JP3196871B2 - Diagnostic device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates, for example about DanSo location examination obtain data of the autonomic nervous system from the interval variations of the pulse train of the heart or the like.

[0002]

BACKGROUND OF THE INVENTION In the 1950's, Hon et al. Revealed that fetal heart rate patterns were associated with fetal hypoxia, and began monitoring fetal heart rate during labor. The heartbeat chart at that time was obtained by incorporating the heart sound of the fetus into, for example, a stethoscope and monitoring it with a microphone, amplifying the signal of the microphone, inputting it to a recorder, and drawing a line on a recording paper moving at a constant speed. Thus, the fetal heart rate chart has been the most important means of providing fetal information to date, but its analysis has the potential for even a skilled physician to make a misdiagnosis.

[0003] On the other hand, in the 1970's, fetal heart rate charts have been used clinically as a means of evaluating the developmental status of a fetus based on information on minute fluctuations in the heart rate baseline. Since then, it has been widely practiced not only during childbirth. Also, heart rate fluctuations are short
Several quantitative clinical indicators have been proposed, categorized as term variability and long term variability.

According to the definition of ACOG (1975), ST
V is said to be a change for each heartbeat of the fetal heart. Also,
LTV has a frequency of 2 to 6 cycles per minute, and normally 6 to 6 cycles.
It is said that the fluctuation is 10 bpm. However, these indices were ambiguous as to what the values obtained clinically reflected. As a result, clinical diagnosis using heart rate variability uses empirical judgments on heart rate variability patterns.

[0005]

In monitoring during delivery, an acute fetal asphyxia is diagnosed based on the pattern, and rapid delivery, particularly fetal adaptation for cesarean section, is performed based on the FHR pattern. This FHR pattern and its physiological significance have been elucidated by various experimental animal fetuses. According to recent studies, infant cerebral palsy or mental retardation may be due to fetal asphyxia during childbirth and subsequent neonatal asphyxia, or events that have occurred in the fetus during pregnancy are already due to some central nervous system abnormalities in the womb. there's a possibility that. Therefore, as during delivery, monitoring of the fetus during pregnancy is important.

For monitoring a fetus during pregnancy, non-stress examination and analysis of image data by ultrasonic tomography have been devised. However, ultrasonic tomography requires time and manpower for the inspection itself, and its determination is also not objective. On the other hand, the non-stress test is simple but can be judged only after 30 weeks of pregnancy.

Japanese Patent Application Laid-Open No. 61-56635 proposes an analysis method for converting a preselected analog signal of an electrocardiograph into a digital signal and then performing a fast Fourier transform. In addition, Clin. Phys. Phy of Enrico Ferrazzi et al.
siol. Meas., 1989, Volume 10, Suppl. B, 57-60.
The page discloses a power spectrum analysis of the heart rate of fetal distress at 26 and 36 weeks gestation. For this analysis, a standard electrocardiograph was used, and the audio signal was recorded on an analog tape recorder for 20 minutes and A / D converted at a sample rate of 1024 Hz.

Further, J. Biomed. En by JS Brown et al.
g., 1992, Vol. 14, pp. 263-267, discloses a technique for identifying respiratory arrhythmias in the uterus. For this analysis, an ultrasonic Doppler was used, and a low-order autocorrelation method assuming stationarity was used for the spectral analysis. It is recorded on an analog tape recorder for 20 minutes and 1024
A / D conversion is performed at a sample rate of Hertz.

[0009] J. Kalin et al., Pediatric Research, 19
In 1993, Vol. 34, No. 2, pp. 134-138, an evaluation of autonomic state of asphyxia by spectral analysis of fetal asphyxia heart rate variability during about 24 pregnancies and 40 weeks of work is disclosed. In this evaluation, a chest electrocardiogram signal was recorded on a cassette type data recorder for 5 minutes, A / D converted at a sampling rate of 300 Hz, and an algorithm for detecting the asphyxia heart rate was used. Further, a series of RR intervals are input to an algorithm for forming an asphyxial heart rate at equal intervals after passing through an automatic correction procedure that holds absolute time, and are simultaneously passed through a low-pass filter, and are equally spaced at 4 Hz. A series of asphyxia heart rates calculated by are calculated. Next, this fluctuating asphyxia heart rate time sequence is subjected to a fast Fourier transform (FFT),
The power spectrum up to a frequency of 2 Hz is calculated.

[0010] All of these analysis methods have poor accuracy. That is, even if the fluctuation of heart rate, that is, fluctuation is analyzed, an input signal always uses an A / D-converted level signal at a predetermined sampling rate. Is used. Therefore, F which has been frequently used in the medical field is conventionally used.
In the FT, it is difficult in principle to derive a clear frequency component from the heart rate variability because the resolution of the spectrum is low due to a constraint existing in the method itself.

In view of the above circumstances, the present invention directly measures not the heart rate but the heartbeat, that is, the RR interval, and then performs a moving average to remove noise and high-frequency components. It is an object of the present invention to provide a highly accurate diagnosis method using a linear prediction method based on an autoregressive model of order based on periodicity, since the spectrum analysis can be performed even with a small number of data.

[0012]

Diagnostic apparatus of the present invention, in order to solve the problems] includes means for obtaining a biological signal from a living body, the time of the maximum point of the biological signal by sequentially detecting, form a time T ₀ through T _n, Where n is a positive integer, and peak detecting means, and counter means for sequentially dividing the time between a certain time and the next time by a predetermined basic time to form heartbeat intervals P _{1 to} P _n. And a predicting means for performing spectrum analysis on the intervals between the heartbeats by a linear prediction method using a 24th order autoregressive model to obtain fluctuations in the heartbeat intervals.

[0013] The peak detecting means includes three sample-and-hold circuits to which the biological signal is input and to which a three-phase hold enable signal is sequentially input. Three comparators for comparing outputs, three AND gates for performing an AND operation on every two outputs of the comparators and outputting three AND outputs, and any one of these AND gates Means for storing a time corresponding to said enable signal when the output goes high.

The peak detecting means includes an A / D converter to which the biological signal is input, a three-row shift register circuit to which the output of the A / D converter is input, and, among these shift register circuits, A first comparator for comparing the outputs of the first and second columns, a second comparator for comparing the outputs of the second and third columns, an AND gate for ANDing the outputs of these comparators, and an output of the AND gate Means for storing the time when it becomes H.

[0015] The predicting means may be configured to execute the spectrum analysis before
Data for removing the high frequency component of the heartbeat interval P while standing
A digital low-pass filter is provided.

[0016] The predicting means may be arranged to perform the above-mentioned spectrum analysis.
Standing, for spacing P ₁ to P _n of the heart, the time distribution
The interval between assist heartbeats from the front and back of the row to P _1-m and P _{n + m}
Then, a moving average is calculated for 2m + 1 minutes.

[0017]

FIG. 1 is a schematic diagram showing an embodiment of a diagnostic apparatus according to the present invention. The diagnostic apparatus includes a microphone, that is, an ultrasonic transducer 11 for collecting a biological signal from a heartbeat of a living body, for example, the heart wall of a pregnant fetus. The ultrasonic transducer 11 applies an ultrasonic wave modulated at 1.15 MHz to the fetal heart in the uterus, and the reflected wave changes with the heartbeat due to the Doppler effect. Collected. In addition, the heartbeat of an adult is collected as a biological analog signal from an electrode of an electrocardiogram by a bipolar lead method. This biological signal may be collected by a blood pressure wave system, a pulse oximeter, or the like. The bioanalog signal has a period between one heartbeat and the next heartbeat, ie, R
The signal is input to the peak detection circuit 12 in order to sequentially determine the -R interval.

The peak detection circuit 12 first detects times T _{0 to} T _n of the biological signal, that is, the maximum point of the R wave, and then determines a period between a certain time and the next time in advance. successively dividing the basic clock which is to form the spacing P ₁ to P _n of the heart. Here, n is a positive integer. This basic clock is sent from the clock circuit 13.

That is, the predetermined basic clock is represented by T
_{Assuming CLK} , the heartbeat interval _Pn is as follows. _{P n = (T n -T n} -1) / T CLK where n is a positive integer. Here, the conventional heart rate fluctuation and the heart rate fluctuation or fluctuation according to the present invention are fundamentally different. That is, the heart rate is, for example, the number of beats of the heart beat in one minute, while the time interval of the heart beat is a time period between one beat (beat) and the next beat, that is, a time function.

Therefore, the interval between heartbeats is determined by, for example, an 8-bit width counter 14 to which a clock of 1 kHz is input.
After that, each time the time of the maximum point is detected, it is sequentially stored in, for example, an n-bit RAM 15 having an 8-bit width. The contents of these n-bit RAMs 15 are input to a microcomputer (CPU) or a digital signal processor (DSP) 16, and the spectrum is analyzed by, for example, a 24th-order linear prediction method using an autoregressive model. Further, the n-bit RAM 15 may be replaced with an n-column shift register.

FIG. 2 shows a predetermined basic clock (for example, 1 k
Hz) ultrasonic transducer 1 sampled sequentially at
FIG. 3 is a schematic diagram of one embodiment of a peak detection circuit 12 that compares each of three consecutive biological signals from one. The peak detection circuit 12 detects when the first sampled first biological signal is lower than the second sampled second biological signal and the second biological signal is higher than the next sampled third biological signal.
The time when the second biological signal is sampled is stored.

Accordingly, the peak detection circuit 12 compares three sample-and-hold circuits 21 to 23 to which a biological signal from the ultrasonic transducer 11 can be inputted with the outputs of every two of the three hold circuits 21 to 23. And three comparators 24-26. These sample and hold circuits 21 to 23 include a 3-bit ring counter 27
Are sequentially input. The ring counter 27 has three outputs to which a basic clock of, for example, 1 kHz is input and only one of which becomes H, and the carry output of which is provided to a clock terminal or a clock enable terminal of an 8-bit binary counter 28, for example. Is entered.

Therefore, the three sample and hold circuits 2
1 to 23, each time the basic clock is input to the ring counter 27, one of them becomes a state in which a biological signal can be sampled, and the other two become a state in which the first and second biological signals are held. After a lapse of time, the sampled data, that is, the third biological signal is stabilized. at the same time,
These counters 27 and 28 hold counts related to the time when the biological signal was sampled.

Thus, three consecutively sampled biological signals are compared with the second with the first or third biological signal. Therefore, two comparators are sufficient, but in this embodiment, for example, three comparators are necessary because the hold circuit of the first biological signal moves in order. First, the comparator 2
The output of 4 is input to an AND gate 31 and an AND gate 32 via an inverter (shown by ○). Next, the output of the comparator 25 is supplied to the AND gate 32 through an inverter.
Is input to the AND gate 33. Also, the comparator 2
The output of 6 is input to the AND gate 33 and the AND gate 31 via the inverter.

When the output of any of these AND gates 31 to 33 becomes H, that is, when the maximum biological signal is detected, the time corresponding to the associated enable signal, that is, the count is, for example, 10 bits wide. Stored in the 4 kB RAM 15. Thereafter, the address of the RAM 15 is incremented, and the ring counter 27 and the binary counter 28 are reset to prepare for storage of the next RR interval.
In this case, the time is not directly stored, but the interval between the maximum points of the biological signal, that is, the RR interval is directly stored.

Next, as shown in FIG. 3, a peak detection circuit according to another embodiment includes an A / D converter 41 to which the biological signal is input at a sampling rate of, for example, 1 kHz, and an A / D converter. The output of 41 is input to three columns of shift register circuits 42 to 44, and among these shift register circuits, the first comparator 45 for comparing the output of one column and two columns is compared with the output of two columns and three columns. A second comparator 46, an AND gate 47 for ANDing the outputs of these comparators, a binary counter 14 to which a basic clock of 1 kHz is input, and a RAM 15 in which the value of the binary counter 14 can be sequentially stored. Prepare. When the output of the AND gate 47 becomes H, the contents of the binary counter 14 are stored in the RAM 15 and thereafter the RA
The address of M15 is incremented, and the binary counter 4
8 is reset.

That is, the A / D converter 41 converts an analog biological signal into, for example, an 8-bit digital signal in order to detect the maximum time of the biological signal unlike the conventional sampling of the waveform of the biological signal. This digital signal is input to a three-column 8-bit width shift register, and digital biosignals in three stages before and after are compared. Further, a counter for measuring the RR interval is provided in synchronization with the sampling of the biological signal, and when the digital biological signal before and after is lower than that in the middle, the content of the counter is stored in a computer system or a digital signal processor (DSP). And then reset the counter to start measuring the next RR interval. As described above, the RR interval data between the beats of the biological signal is sequentially stored for 300 times in the case of a fetus, for example.

These 30 stored in the RAM in the DSP
Zero RR interval data is one before and after one data.
One piece of data is moving averaged to obtain 278 pieces of data from which noise and high frequency components have been removed. These 278 pieces of data are subjected to spectral analysis using a linear prediction method based on a 24th-order autoregressive model to obtain a power spectrum distribution diagram of the fluctuation of the RR interval data shown in FIG. FIG.
Indicates the power spectrum density on the vertical axis and the deviation value of the fluctuation for each beat on the horizontal axis. In the case of a fetus, a peak appears in the low-frequency component. Has been determined. These 278 data and decisions are based on the following clinical case.

On the assumption that the fetal heart rate variability is non-stationary linear, a non-parametric method using a repeated test was used to verify the fetal heart rate variability. In the physiologically stable state, the adult showed a stationary state, while the fetus showed a periodicity every 24 heartbeats. In addition, the straight line portion in the continuous graph was considered as a physiological steady state, and the average length of the physiological steady interval was produced for the 8308 heartbeats of 10 normal fetuses from 18 weeks to 39 weeks of gestation. As a result, the average length of the section where the fetus is physiologically considered to be in a steady state is 237.5.
It was a heartbeat. Therefore, the linear prediction method based on the 24th-order autoregressive model is determined from the periodicity of every 24 heartbeats in the fetus, and 278 data are the average stationary section length 23 of the fetus.
Determined based on 7.5 heartbeats.

In adults, spectral analysis of a linear prediction method using an autoregressive model of heart rate variability is used clinically,
A low-frequency component of 0.1 c / b (cycle / beat) or less;
There are two peaks in the mid-range component of 0.2-0.3 c / b. It has been experimentally shown that these fluctuations closely reflect the activities of the sympathetic nervous system and parasympathetic nervous system, respectively.

Assuming that fetal asphyxia in the second trimester is fetal hypoxemia, and applying the spectral analysis according to the present invention, the high peak in the fetus indicates parasympathetic activity,
Involvement of respiratory factors as in adults. In addition, the lower band peak mainly showed the activity of the sympathetic nerve and partly the parasympathetic nerve, and animal experiments showed that the lower band peak decreased in synchronization with the blood pH. These series of results were obtained from the relationship between fetal blood oxygen partial pressure obtained by umbilical vein puncture and low frequency area.

When an electrocardiogram is used, the RR interval may be automatically detected by a template matching method. Alternatively, after removing the low-frequency component of 25 heartbeats or less, the noise may be visually removed on the display screen, and then only the steady state section may be extracted.

[0033]

As described in the foregoing, according to the DanSo location diagnosis of the present invention, by measuring the interval of heartbeats directly after moving average, using a linear prediction method by 2 fourth-order autoregressive model , The power spectrum distribution of the fluctuation of the heartbeat interval is obtained with less data than FFT. Therefore, the fetal asphyxia around 25 to 26 weeks of pregnancy, which has been difficult to measure conventionally, can be determined with high accuracy from the low frequency components of the power spectrum distribution of this fluctuation.

[Brief description of the drawings]

FIG. 1 is a schematic diagram showing one embodiment of a diagnostic device according to the present invention.

FIG. 2 is a schematic circuit diagram showing one embodiment of a peak detection circuit according to the present invention.

FIG. 3 is a schematic circuit diagram showing another embodiment of the peak detection circuit according to the present invention.

FIG. 4 is a power spectrum distribution diagram of fluctuation of RR interval data.

[Explanation of symbols]

 Reference Signs List 11 sensor (microphone) 12 peak detection circuit 13 clock circuit 14 counter 15 RAM 16 DSP or CPU

Continuation of the front page (72) Inventor Terumi Matsubara 2-2-1 Dojo, Urawa-shi, Saitama Atom Co., Ltd. Urawa Plant (56) References JP-A-7-88094 (JP, A) JP-A-6 −105818 (JP, A) Hiroyoshi Takatsuji et al., Development of a system for analyzing fluctuations in heart rate, Report of the Physiological Technology Workshop, published by the National Institute for Physiological Sciences (September 1991), No. 13, No. 59-62. Page (58) Field surveyed (Int.Cl. ⁷ , DB name) A61B 5/0402-5/0472 JICST file (JOIS)

Claims (7)

(57) [Claims] 1. A means for obtaining a biological signal from the raw body, the time of the maximum point of the biological signal by sequentially detecting the time T ₀
To T _n , where n is a positive integer, and the time between a certain time and the next time is sequentially divided by a predetermined basic time to obtain a heartbeat interval P ₁ to A diagnostic apparatus comprising : counter means for forming P _n ; and predicting means for performing a spectrum analysis on the intervals between the heartbeats by a linear prediction method using a 24th-order autoregressive model to obtain fluctuations in the heartbeat intervals. 2. The sample detecting circuit according to claim 2, wherein the biological signal is input to each of the peak detecting means, and a three-phase hold enable signal is sequentially input to the peak detecting means. Three comparators for comparing the outputs of each of the three comparators, of these comparators, ANDing the outputs of every two of them, and three AND gates each outputting three AND outputs, and any of these AND gates Kano output diagnostic apparatus according to claim 1, further comprising a means for time are stored corresponding to the enable signal related when they become H. 3. An A / D converter to which the biological signal is input, a three-row shift register circuit to which the output of the A / D converter is input, The first of which compares the output of one and two columns
A second comparator that compares the output of the comparator with two and three columns;
An AND gate for ANDing the outputs of the comparators, diagnostic apparatus according to claim 1, wherein the time and means to be stored when the output of the AND gate becomes H. 4. The prediction means according to claim 1 , wherein
Prior to removing the high frequency component of the heartbeat interval P
The diagnosis according to claim 1, further comprising a digital low-pass filter.
apparatus. 5. The prediction means according to claim 1 , wherein
Prior, the intervals P ₁ to P _n of the heart, the time
Interval between assist heartbeats from before and after the array to P _1-m and P _{n + m}
A moving average of 2m + 1 minutes.
The diagnostic device according to claim 1. Wherein said predicting means includes a RAM for a predetermined number storing interval data of the heartbeat, diagnostic apparatus according to claim 1, further comprising a CPU for determining the normal distribution of the fluctuation of the interval data from the contents of the RAM . Wherein said predicting means includes a RAM for a predetermined number storing interval data of the heartbeat, diagnostic apparatus according to claim 1, further comprising a DSP to determine the normal distribution of the fluctuation of the interval data from the contents of the RAM .