WO2020210982A1

WO2020210982A1 - Bcg-signal-based multi-sensor blood pressure monitoring apparatus and method

Info

Publication number: WO2020210982A1
Application number: PCT/CN2019/082874
Authority: WO
Inventors: 卢坤涛; 刘众; 乐勇
Original assignee: 深圳市格兰莫尔科技有限公司; 卢坤涛; 刘众; 乐勇
Priority date: 2019-04-16
Filing date: 2019-04-16
Publication date: 2020-10-22

Abstract

A BCG-signal-based multi-sensor blood pressure monitoring apparatus, comprising: a BCG signal collection module provided with a plurality of sensing points and used for collecting BCG signals of a plurality of parts of a body, wherein the BCG signal collection module comprises sensors (11, 12) distributed at a plurality of points; a signal processing module for filtering and amplifying the BCG signals, determining the validity of the BCG signals and extracting BCG signal characteristics, wherein the signal processing module comprises a signal filtering and amplifying unit (21) and a BCG signal characteristic extraction module (22); and a blood pressure calculation module (23) for calculating a blood pressure value of a user. The blood pressure monitoring apparatus has the advantages of a high blood pressure measurement accuracy, the capability to continuously monitor a blood pressure, non-contact operation and low monitoring costs, and is more applicable to real-time monitoring of heart functions in daily life.

Description

Multi-sensor blood pressure detection device and method based on BCG signal

Technical field

The invention belongs to the technical field of blood pressure monitoring, and specifically relates to a multi-sensor blood pressure detection device and method based on BCG signals.

Background technique

Blood pressure is one of the important physiological indicators of the human body and an important physiological parameter reflecting cardiovascular function, so it has become an important indicator of clinical disease diagnosis.

At present, there are mainly four commonly used non-invasive blood pressure detection methods: Offset sound method, oscillometric method, constant volume method and pulse wave method. Offset sound method is determined by identifying the over-flow sound and the corresponding pressure point in the process of obstructing arterial blood flow, but its accuracy is greatly affected by human factors, including subjective sensation and coordination of the human body, cuff position, and cuff The size, etc., and the mean arterial pressure cannot be directly measured. The most important thing is that continuous monitoring cannot be achieved. The oscillometric method is to detect the gas oscillating wave generated by the pulsation of the blood vessel wall in the cuff, and directly judge the fluctuation of the pressure in the cuff to determine the blood pressure of the body. At present, the widely used oscillometric criterion is given by statistical methods through a large number of population experiments, so it is easy to cause individual measurement differences, and continuous monitoring cannot be achieved. The principle of the constant volume method is: when the arterial blood vessel is under load due to external force, the applied pressure is equal to the arterial pressure. At this time, the diameter of the blood vessel does not change with the fluctuation of the blood vessel, and the blood vessel is in a constant volume state. This method measures the discrete type of systolic blood pressure. The pulse wave method is proposed based on the positive correlation between the pulse wave propagation rate along the artery and the arterial blood pressure. By measuring the pulse wave velocity (PWV), the arterial blood pressure value is indirectly calculated. It is necessary to measure the electrocardiogram (ECG) and the photoplethysmogram (PPG). ), although continuous monitoring can be achieved, but electrodes need to be attached, which is inconvenient to use.

technical problem

In view of the shortcomings in the prior art, the present invention provides a multi-sensor blood pressure monitoring device based on BCG (ballistocardiography) signals to solve the problem that the current commonly used non-invasive blood pressure detection methods and devices are difficult to continuously monitor blood pressure. The problem of low detection accuracy.

Technical solutions

In order to achieve the above objectives, the present invention adopts the following technical solutions:

A multi-sensor blood pressure detection device based on BCG signals, including:

A BCG signal acquisition module with multiple sensing points, used to acquire BCG signals of multiple parts of the body, the BCG signal acquisition module including sensors arranged at multiple points;

A signal processing module for filtering and amplifying the BCG signal, judging the validity of the BCG signal, and performing feature extraction of the BCG signal, the signal processing module including a signal filtering and amplifying unit and a BCG signal feature extraction module; and

The blood pressure calculation module is used to calculate the user's blood pressure value.

Further, the sensors are respectively arranged at different parts in a parallel body direction or a perpendicular body direction. Further, the sensor is a piezoelectric film sensor, a piezoelectric ceramic sensor, a piezoelectric cable sensor, an acceleration sensor, a gyroscope sensor or an optical fiber sensor.

Further, the judging the validity of the BCG signal includes: when the signal strength is greater than the threshold value 1, it is considered that the user is in a physical state; when the signal strength is less than the threshold value 2, it is considered that there is no one in the monitoring area or the signal is weak. In these two cases The BCG signal is judged to be invalid; only when the signal strength is between threshold 2 and threshold 1, the collected BCG signal is judged to be valid.

Further, the BCG signal feature extraction of each sensing point includes: H, I, J, K wave identification and waveform feature extraction, and the waveform feature includes HI interval, IJ interval, HIJ pulse width, IJ Amplitude, JJ interval, and pulse wave transit time PPT between sensing points.

Further, the blood pressure calculation unit calculating the user's blood pressure value according to the characteristics of the BCG signal includes: obtaining the distance matrix L between each sensing point, and the respective HI, IJ, HIJ pulse width interval matrix THI, TIJ of each sensing point , THIJ, the IJ amplitude matrix AIJ of each sensing point, the JJ interval matrix TJJ of each sensing point and the pulse wave transit time matrix TPPT between each sensing point, to calculate the blood pressure value.

The embodiment of the present invention also provides a multi-sensor blood pressure monitoring method based on BCG signals, which includes the following steps:

Multi-sensing point BCG signal acquisition unit collects BCG signals of multiple parts of the body;

The signal processing unit filters and amplifies the BCG signal, and judges the validity of the BCG signal;

If the signal is judged to be valid, perform BCG signal feature extraction; and

According to the characteristics of the BCG signal, enter the blood pressure calculation unit to measure the user's blood pressure value.

Another object of the embodiments of the present invention is to provide a mattress with the blood pressure detection device of the present invention, wherein the components of the blood pressure detection device are built in the mattress. Furthermore, in the mattress of the present invention, the sensors are arranged in a strip or dot matrix arrangement.

Beneficial effect

Compared with the prior art, the present invention has the following beneficial effects: the multi-sensor blood pressure monitoring method based on BCG signals overcomes the defects of weak BCG signals and unstable signal collection caused by external interference. The signal is filtered and amplified and the signal feature is extracted, which significantly improves the accuracy of blood pressure measurement, and has the advantages of continuous blood pressure monitoring, non-contact operation, and low monitoring cost. It is more suitable for real-time heart monitoring in daily life Features.

Description of the drawings

Fig. 1 is a time-domain waveform diagram of a typical BCG signal provided by the prior art;

2 is a flowchart of a multi-sensor blood pressure monitoring method based on BCG signals according to an embodiment of the present invention;

3 is a schematic structural diagram of a mattress with a blood pressure detection device provided by an embodiment of the present invention; and

Fig. 4 is a schematic structural diagram of another mattress with a blood pressure detection device provided by an embodiment of the present invention.

Embodiments of the invention

In order to make the technical problems, technical solutions, and beneficial effects to be solved by the present invention clearer, the following further describes the present invention in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention.

In the following description, the use of suffixes such as "module", "part" or "unit" used to indicate elements is only for the description of the present invention and is not used for special limitation. "Module" and "unit" can be mixed To use.

The embodiment of the present invention provides a multi-sensor blood pressure monitoring method based on BCG signals, the method includes the following steps:

(1) The multi-sensing point BCG signal acquisition unit collects BCG signals of various parts of the body;

(2) The signal processing unit filters and amplifies the BCG signal, and analyzes the steady state of the body, that is, judges the validity of the BCG signal;

(3) If the signal is judged to be valid, then perform BCG signal feature extraction; and

(4) According to the characteristics of the BCG signal, enter the blood pressure calculation unit to measure the user's blood pressure value.

BCG is a non-invasive graphical interface that accurately describes the impact of heart contraction, blood ejection, and blood flow decelerating through large blood vessels to cause physical activity. Every time the heart beats, blood will be ejected from the heart into the blood vessels, and during this ejection process, an extremely small force is generated on the human body. After the extremely weak reaction force is obtained by the BCG recorder, the analysis and calculation can be obtained. A series of indicators of human heart function.

Specifically, in step (1), the multi-sensing point BCG signal acquisition unit includes sensors arranged in different parts of the body parallel to or perpendicular to the body, and the signals are connected to the signal processing unit. The placement parts include, for example, the heart area, the head area, the back area, and the leg area in order to obtain more body information.

Further, the sensor is a piezoelectric film PVDF sensor, a piezoelectric cable sensor, an acceleration sensor, a gyroscope sensor or an optical fiber sensor.

In step (2), the signal processing unit amplifies the collected weak BCG signal, and filters out the interference signal of the environment, so as to extract the strength of the BCG signal, and then analyze the steady state of the body, that is, judge the collected signal Validity: When the signal strength is greater than threshold 1, the user is considered to be in a physical state; when the signal strength is less than threshold 2, it is considered that there is no one in the monitoring area or the signal is weak. In both cases, the BCG signal is judged to be invalid; When the signal strength is between threshold 2 and threshold 1, it is determined that the collected BCG signal is valid. Then, the next step of BCG signal feature extraction is performed on the effective signal, thereby improving the accuracy of blood pressure measurement.

Specifically, step (3) performs feature extraction on the effective BCG signal collected in step (2). The feature extraction of the BCG signal at each sensing point includes the identification of H, I, J, and K waves and the extraction of waveform features. The characteristics of the waveform include: HI interval, IJ interval, HIJ pulse width, IJ amplitude, JJ interval, and pulse wave transit time PPT between sensing points.

As shown in Figure 1, the figure shows the time-domain waveform of a typical BCG signal. The amplitude of the waveform represents the heart pumping intensity and blood flow acceleration of the subject, and the width of the waveform represents the diastolic and systolic period. Duration, typical BCG signals include H, I, J, K, L, M, and N waves. Among them, it is generally believed that the systolic period of the heart occurs in the I, J, and K waves, and the L, M, and N waves are generated during the diastole. , J wave is the maximum amplitude point in each cycle of the BCG signal. Please refer to Figure 1. For the identification of the BCG signal H, I, J, and K waves of a single sensing point, the specific identification method is: by detecting the peak and valley values of the signal amplified by the BCG filter, find the point with the highest peak And the distance between the highest points to determine whether it is a J wave. When the J wave is calibrated, the H, I, and K waves can be calibrated according to the peak and valley values detected nearby. The adjacent maximum point of the J wave is The two adjacent minimum points of H wave and J wave are I wave and K wave.

Further, the calculation method of the pulse wave transit time PPT between the sensing points is: After obtaining the J wave of each sensing point, obtain the time difference of the J wave between the sensing points (less than one JJ interval), which is Pulse wave transit time PPT between sensing points.

Specifically, in step (4), the blood pressure calculation unit calculates the value of blood pressure based on the BCG signal characteristic value obtained in step (3), that is, BP=F(L, THI, TIJ, THIJ, AIJ, TJJ, TPPT) , Where the specific calculation formula of the F function is not expanded here, L is the distance matrix between each sensing point, THI, TIJ, THIJ are the respective HI, IJ, and HIJ pulse width interval matrix of each sensing point, AIJ is The IJ amplitude matrix of each sensing point, TJJ is the JJ interval matrix of each sensing point, and TPPT is the pulse wave transit time matrix between each sensing point.

In specific applications, the multi-sensing point BCG signal acquisition unit, signal processing unit and blood pressure calculation unit are all implanted inside the mattress. When the subject is asleep, the heart function can be monitored in real time, and more accurate and comprehensive data can be obtained if they persist in long-term use. This non-contact blood pressure measurement method has a better user experience and is easy to promote and use.

Fig. 2 is a flowchart of a multi-sensor blood pressure monitoring method based on BCG signals according to an embodiment of the present invention, which specifically includes the following steps:

S1. Obtain the BCG signal of the heart area and leg area through sensors installed in the human heart area and leg area;

S2. The signal processing module performs band-pass filtering and amplification on the collected original BCG signal, and the band-pass frequency band is 0.8Hz~10Hz;

S3. Perform amplitude monitoring and data validity judgment on the 2s data window of the processed BCG signal; when the signal strength is greater than threshold 1, it is considered that the user is in a physical state at this time, and when the signal strength is less than threshold 2, it is considered The monitoring area is unmanned or the signal is weak. In both cases, the BCG signal is judged to be invalid; the threshold 1 is greater than the threshold 2, so the BCG signal is judged to be valid only when the signal strength is between the threshold 2 and the threshold 1.

S4. Collect the 10s data window of the valid BCG signal, detect the peak and valley values, and calibrate the H, I, J, and K waves of each cycle of the BCG signal in the window;

S5. Calculate the HI interval, IJ interval, HIJ pulse width, IJ amplitude, and JJ interval of each cycle of the BCG signal collected in S4, and calculate the average value: T _HI , T _IJ , T _HIJ , A _IJ , T _JJ ;

S6. Calculate the J wave time difference corresponding to all cycles of the BCG signal of the head and legs collected in S4, and calculate the average value T _PPT ; and

S7. Calculate the blood pressure value according to the feature quantities of the BCG signal extracted by S5 and S6.

The embodiment of the present invention also provides a blood pressure detection device, which adopts the above-mentioned multi-sensor blood pressure monitoring method. The device includes a signal acquisition module, a signal processing module, and a blood pressure calculation module. The signal acquisition module includes regional multi-point sensors and signals. The processing module includes a signal filtering and amplifying unit and a BCG signal feature extraction module.

FIG. 3 is a mattress with a blood pressure detection device provided by an embodiment of the present invention. As shown in FIG. 3, the mattress 4 includes a belt-shaped sensor 11 in the heart area, a belt-shaped sensor 12 in the leg area, and a signal The filtering and amplifying unit 21, the BCG signal feature extraction module 22, the blood pressure calculation module 23 and the wireless data transmission module 3, and these sensors and modules are all arranged inside the mattress. Among them, the strip sensors 11 and 12 are used to collect the BCG signals of the heart and the legs, respectively. The strip sensors can be optical fiber sensors, piezoelectric film sensors or piezoelectric cable sensors, and then transmit the signals to the signal filtering and amplifying unit 21 for filtering. Amplify, and extract the feature quantity of the signal through the BCG signal feature extraction module 22, and finally enter the blood pressure calculation module 23 to measure the blood pressure value. The measurement result can also be displayed on the terminal device through the wireless data transmission module 3.

Figure 4 shows another mattress with a blood pressure detection device provided by an embodiment of the present invention. It can be seen from the figure that the mattress 4 includes dot matrix sensors 111, 112 and 113 in the heart area and Dot matrix sensors 121, 122, and 123, dot matrix sensors 131, 132, and 133 in the leg area, signal filtering and amplifying unit 21, BCG signal feature extraction module 22, blood pressure calculation module 23, and wireless data transmission module 3, and these sensors and The modules are all set inside the mattress. The dot matrix sensor can be piezoelectric film, piezoelectric ceramic, acceleration sensor or gyroscope sensor. The working principle of the mattress is the same as the above embodiment.

In terms of sensor settings, in addition to the above-mentioned belt-shaped settings and dot matrix settings, other settings can also be adopted according to the characteristics of the human body.

The above-mentioned mattress may be an ordinary mattress, for example, a sponge cushion is provided on the upper surface, and a device for adjusting the hardness is arranged on the lower surface. By digging a hole in the foam pad to embed the sensor, it is advisable to receive the sensing signal without causing discomfort to the mattress user; the signal processing module and the blood pressure calculation module are also set inside the mattress to avoid use The thickness of the person’s weight interference is buried in the mattress. The above settings should be settings well known to those skilled in the art.

It should be understood that in terms of the number of components and parts, if the number is not clearly defined, it means that both singular and plural components and parts can be used, and the protection scope does not limit the number of parts.

The above descriptions are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modification, equivalent replacement and improvement made within the spirit and principle of the present invention shall be included in the protection of the present invention. Within range.

Claims

A multi-sensor blood pressure detection device based on BCG signals, including:

A BCG signal acquisition module with multiple sensing points, used to acquire BCG signals of multiple parts of the body, the BCG signal acquisition module including sensors arranged at multiple points;

A signal processing module for filtering and amplifying the BCG signal, judging the validity of the BCG signal, and performing feature extraction of the BCG signal, the signal processing module including a signal filtering and amplifying unit and a BCG signal feature extraction module; and

The blood pressure calculation module is used to calculate the user's blood pressure value.
The multi-sensor blood pressure detection device according to claim 1, wherein the sensors are respectively arranged in different parts parallel to the body direction or perpendicular to the body direction.
The multi-sensor blood pressure detection device according to claim 2, wherein the sensor is a piezoelectric film sensor, a piezoelectric ceramic sensor, a piezoelectric cable sensor, an acceleration sensor, a gyroscope sensor, or an optical fiber sensor.
The multi-sensor blood pressure detection device according to claim 1, wherein the BCG signal feature extraction includes: H, I, J, K wave identification and waveform feature extraction, and the waveform feature includes the HI interval , IJ interval, HIJ pulse width, IJ amplitude, JJ interval and pulse wave transit time PPT between sensing points.
The multi-sensor blood pressure detection device of claim 1, wherein the blood pressure calculation unit measuring the user's blood pressure value according to the characteristics of the BCG signal comprises: obtaining a distance matrix L between each sensing point, and each sensing point Respective HI, IJ, HIJ pulse width interval matrix THI, TIJ, THIJ, IJ amplitude matrix AIJ of each sensing point, JJ interval matrix TJJ of each sensing point, and pulse wave transit time between each sensing point Matrix TPPT to calculate blood pressure value.
A mattress, comprising the multi-sensor blood pressure detection device according to any one of claims 1-5.
The mattress according to claim 6, wherein the sensors are arranged in a strip or dot matrix.
The mattress of claim 6, wherein the multi-sensor blood pressure detection device is arranged inside the mattress.
A multi-sensor blood pressure monitoring method based on BCG signals includes the following steps:

Multi-sensing point BCG signal acquisition unit collects BCG signals of multiple parts of the body;

The signal processing unit filters and amplifies the BCG signal, and judges the validity of the BCG signal;

If the signal is judged to be valid, perform BCG signal feature extraction; and

According to the characteristics of the BCG signal, enter the blood pressure calculation unit to measure the user's blood pressure value.
The method according to claim 9, wherein the multi-sensing point BCG signal acquisition unit comprises sensors arranged in different parts in a parallel or perpendicular direction to the body.
The method according to claim 10, wherein the sensor is a piezoelectric film sensor, a piezoelectric ceramic sensor, a piezoelectric cable sensor, an acceleration sensor, a gyroscope sensor, or an optical fiber sensor.
The multi-sensor blood pressure detection device according to claim 9, wherein the BCG signal feature extraction includes: H, I, J, K wave identification and waveform feature extraction, and the waveform feature includes the HI interval , IJ interval, HIJ pulse width, IJ amplitude, JJ interval and pulse wave transit time PPT between sensing points.
The multi-sensor blood pressure detection device according to claim 9, wherein the measuring the user's blood pressure value according to the characteristics of the BCG signal comprises: obtaining a distance matrix L between each sensing point, and the respective HI of each sensing point , IJ, HIJ pulse width interval matrix THI, TIJ, THIJ, the IJ amplitude matrix AIJ of each sensing point, the JJ interval matrix TJJ of each sensing point and the pulse wave conduction time matrix TPPT between each sensing point, Calculate the blood pressure value.