living body, only one pressure pulse wave sensor 46 is attached to the wrist or the tip of the foot in order to detect the pressure pulse wave generated from peripheral arteries such as the radial artery and the dorsalis pedis artery. Good. Therefore, it is not necessary to wind an electrode for detecting a change in impedance between the body and the neck around the body and the neck, which simplifies use and has the advantage that it is not easily affected by the type of surgery. is there.

Further, according to the present embodiment, the linear prediction coefficients a ₁ , a _2, ... A calculated by SB8 corresponding to the peripheral circulation state calculating means 84 by SB4 corresponding to the linear prediction coefficient calculating means 70. Based on _P , the value I _PE indicating the peripheral circulation state of the living body is calculated. The pressure pulse wave generated in the aorta is affected by the process of propagating to the radial artery 56, which is a relatively peripheral pressure pulse wave detection site, resulting in the pressure pulse wave signal S (t). Linear prediction coefficient a ₁ ,
It is considered that a ₂ ... A _P corresponds to the component that has influenced the effect, that is, the peripheral circulation state. Therefore, for the living body, only one pressure pulse wave sensor 46 is attached to the wrist or the tip of the foot in order to detect the pressure pulse wave generated from peripheral arteries such as the radial artery and the dorsalis pedis artery. Good. Therefore, it is not necessary to wind electrodes around the body and neck to detect the change in impedance between the body and neck, which simplifies the use and reduces hypothermia where the capillaries of the epidermis contract. Since pressure pulse waves can be detected from peripheral arteries even during anesthesia,
It has the advantage that it is not easily affected by the type of surgery.

Further, according to the present embodiment, the value I _CO indicating the cardiac output state displayed on the display 32 by the cardiac output state display means 82, or the value I _CO displayed on the display 32 by the peripheral circulation state display means 86. The displayed value I _PE indicating the peripheral circulation state is updated and displayed by a numerical value or a graph, or is displayed by a trend graph showing a change over time. In particular, by displaying the trend graph on the display 32, the medical staff can easily know the cardiac output state or the peripheral circulation state of the living body.

Although one embodiment of the present invention has been described in detail with reference to the drawings, the present invention can be implemented in still another mode.

For example, in the above-mentioned embodiment, the cardiac output state calculating means 76 and the peripheral circulation state calculating means 84.
So although the linear prediction coefficients a _1, a ₂ ··· a _P has been used, instead of the linear prediction coefficients _{a 1, a 2 ··· a P} , PARCOR coefficient k which is a kind of linear prediction coefficients _n may be used. This PARCOR coefficient k _n is a signal obtained by removing the predictable part from the (n−1) sample values sandwiched between the pressure pulse wave signals S _t and S _tn , that is, the normalization of the residual signal. It is defined as an autocorrelation function, and between the linear prediction coefficient a _i ^(n-1) and a _n ⁽ⁿ⁾ = -k.
There is a relationship of _n . In this way, the PARCO
Since the R coefficient is an orthogonalized partial autocorrelation function,
It is possible to know the cardiac output state or the peripheral circulation state with high accuracy.

Also, the continuous blood pressure monitoring device 8 of the above-mentioned embodiment.
In this case, both the cardiac output state and the peripheral circulation state were monitored by determining the value I _CO indicating the cardiac output state and the value I _PE indicating the peripheral circulation state, respectively. Does not matter.

Further, in the above-mentioned embodiment, the continuous blood pressure monitoring device 8 has the cardiac output monitoring function and the peripheral circulation monitoring function.
However, the device for monitoring the cardiac output state or the device for monitoring the peripheral circulation state may be independently configured.

Further, in the above-mentioned embodiment, the value I _CO indicating the cardiac output state and the value I _PE indicating the peripheral circulation state are values corrected or normalized by using other parameters as necessary. May be done.

Although not specifically exemplified, the present invention is
Various changes can be made without departing from the spirit of the invention.

[Brief description of the drawings]

FIG. 1 is a diagram illustrating a configuration of a continuous blood pressure monitoring device having a function of monitoring a cardiac output state and a peripheral circulation state, which is an embodiment of the present invention.

FIG. 2 is a functional block diagram illustrating a main part of a control function of an electronic control circuit 28 in the embodiment of FIG.

FIG. 3 is a diagram illustrating in detail the configuration of a linear prediction coefficient calculation unit in FIG.

FIG. 4 is a flowchart illustrating a main part of control operation of an electronic control circuit 28 in the embodiment of FIG.

FIG. 5 is a flowchart illustrating in detail the contents of a cardiac output state / peripheral circulation state determination / output routine of FIG.

FIG. 6 is a diagram showing a correspondence relationship between the pressure pulse wave and the blood pressure value of FIG. 4.

[Explanation of symbols]

8: Continuous blood pressure monitoring device (cardiac output monitoring device, peripheral circulation monitoring device) 32: Indicator 46: Pressure pulse wave sensor 56: Radial artery 70: Linear prediction coefficient calculation means 72: Autocorrelation means 74: Coalition Linear equation calculation means 76: Cardiac output state calculation means 78: Prediction value calculation means 80: Residual signal calculation means 82: Cardiac output state display means 84: Peripheral circulation state calculation means 86: Peripheral circulation state display means

Claims (7)

[Claims] 1. A cardiac output state monitoring device for monitoring a cardiac output state of a living body based on a pressure pulse wave detected from an artery of the living body, which is generated from an artery at a peripheral portion of the living body. Detecting pressure pulse wave,
A pressure pulse wave sensor that outputs a pressure pulse wave signal that represents the pressure pulse wave, and a pressure pulse wave signal that is output from the pressure pulse wave sensor in the form of a linear combination of past sampling values of the pressure pulse wave signal. A linear prediction coefficient calculation unit that calculates a linear prediction coefficient for minimizing the residual between the predicted prediction value and the actual value, and a prediction signal is calculated from the linear prediction coefficient calculated by the linear prediction coefficient calculation unit. A cardiac output state calculating means for calculating a value indicating the cardiac output state based on a residual signal which is a difference between a prediction signal and the pressure pulse wave signal, and a cardiac output state monitoring device. apparatus. 2. The cardiac output state calculation means, a predicted value calculation means for calculating a predicted value of the pressure pulse wave from the linear prediction coefficient calculated by the linear prediction coefficient calculation means, and the pressure pulse wave signal. 2. The cardiac output monitoring apparatus according to claim 1, further comprising: a residual signal calculating unit that calculates a residual signal by subtracting the predicted value calculated by the predicted value calculating unit from the residual signal calculating unit. 3. The cardiac output status monitoring device according to claim 1, further comprising cardiac output status display means for displaying a value indicating the cardiac output status calculated by the cardiac output status calculation means on a display. . 4. The linear prediction coefficient calculated by the linear prediction coefficient calculation means is a PARCOR coefficient.
Cardiac output monitoring device. 5. A peripheral circulatory condition monitoring device for monitoring a peripheral circulatory condition of a living body based on a pressure pulse wave detected from an artery of the living body, wherein the pressure pulse is generated from an artery in the peripheral part of the living body. Detect the waves,
A pressure pulse wave sensor that outputs a pressure pulse wave signal representing the pressure pulse wave, a linear prediction coefficient calculation unit that calculates a linear prediction coefficient from the pressure pulse wave signal output from the pressure pulse wave sensor, and the linear prediction A peripheral circulation state monitoring device for calculating a value indicating the peripheral circulation state based on the linear prediction coefficient calculated by the coefficient calculation means. 6. The peripheral circulation state monitoring device according to claim 5, further comprising peripheral circulation state display means for displaying a value indicating the peripheral circulation state calculated by the peripheral circulation state calculation means on a display. 7. The linear prediction coefficient calculated by the linear prediction coefficient calculation means is a PARCOR coefficient.
Peripheral circulation condition monitoring device.