JP2000023930A - Heartbeat disturbance detecting device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To detect the heartbeat signals of a subject to immediately and automatically detect the disturbance of pulse rates. SOLUTION: A heartbeat signal detecting device 1 samples the heartbeat signals of a subject for output to a control part 2. The control part 2 first calculates an RR interval that is the interval of R waves in the heartbeat signals. Next, from a plurality of continuous RR intervals stored in a memory 4, the predicted value of the next or previous RR interval is calculated. When the difference between the predicted value and the measured RR interval corresponding to the predicted value is greater than a predetermined criterion, pulse rates are determined to be disturbed, and after alarm sounds are issued from a music generator 3 to report the disturbance of the pulse rates, calm music is played to promote the recovery of the pulse rates to a stationary condition. As a method of calculating the predicted value, a method of calculating the predicted value of the measurement subsequent or prior to the continuous measurements by obtaining a (k)-order autoregressive model from (k) continuous measurements using an autoregressive factor calculated by Levinson-Durbin prediction process method is used.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a heart rate turbulence detecting apparatus for measuring a heart rate signal of a subject and detecting a heart rate turbulence.

[0002]

2. Description of the Related Art Heretofore, it has been necessary to analyze waveforms by an expert to determine whether or not a detected heart rate signal of a subject has a disturbance in heart rate. Although it is relatively easy to determine the heart rate disturbance from the waveform of the heartbeat signal detected in advance, the occurrence of the disturbance immediately after the disturbance of the heart rate occurs from the sequentially detected heartbeat signal. Was difficult to detect.

[0003]

In recent years, with the improvement of heartbeat signal detection technology, for example, a driver's heartbeat signal is detected from a steering wheel, a moving body is controlled by utilizing a waveform analysis result, and a driving operation is performed. Attempts have been made to improve the safety of the vehicle. However, since there is no means for automatically detecting a heart rate disorder from a heart rate signal, even if the detected heart rate signal has a heart rate disorder, the information cannot be effectively used. SUMMARY OF THE INVENTION It is an object of the present invention to improve the above points and to provide a heart rate turbulence detecting device for automatically detecting a heart rate turbulence from a heart rate signal in real time.

[0004]

SUMMARY OF THE INVENTION Accordingly, the present invention provides a heart rate signal detecting apparatus for sampling a heart rate signal of a subject, calculating and storing heart rate equivalent data from the heart rate signal, and converting the stored heart rate equivalent data to the stored heart rate equivalent data. Heart rate turbulence determining means for calculating a heart rate corresponding data predicted value based on the calculated value, and determining a heart rate turbulence from an error between the heart rate corresponding data predicted value and a heart rate corresponding data corresponding to the heart rate corresponding data predicted value. Was provided.

The heart rate turbulence judging means calculates the (n-1) -th data from the heart rate-equivalent data calculated at the (nk) -th data (where n is an integer of 3 or more and k is an integer of 2 or more). From k heart rate equivalent data up to the obtained heart rate equivalent data to n
A forward prediction error calculating means for calculating a prediction value of the data corresponding to the heart rate, and calculating a forward prediction error which is an error between the actual data corresponding to the nth heart rate and the prediction value of the data corresponding to the nth heart rate; And comparing the forward prediction error with a predetermined first determination value, and, if the forward prediction error is larger than the first determination value, having a forward determination means for determining that the heart rate is disturbed. preferable.

[0006] The heart rate turbulence judging means comprises (nk +
1) (where n is an integer of 3 or more; k is an integer of 2 or more) k number of heart rate equivalent data from the heart rate equivalent data calculated to the nth calculated heart rate equivalent data (n− Calculate the predicted value of the k) th heart rate equivalent data,
The actual (n−k) th heart rate equivalent data and the (n−k) th
k) comparing the backward prediction error with a predetermined second determination value, the backward prediction error calculating means for calculating a backward prediction error which is an error of the prediction value of the data corresponding to the heart rate,
If the backward prediction error is larger than the second determination value, a backward determination unit that determines that the heart rate is disturbed may be provided.

The above k is preferably 15 or 16. In the forward prediction error calculation means or the backward prediction error calculation means, the Levinson-Durbi
The prediction value can be calculated by the n prediction processing method.

[0008]

[Effect] Even if the state of mind and body of the subject is maintained in a steady state, the heart rate does not originally maintain a constant value, but changes periodically with a predetermined width as shown in FIG. Has been repeated. When the state of mind and body becomes an unsteady state for some reason, as shown in FIG. 8B, the heart rate suddenly increases beyond the width of the period change. As the state of mind and body recovers to a steady state, the heart rate gradually decreases and returns to a normal heart rate.

According to the present invention, first, a heartbeat signal of the subject as shown in FIG. 9A is collected by the heartbeat signal detecting device, and as the data corresponding to the heart rate, for example, R in the heartbeat signal shown in FIG. An RR interval, which is a wave interval, is calculated and stored. A predicted value of the RR interval is obtained from the calculated plurality of RR intervals, and a disturbance in the heart rate is determined based on an error between the predicted value and the RR interval corresponding to the predicted value. One way to determine the predicted value is
For example, there is a method in which a k-order autoregressive model is obtained from k continuous measurement values using an autoregression coefficient calculated by a Levinson-Durbin prediction processing method, and a prediction value is calculated from the continuous measurement values.

First, a predicted value of the next measured value is calculated from successive measured values, a forward prediction error which is an error between the predicted value and an actual measured value is obtained, and the forward predicted error is determined by a first predetermined value. If it is larger than the determination value, it can be determined that the heart rate is disturbed. Further, a predicted value of the immediately preceding measured value is calculated from the continuous measured values, a backward prediction error which is an error between the predicted value and the actual measured value is obtained, and the backward prediction error is determined by a predetermined second determination value. If it is larger, it can be determined that the heart rate is disturbed.

In these determinations, a prediction error can be calculated and determined using a microcomputer or the like while detecting the heartbeat signal, and the disturbance of the heart rate can be automatically detected from the heartbeat signal in real time. By appropriately combining the determination method using the forward prediction error and the determination method using the backward prediction error, a desired processing time and determination accuracy can be obtained.

When a large value is used as the value of k, which is the number of predicted values for calculating the prediction error, the prediction error is reduced. However, when the value is excessively increased, statistical stability is lost. , The calculation time increases.
By using 15 or 16 as k, desired determination accuracy can be obtained without losing the immediacy of detection.

[0013]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present invention will be described with reference to examples. FIG. 1 is a diagram showing a first embodiment of the present invention. In the present embodiment, a heart rate signal of the vehicle driver is collected from the steering wheel to determine whether or not the heart rate is disturbed. Also, when a heart rate turbulence is detected, a gentle music is played to prompt a quick recovery to a steady state heart rate.
This device includes a heartbeat signal detection device 1 for detecting a heartbeat signal of a driver from a hand gripping a steering wheel, a control unit 2 and a music generation device 3. The control unit 2 includes a memory 4.

As shown in FIG. 2, the heartbeat signal detecting device 1 includes a positive pole 7, a negative pole 8 installed on a grip of a steering wheel 6, and a detecting circuit 9 connected to each electrode.
And a heartbeat signal as shown in FIG. 9A is collected. In the case of an electrocardiogram signal, electrodes need to be attached to the body, but in this case, since the accurate waveform diagnosis for medical use is not the purpose, the heart rate signal of the driver is measured from the electrode attached to the steering wheel .

The steering 6 is constructed such that the driver's palm naturally comes into contact with the two poles while holding the steering normally. The control unit 2 determines whether or not the heart rate is disturbed. If the heart rate is disturbed, the control unit 2 controls the music generator 3 to play music.

Before explaining the details of the operation, first, Lev
A method of calculating a prediction error using the inson-Durbin prediction processing method will be described. First, the forward prediction for calculating the predicted value of the next measurement value of the continuous measurement value will be described with reference to FIG. In the forward prediction for predicting the value of HR (n) from k measured values from HR (nk) to HR (n-1), the predicted value of HR (n) is represented by the following equation.

(Equation 1) Here, a _j ^(k) is the j-th autoregressive coefficient of the k-th autoregressive model. The auto-regression coefficient a _j ^(k) is Levi
By the nson-Durbin prediction processing method, it is obtained by sequentially calculating a recurrence equation, that is, a j + 1-order autoregressive coefficient from a j-order autoregressive coefficient. Levinson-
The details of the Durbin prediction processing method are described in “User's Digital Signal Processing” by Yoshiro Ehara, Tokyo Denki University Press.

Therefore, the forward prediction error fe ^(k) (n), which is the difference between the actual measured value HR (n) and the predicted value, is expressed by the following equation.

(Equation 2)

The backward prediction for predicting the predicted value of the immediately preceding measurement value from the continuous measurement values will be described with reference to FIG. In the backward prediction for predicting the value of HR (nk) from k values from HR (n) to HR (nk + 1), the predicted value of HR (nk) is represented by the following equation.

(Equation 3)

Therefore, the actual measured value, HR (n−
k) and the backward prediction error be, which is the difference between the prediction value and
^(K) (n) is represented by the following equation.

(Equation 4)

Next, the operation will be described in detail. In this embodiment, 15 is used as the value of k, which is the number of prediction values for calculating the prediction error, in consideration of the detection accuracy and the detection time. First, when the driver grips the steering wheel 6, a heartbeat signal is collected by two electrodes provided on the steering wheel 6 and output to the control unit 2.

The operation of the control unit 2 will be described with reference to the flowchart shown in FIG. In step 101, when the R wave shown in FIG.
Proceed to. At step 102, the address M of the memory 4
The value of the RR interval stored at (m + 1) is
(M) (where m = 1, 2,... 15).

In step 103, an RR interval, which is the interval between the R wave collected in step 1 and the immediately preceding R wave, is calculated and stored in the address M (16). In step 104, the Levinson-Durb is calculated from the 15 RR intervals stored at addresses M (1) to M (15) in the memory.
The auto-regression coefficient a _j ⁽¹⁵⁾ is calculated by the in-prediction processing method.

In step 105, the memory address M
From (2) to the 15 Rs stored at address M (16)
R interval and auto-regression coefficient a _j calculated in step 104
^{From (15 )} , the RR stored in the address M (1)
A backward prediction value corresponding to the interval is obtained, and a backward prediction error be ⁽¹⁵⁾ (16) is calculated by subtracting the prediction value from the RR interval actually stored in the address M (1).
The backward prediction error be ⁽¹⁵⁾ (16) is represented by the following equation.

(Equation 5)

In step 106, the backward prediction error be
⁽¹⁵⁾ Compare (16) with a predetermined determination value A,
If the backward prediction error be ⁽¹⁵⁾ (16) is larger than the determination value A, the process proceeds to step 109. If the backward prediction error be ⁽¹⁵⁾ (16) is smaller than the determination value A,
Proceed to step 107. The judgment value A is a value obtained by subtracting the adjustment value PEAdj from the value obtained by normalizing the judgment reference value ε with the average heart rate, and is expressed by the following equation.

(Equation 6)

In step 107, the memory address M
(1) to 15 Rs stored in the address M (15)
R interval and auto-regression coefficient a _j calculated in step 104
^{From (15 )} , a forward prediction value corresponding to the address M (16) is obtained, and a forward prediction error fe ⁽¹⁵⁾ (1 ⁾ obtained by subtracting the prediction value from the actually measured address M (16).
6) is calculated. Forward prediction error fe ⁽¹⁵⁾ (16)
Is represented by the following equation.

(Equation 7)

In step 108, the forward prediction error fe
⁽¹⁵⁾ Compare (16) with the determination value B, and if the forward prediction error fe ⁽¹⁵⁾ (16) is larger than the determination value B,
Proceed to step 109. Forward prediction error fe
^{(15) If} (16) is smaller than the determination value, the process proceeds to step end and waits until the next R wave is detected. The judgment value B is a value obtained by normalizing the judgment reference value ε with the average heart rate, and is expressed by the following equation.

(Equation 8)

In step 109, the music generator 3 is controlled to generate an alarm sound to notify the driver that the heart rate has been disturbed. Thereafter, gentle music having the effect of relaxing the driver's tension and quickly restoring the heart rate is played for a predetermined time. Steps 101 to 108 of the flowchart shown in FIG. 5 constitute the heart rate turbulence determination means of the present invention. In particular, Steps 104 and 105 constitute a backward prediction error calculation means, and Steps 104 and 107 constitute a forward prediction error calculation means. Step 106 constitutes a backward determination means,
Step 108 constitutes a forward determining means. Further, the judgment value A is a second judgment value of the invention, and the judgment value B is a first judgment value.

With the above operation, the disturbance of the heart rate can be automatically detected in real time from the heartbeat signal. In the present embodiment, the backward prediction error is calculated, the disturbance of the heart rate is determined, and if no disturbance is detected, the forward prediction error is calculated, and the disturbance of the heart rate is again determined. However, the present invention is not limited to this. If only one of the prediction errors is calculated and the determination is made, the determination accuracy is slightly lowered, but the determination time is reduced, and the heart rate disturbance is determined by a lower-cost device. it can.

Further, in this embodiment, when the disturbance of the heart rate is detected, gentle music is played for a predetermined time to prompt the driver to quickly recover the heart rate. Instead, a method of supplying a pleasant scent or supplying oxygen may be used, that is, any means that has an effect of relaxing the driver's tension state may be used.

Next, a second embodiment will be described. this is,
When a disturbance in the heart rate is detected, the control of the car phone is also performed. In this embodiment, the forward prediction process and the backward prediction process are performed in parallel. As shown in FIG. 6, this embodiment includes a heartbeat signal detection device 1, a control unit 10, a music generation device 3, and a car phone 11. The control unit 10 has a memory 12 built therein.

First, as in the first embodiment, when the driver grips the steering wheel 6, heart rate signals are collected by the electrodes of the heart rate signal detecting device 1 provided on the steering wheel 6 and output to the control unit 10. . The operation of the control unit 10 will be described with reference to the flowchart shown in FIG. Steps 201 to 204 are the same as steps 101 to 104 of the flowchart showing the operation of the first embodiment shown in FIG.

In step 205, the backward prediction error be ⁽¹⁵⁾ (1 ⁾ which has been sequentially calculated in the first embodiment.
6) and the forward prediction error fe ⁽¹⁵⁾ (16) are calculated in parallel. In step 206, the backward prediction error be
⁽¹⁵⁾ Compare (16) with a predetermined determination value A. In parallel, the forward prediction error fe ⁽¹⁵⁾ (16)
And the judgment value B are compared. Backward prediction error be
^{(15) When} (16) is larger than the determination value A or when the forward prediction error fe ⁽¹⁵⁾ (16) is larger than the determination value B, the process proceeds to step 207. Backward prediction error be
^{(15) If} (16) is smaller than the determination value A and the forward prediction error fe ⁽¹⁵⁾ (16) is smaller than the determination value B, the process proceeds to step end and waits until the next R wave is detected.

In step 207, the control unit 10 first detects the state of the car phone, and if the car phone is not in operation, releases gentle music from the music generator 3 as in the first embodiment. If the mobile phone is in a calling state, the voice is output to the voice output device of the mobile phone. Also, if the car phone is busy, the call is distracted,
Since the heart rate may be disturbed due to the danger, the mode is temporarily switched to the call holding mode for holding the call.

Steps 201 to 206 of the flow chart shown in FIG. 7 constitute the heart rate disturbance determining means of the present invention. In particular, Step 205 constitutes a backward prediction error calculation unit and a forward prediction error calculation unit, and Step 206 constitutes a backward determination unit and a forward determination unit. By the above operation, the determination using the backward prediction error and the determination using the forward prediction error are performed in parallel, so that the disturbance of the heart rate can be automatically detected from the heartbeat signal more quickly.

[0035]

As described above, the heart rate turbulence detecting apparatus according to the present invention detects a heart rate signal of a subject and, for example, detects Levison-Durbin from the data corresponding to the heart rate.
A prediction value of the heart rate equivalent data is calculated using the prediction processing method, and an error between the predicted value and the heart rate equivalent data corresponding to the predicted value is calculated. By determining the disturbance of the heart rate based on the error, the disturbance of the heart rate can be automatically detected in real time while detecting the heartbeat signal.

The forward prediction processing for calculating the predicted value of the next heart rate equivalent data from the continuous heart rate equivalent data and the backward prediction processing for calculating the predicted value of the immediately preceding heart rate equivalent data are used singly or in combination as appropriate. By doing so, it is possible to obtain a desired processing time and determination accuracy.
Also, by using 15 or 16 as k,
Desirable determination accuracy can be obtained without losing the immediacy of detection.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of a first exemplary embodiment of the present invention.

FIG. 2 is a diagram illustrating a configuration of a signal detection unit.

FIG. 3 is a diagram illustrating a forward prediction process.

FIG. 4 is a diagram illustrating a backward prediction process.

FIG. 5 is a flowchart illustrating a flow of a heart rate disturbance determination process.

FIG. 6 is a block diagram showing a configuration of a second embodiment.

FIG. 7 is a flowchart showing a flow of a heart rate disturbance determination process.

FIG. 8 is a diagram illustrating a state of a heart rate.

FIG. 9 is a diagram illustrating an electrocardiographic signal and an RR interval.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Heart-rate signal detection device 2, 10 Control part 3 Music generator 4, 12 Memory 6 Steering 7 Positive pole 8 Negative pole 9 Detection circuit 11 Car telephone

 ──────────────────────────────────────────────────続 き Continued on the front page F term (reference) 3D037 FA09 FB10 4C017 AA02 AC15 BB13 BC11 CC06 FF30 4C027 AA01 CC06 GG05 GG18 HH06 KK05

Claims (5)

[Claims] A heart rate signal detecting device for obtaining a heart rate signal of a subject; calculating and storing heart rate equivalent data from the heart rate signal; and calculating a heart rate equivalent data prediction value based on the stored heart rate equivalent data. And a heart rate disturbance determining means for determining a heart rate disturbance from an error between the heart rate corresponding data predicted value and a heart rate corresponding data corresponding to the heart rate corresponding data predicted value. Detection device. 2. The method according to claim 1, wherein the heart rate turbulence determining means comprises (nk)
(Where n is an integer of 3 or more, and k is an integer of 2 or more) from the heart rate equivalent data calculated from the heart rate equivalent data calculated to the (n-1) th calculated heart rate equivalent data to n Calculate the predicted value of the data corresponding to the heart rate of the
A forward prediction error calculating means for calculating a forward prediction error which is an error between a predicted value of the nth heart rate equivalent data and a predicted value of the nth heart rate equivalent data; 2. The heart rate turbulence detecting device according to claim 1, further comprising a forward determining unit that determines that the heart rate is erratic when the forward prediction error is larger than the first determination value. 3. The apparatus according to claim 2, wherein the heart rate turbulence determining means comprises (nk +
1) (where n is an integer of 3 or more; k is an integer of 2 or more) k number of heart rate equivalent data from the heart rate equivalent data calculated to the nth calculated heart rate equivalent data (n− Calculate the predicted value of the k) th heart rate equivalent data,
The actual (n−k) th heart rate equivalent data and the (n−k) th
k) a backward prediction error calculating means for calculating a backward prediction error which is an error of a prediction value of the data corresponding to the heart rate, and comparing the backward prediction error with a predetermined second determination value to obtain the backward prediction error. 3. The heart rate turbulence detecting device according to claim 1, further comprising a backward determining unit that determines that the heart rate is turbulent when the error is larger than the second determination value. 4. The apparatus according to claim 2, wherein k is 15 or 16. 5. The forward prediction error calculation means or the backward prediction error calculation means, wherein the Levinson-Durb
5. The heart rate turbulence detecting device according to claim 2, wherein a predicted value is calculated by an in-prediction processing method.