KR100755236B1 - Implementation of bio-information detecting system - Google Patents

Abstract

A bio-information detection system is provided to measure stiffness of the main artery and the peripheral artery by measuring blood pressure using a PTT(Pulse Transit Time) calculated time difference between an R peak point of an ECG(Electro-Cardio Graphy) signal and a characteristic point of a PPG(Photo-Plethysmo Graphy) signal and monitoring the bio signal ECG and the PPG signal inputted from a sensor. In a bio-information detection system for detecting reflection index and blood vessel stiffness index, an ECG and PPG signal acquisition unit acquires an ECG signal and a PPG signal from a bio-signal measurement sensor attached to one side of a user. A calculation unit calculates percentage of the amplitude of a peak point from a base point of a pulse wave and the amplitude of an inflection point in order to obtain the reflection index from the pulse wave signal of the acquired bio signal. A unit calculates the time until a reflection wave arrives after a propagation wave of the pulse wave arrives, and then divides the height of a measurement person by the calculated value, in order to obtain the blood vessel stiffness index from the acquired bio signal.

Description

{Implementation of Bio-information detecting system}

1 is a view for calculating the reflection index and vascular stiffness index in the pulse wave signal according to the present invention

Figure 2 is a view for defining the pulse wave propagation time in accordance with the present invention

3 is a signal form after the PPG original signal and IIR filtering according to the present invention

4 is a signal form after ECG original signal and IIR filtering according to the present invention

5 is a signal form before and after smoothing of a PPG signal according to the present invention.

6 is a signal form before and after smoothing of an ECG signal according to the present invention;

7 is a form of a PPG signal and a differential signal according to the present invention

8 is an ECG signal and a reduction graph according to the present invention.

9 is a signal processing result waveform of the PPG signal according to the present invention

10 is a signal processing result waveform of the ECG signal according to the present invention

명에 따른 시리얼 통신으로 PC에 모니터링된 신호형태Fig. 11

Signal type monitored on PC by serial communication according to command

 * Explanation of symbols for the main parts of the drawings

ΔT: Time until the reflected wave reaches after the traveling wave of the pulse wave signal arrives

a: magnitude of maximum point from base point of pulse wave signal

b: magnitude of inflection point H: height

: 심전도 신호에서 ECG 신호 R정점과 PPG 신호의 특징점 사이의 시간 차이

Is the time difference between the ECG signal R peak and the feature point of the PPG signal in the ECG signal.

: 심전도 신호에서 ECG 신호의 R정점과 압력 맥파 신호의 특징점 사이의 시간 차이

Is the time difference between the R peak of the ECG signal and the characteristic point of the pressure pulse wave signal in the ECG signal.

The present invention is based on the principle that the pulse transit time (PTT) is inversely proportional to the magnitude of blood pressure between the R peak of the ECG (Electro-Cardio Graphy) signal and the characteristic point of the PPG (Photo-Plethysmo Graphy) signal. Blood pressure is measured using PTT, which is calculated by the time difference of, reflex index SI that monitors ECG and PPG signals, which are bio signals from the sensor, and measures the stiffness of the aorta and peripheral artery using the characteristic points of this signal. (Stiffness Index) and the blood vessel stiffness index RI (Reflection Index) for assessing the tension of the peripheral artery relates to a biological information detection system.

In the related art, with the development of electronic component integration technology, low power design, signal processing, and wireless communication technology, the interest in the development of medical engineering and health is increasing, and also the medical sensing technology for health monitoring is being developed. There is a need for methods to measure and interpret non-invasive, non-invasive, non-drug drugs, and technologies to measure health status anytime, anywhere, and further research and development of technologies for measuring health status anytime, anywhere.

Another related prior art discloses a technology for providing a precise mobile blood pressure monitoring device using a PPG signal that provides comfort when measuring blood pressure to a patient in Korean Registered Utility Model Publication No. 20-0380928, but with an ECG signal. No technical content has been disclosed for the system and method for measuring the stiffness index of reflex index SI and peripheral artery stiffness, which can measure the stiffness of aorta and peripheral artery using the R peak and the characteristic point of PPG signal. not.

The technical problem to be achieved by the present invention is to recognize the problems of the prior art as described above, based on the principle that the pulse wave transmission time is inversely proportional to the magnitude of blood pressure, the time difference between the R peak of the ECG signal and the feature point of the PPG signal Blood pressure is measured using PTT, which is calculated by, and biological signals ECG and PPG signals input from the sensor are monitored, and reflex index SI and peripheral which can measure the stiffness of aorta and peripheral artery using the characteristic points of this signal. By implementing a biometric information detection system that measures the vascular stiffness index RI that evaluates the arterial tension, it is possible to measure one's own health status and adapt to the ubiquitous era when implementing the biometric information detection system as a System on a Chip (SoC). Its purpose is to.

Another object of the present invention is to implement the biometric information detection system according to the present invention is more resistant to noise, and the characteristics of the filter or the cut-off frequency can be changed to some extent, considering the individual characteristics in the measuring instrument for medical purposes A filter can be designed, and the number of bits of the coefficient value and the number of bits of the PPG and ECG signals are adjusted to facilitate adjustment of the size of the hardware.

The present invention measures blood pressure using a PTT calculated as the time difference between the R peak of the ECG signal and the feature point of the PPG signal, based on the principle that the pulse wave propagation time is inversely proportional to the magnitude of the blood pressure. ECG and PPG signals, which are input biometric signals, are monitored, and reflex index SI, which measures the stiffness of the aorta and peripheral arteries, and vascular stiffness index RI, which evaluates the tension of the peripheral arteries using the characteristic points of the signals. It relates to a biological information detection system.

Hereinafter, with reference to the accompanying drawings illustrating the configuration and operation of the embodiment of the present invention, the configuration and operation of the present invention shown and described in the drawings will be described as at least one or more embodiments, whereby the present invention described above The technical idea and its core composition and operation are not limited.

With reference to the drawings shown to facilitate understanding of the present invention. FIG. 1 is a diagram illustrating a parameter necessary for calculating a reflection index and a vascular stiffness index in a pulse wave signal which is one of biological signals measured according to the present invention, and FIG. 2 is a diagram for defining a pulse wave propagation time according to the present invention. It is shown. Fig. 3 shows the PPG original signal and the signal after IIR filtering according to the present invention, and Fig. 4 shows the ECG original signal and the signal after IIR filtering according to the present invention. Figure 5 shows the before and after smooth signal of the PPG signal according to the present invention, Figure 6 shows the before and after smooth signal of the ECG signal according to the present invention. 7 shows a PPG signal and a differential signal according to the present invention, and FIG. 8 shows an ECG signal and a reduction graph according to the present invention. 9 is a waveform showing a signal processing result of the PPG signal according to the present invention, Figure 10 is a waveform showing a signal processing result of the ECG signal according to the present invention. Figure 11 shows the signal form monitored on the PC in the serial communication according to the present invention.

The structural means constituting the present invention will be described in a specific embodiment according to the present invention.

EXAMPLES

An embodiment according to the present invention will be described with reference to the drawings. The biometric information detection system according to the present invention measures blood pressure using a PTT calculated as a time difference between the R peak of the ECG signal and the feature point of the PPG signal, based on the principle that the pulse wave propagation time is inversely proportional to the magnitude of the blood pressure. A blood vessel that monitors ECG and PPG signals, which are biological signals input from a sensor attached to one side, and uses the characteristic points of the signals to evaluate the reflex index SI for measuring the stiffness of the aorta and the peripheral artery and the tension of the peripheral artery. There are constituent means for measuring the stiffness index RI.

First, the configuration means for implementing the biometric information detection system according to the present invention will be described in detail. In the present invention, the reflection index is an index indicating the tension of the peripheral artery, and the reflection index is defined as the ratio of the magnitude of the incident wave and the reflected wave separated from the pulse wave. For convenience, the reflection index is determined as a percentage of the magnitude (a) of the maximum point and the magnitude (b) of the inflection point from the base point of the pulse wave signal input from the pulse wave measuring sensor as shown in FIG. 1. This reflection index is given by Equation (1).

(1)

(One)

The magnitude of the reflected wave in the pulse wave signal measured from the pulse wave sensor is related to the blood vessel tension. Therefore, the contraction or expansion of blood vessels has a great influence on the change in the shape of the pulse wave signal. Increasing the tension of the peripheral artery increases the rate of propagation of the reflected wave as the pulse wave propagates. As a result, the difference in the time at which the peaks of the incident wave and the reflected wave arrive at an arbitrary point is reduced, and the reflection index increases by increasing the amplitude of the inflection point relatively. In contrast, when the tension in the peripheral artery decreases, the reflex index decreases.

The vascular stiffness index calculates the time (ΔT) from the arrival of the traveling wave of the pulse wave signal to the arrival of the reflected wave as shown in Fig. 1, and then when the reflected wave reaches the height (H) of the measurer (user). It is defined as a value divided by the time ΔT, and the vascular stiffness index according to the present invention can be obtained by Equation (2).

(2)

(2)

As the stiffness of the aorta increases, the velocity of the pulse wave increases, and thus, the difference in time between the pulse wave signal and the reflected wave time decreases, thereby increasing the vascular stiffness index.

Next, let's take a look at pulse wave propagation time. The pulse wave arrival time is a method of calculating the time difference between the R peak of the ECG and the characteristic point of the pulse wave signal, the method of calculating the time delay using the cross-correlation function of the pulse wave signals measured at the two measurement sites, and the frequency of the two pulse wave signals. It can measure by the method etc. which calculate using a phase difference. Compared to other methods, the present invention adopts a PTT detection method which is easy to implement and can be measured in a short time, and can be implemented as a real-time system because it can be implemented in a circuit, and between the ECG R peak and the pulse wave feature point. We implement a system to calculate the pulse propagation time by calculating the time difference.

는 심전도 신호에서 ECG 신호 R정점과 PPG 신호의 특징점 사이의 시간 차이를 의미하고,

는 심전도 신호에서 ECG 신호의 R정점과 압력 맥파 신호의 특징점 사이의 시간 차이를 나타낸다.PTT measurement principle adopted in the present invention is shown in Figure 2. (A) of FIG. 2 shows an electrocardiogram signal, (b) shows a PPG signal, and (c) shows a pressure pulse wave signal.

Is the time difference between the ECG signal R peak and the PPG signal feature point in the ECG signal,

Represents the time difference between the R peak of the ECG signal and the feature point of the pressure pulse wave signal in the ECG signal.

Next, the configuration of the biometric information detection system according to the present invention will be described. According to the present invention, unnecessary noise is eliminated by passing two types of filters, a smooth filter and an infinite impulse response low pass filter, for an input signal input from a biosignal or pulse wave measuring sensor. And acquire the necessary signal components.

The biosignal or pulse wave measuring sensor employed in accordance with the present invention is attached to one side of the subject using a pulsed light source that generates a predetermined wavelength (light around 940 nm) and intensity at a predetermined period, and is generated from the attached light source. In order to detect light emitted through the blood vessels of the human body, a light sensor capable of detecting light may be attached to a wavelength generated by the light source to detect a signal output from the light sensor.

The IIR low pass filter has a disadvantage in that a convergence time until the signal is stabilized exists compared to a finite impulse response (FIR) filter, but it has an advantage of using less hardware area. The convergence time problem is negligible because of the nature of the system, it takes some time for the signal to stabilize in the PPG sensor and electrode pad. IIR filter obtains transfer function through simulation using Matlab and implements biometric information detection system using VHDL using this transfer function. The cutoff frequency of PPG is 4.8Hz, and the transfer function is shown in Equation (3). The cutoff frequency of the ECG is 34 Hz, and the transfer function is shown in Equation (4).

(3)

(3)

(4)

(4)

The smooth filter takes a pipeline structure to smooth the input signal and process it in real time in order to remove high frequency noise included in the input signal. In order to average the values of the eight input signals input from the sensor, they are stored in eight registers, and after adding them, they are shifted by three bits to the right and divided by eight to obtain an accurate value. 5 and 6, it can be seen that the high frequency noise is removed from the waveform after smoothing.

The number of input signals inputted from the biosignal and the pulse wave measuring sensor may be configured as 1, 4, 8, 16, etc., stored in a register, and added thereto, and then divided by the number of input signals to obtain an average value.

A feature point detection algorithm of the PPG and ECG signals will be described. The characteristics of pulse wave signals, which are biological signals such as ECG and PPG, are sensitive to noise, and may be large or small in amplitude depending on the person, and the period may be fast or slow. The same person can also be measured before or after exercise, depending on the state of health. For this reason, in order to find a feature point in a pulse wave signal, which is a biological signal, an algorithm for obtaining a feature point by using an absolute value of the input signal is difficult to implement, and it is preferable to implement by using relative values of a signal.

The algorithm for the PPG signal uses the difference method as a method of obtaining this since the inflection point becomes direct information about the feature point. 7 shows a simulation waveform in which the difference signal shows a low value while the PPG is increasing and a high value while the PPG is decreasing. This value can be used to obtain information about the inflection point. The moment when the value of the difference signal changes from low to high becomes the inflection point that decreases after the PPG signal increases, and thus it is determined as the maximum value. Likewise, the moment when the value changes from high to low can be determined as the minimum value.

The maximum and minimum points found by the above method are present in two periods. The method of distinguishing peak and reflection starts to find the maximum value at any time, and when the maximum value is found, the current input value is stored in the buffer. In the same way, the maximum value is continuously searched and compared with the input value corresponding to the maximum value to be found next. If the current value is large, it is determined as a peak, and if the current value is small, it is determined as a reflection signal. Similarly, the valley value is similarly found and compared with the input value of the next minimum value. If the current value is large, the valley value is ignored.

An algorithm for finding feature points of the ECG signal will be described. In the case of ECG signal, the value of the R vertex is significantly larger than other values, and it can be confirmed that this value is large enough even considering individual differences and health conditions. This feature is used to find the value of the R vertex. The value of the R vertex at the moment of finding the signal value is stored in the buffer and reduced by a constant slope. If the value is large and the maximum point, it is determined as the R peak value of the ECG signal.

The simulation waveform of FIG. 8 also uses a similar method to PPG. In the case of ECG, the maximum value is generated 3 to 4 in one cycle. In order to find the value of the R peak among the signals, the maximum value is found and the maximum value is determined. The input signal is stored in the buffer at the time of acquisition, and the input value is compared among the instants having 3 to 4 maximum values to determine the largest signal as the value of the R peak of the ECG signal. However, because the R vertices mentioned earlier in this case may momentarily increase inclination, this feature can result in less comparisons and less noise-sensitive systems.

를 계산 한다. 이 값 중 R 정점 값과 밸리 점 값의 차를 이용해서 PTT를 구한다.The biosignal processing part receives the filtered signal and finds the feature point through the feature point algorithm. Calculate the R peak value and period in ECG signals, peak, reflection, valley and period in PPG signals, variables a, b, and SI in RI.

Calculate The PTT is calculated using the difference between the R peak value and the valley point value.

와 PPG의 주기 값을 보여주는 시뮬레이션 파형이다. 도10의 파형은 ECG 신호, R 정점 값 및 주기 값에 대한 것이다.Figure 9 shows feature points in order of peak, reflection, and valley for PPG signal processing, and variables a, b, and SI of RI.

Simulation waveform showing the periodic values of and. The waveforms in FIG. 10 are for ECG signals, R peak values, and period values.

The signals from the filter and the signal processing are serial programs implemented in Visual C ++. The display has a reflex index that can measure the stiffness of the aorta and the peripheral artery and a vascular stiffness index that evaluates the tension of the peripheral artery. Communication means for displaying or transmitting to a PC is provided. In communication, baud rates are available at 9600, 19200, and 38400 bps. 11 is a monitoring waveform of PPG and ECG processed by a smooth filter sent to a PC in serial communication.

The processing algorithm for the pulse wave signal, which is the biosignal, is designed in VHDL and verified by simulation, and then implemented in FPGA to verify real-time operation.

The present invention measures the blood pressure using the PTT calculated as the time difference between the R peak of the ECG signal and the feature point of the PPG signal on the basis of the principle that the pulse wave propagation time is inversely proportional to the magnitude of the blood pressure. The biometric information detection system can be monitored by implementing a biometric information detection system that monitors and measures the stiffness index of the peripheral artery and the reflex index that can measure the stiffness of the aorta and the peripheral artery using the characteristic points of the signal. When implemented as an SoC, it has the effect of measuring its health and adapting to the ubiquitous era anytime and anywhere.

Another effect of the present invention is that when the biometric information detection system according to the present invention is implemented as a digital filter, it is more resistant to noise, and the characteristics of the filter and the cutoff frequency can be changed to some extent. A filter can be designed, and the number of bits of the coefficient value and the number of bits of the PPG and ECG signals are adjusted to facilitate adjustment of the size of the hardware.

Claims (5)

In the biometric information detection system for detecting the reflection index and vascular stiffness index, Means for acquiring ECG and PPG signals, which are biological signals, from a biological signal measuring sensor attached to one side of a user; Means for calculating a percentage of the magnitude of the maximum point and the magnitude of the inflection point from the base point of the pulse wave signal in order to obtain a reflection index from the pulse wave signal among the obtained biological signals; Biometric information detection comprising means for calculating the time from the arrival of the pulse wave to the reflected wave to obtain the vascular stiffness index from the obtained biosignal, and then dividing the height of the measurer by the calculated value. system. The method according to claim 1, And a means for passing a smooth filter and an IIR low pass filter to remove unnecessary noise included in the biosignal input from the biosignal measuring sensor and to acquire only necessary signal components. The method according to claim 1 or 2, And a display unit for displaying a reflection index and a blood vessel stiffness index calculated from the biosignal, and communication means for transmitting data. The method according to claim 1 or 2, And a means for acquiring and storing the values of a plurality of signals input from the sensor in order to accurately measure the reflection index and the vascular stiffness index, adding the stored values, and dividing by the added number to obtain an average value. The method according to claim 1, The ECG and PPG signals, which are bio signals input from the sensor attached to one side of the user, are sensitive to noise and may be large or small in amplitude according to a person, and the period of the signal may also be fast or delayed for accurate measurement. And a means for measuring a reflection index and a blood vessel stiffness index by using a relative value of an input biosignal.

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