CN104757959B - Pulse wave transmission velocity detecting method and system based on image foldover - Google Patents

Abstract

The present invention relates to a pulse wave transmission rate detection method and system based on image ghosting. The method includes: step S1: collecting ECG signals and pulse wave signals; step S2: after preprocessing and period position identification, extracting the corresponding Multiple periodic sequences; Step S3: Obtain the peak position characteristics of the periodic sequence of the signal, and obtain the position of each periodic sequence according to the peak position characteristics; Step S4: Based on the image ghosting technology, according to the peak position characteristics, the ECG signal and pulse wave The starting point of each cycle sequence of the signal is aligned, and the value of the corresponding position of each cycle sequence after alignment is superimposed to obtain a single-cycle sequence waveform, and the highest point of the power spectrum of the single-cycle sequence waveform, the highest point of the power spectrum of the ECG signal and pulse wave signal The corresponding time is used as the pulse wave transmission time PTT, and then the pulse wave transmission rate PWV is obtained. Compared with the prior art, the invention has the advantages of short measurement time, high PWV detection precision and the like.

Description

A pulse wave transmission rate detection method and system based on image ghosting

technical field

The invention relates to the field of medical signal processing, in particular to a pulse wave transmission rate detection method and system based on image ghosting.

Background technique

Pulse Wave Velocity (PWV) refers to the rate at which the pulse wave propagates from one specific position of the artery to another specific position. Increased arterial stiffness, an index of arterial elasticity and expandability, will increase the PWV value, while weakening arterial elasticity will decrease the PWV value. So by measuring the PWV value, we can estimate the elasticity and distensibility of arteries. The PWV value is also a very useful non-invasive indicator, making it possible to detect and diagnose a variety of vascular diseases such as arteriosclerosis, hypertension, hyperlipidemia, diabetes and kidney disease early.

The detection of arteriosclerosis has been paid more and more attention by the medical field. The detection results can remind patients of their own arteriosclerosis status, timely treatment or increase the corresponding exercise, and change the diet structure. The calculation formula of PWV is very simple, the calculation method of PWV is as follows: PTT means pulse wave transmission time, L means distance, there is nothing worth studying, but the simpler the formula, the higher the requirements for calculation parameters, and the measurement of time parameters requires the detection instrument to provide a good detection waveform. It is very difficult. The corresponding signal of the human body has a lot of noise. How to extract the real signal from the signal with severe noise is a common problem faced by medical testing instruments. Traditional PWV detection instruments use general filtering technology or probability statistics technology to eliminate noise as much as possible. However, filtering technology will bring a large time delay. PWV detection is mainly to calculate the interval time. The delay will bring a large calculation error, and probability statistics require a large amount of sample data, which will not only greatly increase the measurement time, but also effectively remove The signal-to-noise sample size is nearly impossible to achieve.

Contents of the invention

The purpose of the present invention is to provide a pulse wave transmission rate detection method and system based on image ghosting to overcome the defect of inaccurate detection results in the above-mentioned prior art, and to use image ghosting technology for PWV detection. First, the input signal (ECG signal and pulse wave signal) is preprocessed; then the peak position feature extraction of the ECG signal is performed for the use of the image ghosting technology; finally, the continuous signal is divided into corresponding independent signals by the image ghosting technology. Modules, using the cross power spectrum method to estimate the time delay of independent modules, not only easy to operate, but also accurate and reliable detection results.

The purpose of the present invention can be achieved through the following technical solutions:

A pulse wave transmission rate detection method based on image ghosting comprises:

Step S1: collecting ECG signals and pulse wave signals;

Step S2: after performing preprocessing and periodic position identification on the ECG signal and the pulse wave signal in step S1 respectively, extract multiple periodic sequences of the ECG signal and the pulse wave signal;

Step S3: Obtain the peak position characteristics of multiple periodic sequences of the central electrical signal and pulse wave signal in step S2 respectively, and obtain the position of each periodic sequence in the electrocardiographic signal and pulse wave signal according to the peak position characteristics;

Step S4: Align the starting points of each cycle sequence in the central electrical signal and pulse wave signal in step S3 based on the image ghosting technology according to the peak position characteristics, and superimpose the values of the corresponding positions of each cycle sequence after alignment to obtain the ECG signal and pulse The single-period sequence waveforms of each wave signal, respectively obtain the highest point of the power spectrum of the two single-cycle sequence waveforms, and take the time interval corresponding to the highest point of the power spectrum of the ECG signal and the pulse wave signal as the pulse wave transmission time PTT, which is given by the formula (1) Obtain the pulse wave transmission rate PWV:

Among them, L is the distance of the artery between two given points, which is obtained by measuring the body surface.

The preprocessing in the step S2 includes amplitude and phase processing of the ECG signal and amplitude processing of the pulse wave signal;

The amplitude and phase processing of ECG signals includes: taking a group of ECG signals, obtaining the average value, maximum value and minimum value of this group of ECG signals, and judging whether the width from the average value to the maximum value is greater than the width from the average value to the minimum value. Width, if so, the ECG signal input is a positive signal, otherwise, the value of the ECG signal is reversed, and the judged ECG signal is normalized;

The amplitude processing of the pulse wave signal includes: taking a group of pulse wave signals for normalization processing.

The period position identification in the step S2 includes: according to the change law of the signal, marking at the end of each signal period, deleting the incomplete part of the signal period, and obtaining a complete period sequence.

In the step S2, the corresponding 10-20 periodic sequences are extracted.

The peak position features in step S3 include the number and corresponding positions of peaks and valleys.

The highest point of the power spectrum in the step S4 is the highest peak feature point.

A pulse wave transmission rate detection system based on image ghosting for realizing the above method comprises:

The data acquisition module is used for collecting ECG signals and pulse wave signals;

The preprocessing module is used to receive the output of the data acquisition module, and after performing preprocessing and periodic position identification on the ECG signal and the pulse wave signal respectively, extract multiple periodic sequences of the ECG signal and the pulse wave signal;

The peak detection module is used to receive the output of the preprocessing module, respectively obtain the peak position characteristics of multiple periodic sequences of the ECG signal and the pulse wave signal, and obtain each period sequence of the ECG signal and the pulse wave signal according to the peak position characteristics s position;

The image ghosting module is used to receive the output of the peak detection module. Based on the image ghosting technology, the starting point of each cycle sequence in the ECG signal and the pulse wave signal is aligned according to the peak position characteristics, and the corresponding position of each cycle sequence after alignment The values of the superposition of the ECG signal and the pulse wave signal are the single-period sequence waveforms, and the highest point of the power spectrum of the two single-cycle sequence waveforms is obtained, and the time corresponding to the highest point of the power spectrum of the ECG signal and the pulse wave signal is used as the pulse wave Propagate the transmission time PTT, and then obtain the pulse wave transmission rate PWV.

The data acquisition module includes:

A sensor unit for collecting electrocardiographic signals and pulse wave signals;

The signal conditioning unit is used to receive the output of the sensor unit, and sequentially perform primary differential amplification, low-pass filtering, high-pass filtering and secondary amplification on the ECG signal and the pulse wave signal;

The AD conversion unit is used to receive the output of the signal conditioning unit, perform AD conversion on the ECG signal and the pulse wave signal, and then send it to the preprocessing module.

The preprocessing module, peak detection module and image superimposition module are all realized by a host computer containing virtual instruments.

Compared with the prior art, the present invention has the following advantages:

1) The method of the present invention only needs a limited number of input signal samples of periodic sequences at a time, and the sampling samples are few, so that the acquisition of signals can be quickly realized, and incomplete periodic sequences are eliminated at the same time, and the output waveform changes significantly after being processed by image ghosting technology, and Comparable, the cross power spectrum function is used to estimate the time interval of the corresponding feature points of the single-cycle waveforms of the electrocardiogram signal and the pulse wave signal, and the time interval of the highest peak feature points of the two signals can be accurately obtained from the waveform of the successful overlap. The time interval is the required pulse propagation time. Compared with the traditional PWV detection method, this method can effectively overcome the influence of noise without causing time delay, and improves the PWV detection accuracy.

2) The method of the present invention performs phase discrimination and periodic sequence position identification on the electrocardiographic signal and the pulse wave signal, prevents the reverse signal of the electrocardiogram from affecting the phase location and eliminates incomplete periodic sequences, and reduces calculation errors.

3) The method of the present invention extracts the peak position feature of the electrocardiogram and the pulse wave signal, obtains the number of peaks/troughs and corresponding positions of the input signal, and is used to divide the position of each cycle sequence to ensure accurate division of the single cycle sequence.

4) The method of the present invention extracts a plurality of complete periodic sequences of the electrocardiographic signal and the pulse wave signal respectively and carries out superimposition processing, obtains the single-period waveform of the electrocardiographic signal and the pulse wave signal whose amplitude is enlarged multiple times, and the single-period waveform obtained after adding The amplitude of the periodic signal waveform changes significantly, which realizes the strengthening of the effective signal and weakens the influence of noise on the signal.

5) The method of the present invention adopts image overlapping technology and virtual instrument LabVIEW to design a host computer structure, which has strong practicability and good portability.

6) The system of the present invention adopts electrocardiographic electrodes and pulse wave sensors to collect electrocardiographic signals and pulse wave signals to realize the collection of human body millivolt signals; a signal conditioning circuit is designed to denoise and amplify the signals to obtain AD sampling conditions. The analog signal; the USB-6008 data acquisition card of NI Company is used to realize the simultaneous acquisition and transmission of multiple signals to the host computer. At the same time, a host computer based on virtual instruments is designed, making full use of the powerful advantages of virtual instruments in signal testing and analysis, making the development cycle of the detection device short, flexible and efficient, using virtual instruments to realize image ghosting technology, effectively overcoming the influence of noise, and No time lag is caused, and the PWV detection accuracy is improved.

Description of drawings

Fig. 1 is the structural representation of data acquisition module in the system of the present invention;

Fig. 2 is the structural representation of the upper computer that contains the virtual instrument in the system of the present invention;

Fig. 3 is the circuit diagram of signal conditioning unit in the system of the present invention;

Fig. 4 is the signal waveform schematic diagram that gathers in the inventive method;

Fig. 5 is the signal waveform schematic diagram after the mark "|" is processed in the method of the present invention;

Fig. 6 is the schematic diagram of electrocardiogram signal and pulse wave signal waveform after amplitude and phase processing in the method of the present invention;

Fig. 7 is a schematic diagram of the peak detection function in the method of the present invention;

Fig. 8 is a schematic diagram of a waveform alignment function in the method of the present invention;

Fig. 9 is a schematic diagram of cross power spectrum function in the method of the present invention;

Fig. 10 is a schematic diagram of the signal waveform after ghosting in the method of the present invention.

In the figure: 1. Data acquisition module, 2. Host computer, 11. Sensor unit, 12. Signal conditioning unit, 13. AD conversion unit, 21. Preprocessing module, 22. Peak detection module, 23. Image overlay module, 121, a first-stage differential amplifier circuit, 122, a low-pass filter circuit, 123, a high-pass filter circuit, and 124, a second-stage amplifier circuit.

detailed description

The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is carried out on the premise of the technical solution of the present invention, and detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

As shown in Figure 1 and Figure 2, a pulse wave transmission rate detection system based on image ghosting includes two parts: a data acquisition module 1 and a host computer 2. The data acquisition module 1 is used to collect ECG signals and pulse wave signals, and includes three units, namely a sensor unit 11, a signal conditioning unit 12 and an AD conversion unit 13; the host computer 2 containing virtual instruments includes three processing modules, respectively It is a preprocessing module 21 , a peak detection module 22 and an image superimposition module 23 .

Working principle: firstly, the sensor unit 11 collects the ECG signal and the pulse wave signal, and the output signal is an analog signal with noise and DC component, which needs to be obtained by the signal conditioning unit 12 to obtain a pure ECG analog signal and pulse wave analog signal, and the conditioning The final signal is then AD-converted by the AD conversion unit 13, and the AD conversion unit 13 uploads the collected digital signals of the electrocardiogram and pulse wave to the host computer 2, and the host computer 2 utilizes the integrated virtual instrument to analyze the electrocardiogram signal and the pulse wave. The signal is processed and analyzed, and the processed and analyzed results are output. Each component is described in detail below:

The sensor unit 11 includes electrocardiogram electrodes and a pulsation sensor. The pulsation sensor adopts PVDF piezoelectric film, the measurement range is 0-50g, the accuracy error is ≤5% F.S, and the sensitivity is ≥20mV/F.S. The extracted pulse wave signal is more real, and the measured human pulse The wave signal is a millivolt level signal.

The input end of the signal conditioning unit 12 is connected to the output end of the sensor unit 11 . The signal conditioning unit 12 is divided into an electrocardiographic signal conditioning circuit and a pulse wave signal conditioning circuit, and the two signal conditioning circuits are similar in structure. As shown in FIG. 3 , the pulse wave signal conditioning circuit includes a first-stage differential amplifier circuit 121 , a low-pass filter circuit 122 , a high-pass filter circuit 123 and a second-stage amplifier circuit 124 connected in sequence. The primary differential amplifier circuit 121 includes AD620 differential amplifier and its surrounding circuits (including resistor R1 and capacitors C1 and C2). Low-pass filter circuit 122 comprises OPA2277 chip and surrounding circuit (comprising resistance R2, R3, R4, R5 and electric capacity C3), high-pass filtering circuit 123 comprises OPA2277 chip and surrounding circuit (comprising resistance R6, R7, R8 and electric capacity C4, C5), the secondary amplifier circuit 124 includes the OPA2277 chip and its surrounding circuits (including resistors R9, R10, R11, R12 and capacitors C6, C7). Among them, the OPA2277 chip is a dual operational amplifier circuit, and U2A and U2B are different parts of the same chip. The two signal conditioning circuits pre-amplify the output signals of the electrocardiogram electrodes and pulsation sensors through the differential amplifier to improve the signal-to-noise ratio, and then remove the high-frequency noise in the signal through the low-pass filter circuit 122, and then pass the high-pass filter circuit 123 The DC component in the signal is removed, and then the analog signal satisfying the AD sampling condition is obtained through the secondary amplifier circuit 124 .

The input end of the AD conversion unit 13 is connected to the output end of the signal conditioning unit 12 , and the output end is connected to the input end of the upper computer 2 . The AD conversion unit 13 adopts the USB-6008 data acquisition card of NI Company. The card is a multi-function data acquisition card based on the USB2.0 serial port. There are 8 analog input terminals that can be used to receive ECG signals and pulse wave signals. Each input range is ±10V, 10Ks/s, and 12-bit resolution . It converts the analog signal into a digital signal and sends it to the USB interface of the upper computer 2 through the USB data line for further processing.

The upper computer 2 is a computer that integrates the LabVIEW software platform based on virtual instrument image programming, and realizes functions such as signal processing, analysis, display, storage, waveform playback, signal smoothing and filtering, cycle identification, baseline adjustment, and feature point identification. The powerful advantages of the upper computer 2 with virtual instruments in signal testing and analysis make the detection device development cycle short, flexible and efficient. as shown in picture 2,

The preprocessing module 21 is used to receive the output of the data acquisition module 1, perform preprocessing and cycle position identification on the ECG signal and the pulse wave signal respectively, and extract 10 to 20 cycle sequences of the ECG signal and the pulse wave signal respectively, This can ensure the detection accuracy and reduce the measurement time. In this embodiment, 15 periodic sequences are selected;

The peak detection module 22 is used to receive the output of the preprocessing module 21, to the peak position characteristics of a plurality of periodic sequences of the electrocardiogram signal and the pulse wave signal, and obtain the position of each periodic sequence according to the peak position characteristics;

The image ghosting module 23 is used to receive the output of the peak detection module 22. Based on the image ghosting technology, according to the peak position characteristics, the starting points of each cycle sequence of the ECG signal and the pulse wave signal are respectively aligned, and each cycle sequence after alignment The values of the corresponding positions are superimposed to obtain the respective single-cycle sequence waveforms of the ECG signal and the pulse wave signal, and the highest point of the power spectrum of the two single-cycle sequence waveforms is obtained, and the time corresponding to the highest point of the power spectrum of the ECG signal and the pulse wave signal is taken as The pulse wave transmission time PTT (that is, the time interval for obtaining the corresponding feature points from the single-cycle ECG signal and the waveform diagram of the pulse wave signal), and then the pulse wave transmission rate PWV is obtained.

As shown in Figure 1 and Figure 2, a pulse wave transmission rate detection method based on image ghosting using the above detection system includes:

Step S1: The data collection module 1 collects ECG signals and pulse wave signals. The ECG signal refers to the physiological electrical signal generated when the heart is active, and the pulse wave signal refers to the physiological signal generated by the radial artery blood flow.

The present invention collects the signals of the upper and lower limbs and the aorta of the human body, and the collected signals are as shown in Figure 4, which are carotid artery waveform, radial artery waveform, femoral artery waveform, ankle artery waveform, phonocardiogram, and electrocardiogram from top to bottom. . It can be seen from the waveform that the signal that can be collected has a lot of noise. The present invention adopts the electrocardiographic pulse method, and only needs to process the electrocardiographic signal and the pulse wave signal of one arterial terminal. The present invention extracts the ECG signal and the pulse wave signal of the radial artery which is relatively small in noise and easy to measure, that is, extracts the second row and the sixth row signal.

Step S2: The preprocessing module 21 performs preprocessing and cycle position identification on the ECG signal and the pulse wave signal output by the data acquisition module 1 respectively, and then extracts 15 cycle sequences of the ECG signal and the pulse wave signal respectively. Among them, the preprocessing includes the amplitude and phase processing of the ECG signal and the amplitude processing of the pulse wave signal, specifically:

Take a group of ECG signals and a group of pulse wave signals, obtain the average value, maximum value and minimum value of this group of ECG signals, compare the width from the average value to the maximum value and the average value to the minimum value, if the width from the average value to the maximum value If it is larger, the input is a positive signal, and the output goes to the next step; otherwise, the value of the ECG signal at the input terminal is reversed, and finally the normalized amplitude processing is performed on the ECG and pulse wave signals.

Periodic position identification includes: ECG signal and pulse wave signal are compared with the values in their respective signals to obtain the change rule of the signal, mark at the end of each signal period, delete the incomplete part of the signal period, and finally obtain the ECG signal respectively and a complete periodic sequence of pulse wave signals. As shown in Figure 5, the periodic sequence is marked with "|" for the periodic sequence, that is, the original pulse wave sequence is divided into several subsequences, the first and last two subsequences are removed, and the incomplete part is eliminated. Each subsequence in the middle They are all a complete pulse cycle, and a complete cycle sequence can be extracted separately to realize the cycle recognition of the original pulse wave. The corresponding 15 complete cycle sequences are extracted to prepare for image ghosting technology processing, which can ensure detection accuracy and reduce measurement time.

Figure 6 shows the superimposition results of the ECG signal and the radial artery signal after preprocessing.

Step S3: The peak detection module 22 respectively acquires the peak position characteristics of the periodic sequence of the ECG signal and the pulse wave signal output by the preprocessing module 21, and obtains the position of each periodic sequence according to the peak position characteristic. Peak features include the number and corresponding positions of peaks and troughs.

The peak detection module 22 adopts a standard peak detection function, which is a waveform detection control in the signal processing toolkit of the labview virtual software, through which the number of peaks of the provided waveform, the amplitude vector of the corresponding peak and the position vector of the peak can be obtained, The peak detection function is shown in Figure 7.

Step S4: The image ghosting module 23 is designed based on the image ghosting technology, and uses the waveform alignment function to align the starting point of each cycle sequence of the ECG signal and the pulse wave signal output by the peak detection module 22 according to the peak position characteristics, time and The component values are the same, which is convenient for the comparison of the two signals. The values of the corresponding positions of each cycle sequence after alignment are superimposed to obtain the respective single-cycle sequence waveforms of the ECG signal and the pulse wave signal, and then the two single-cycle sequence waveforms are obtained through the cross-power spectrum function. The highest point of the power spectrum (the highest point of the power spectrum is the highest peak feature point), the time corresponding to the highest point of the power spectrum of the ECG signal and the pulse wave signal is taken as the pulse wave transmission time PTT, and the pulse wave transmission rate is obtained by formula (1) PWV:

Among them, L is the distance between two given points of the artery, such as the distance between the radial artery and the femoral artery, which is obtained by measuring the body surface.

Image ghosting technology refers to superimposing one or more waveforms on another waveform to form a ghosting effect. Each waveform of the ghosting must be aligned at the time point of the abscissa. Before the ghosting, the waveform must be Noise removal.

The waveform alignment function is shown in Figure 8, which is the waveform conditioning control in the signal processing toolkit of the labview virtual software. In the result, the time and component values of the waveform A output and waveform B output are the same. The waveform alignment function aligns the starting point of the single-cycle waveform of the ECG signal and the pulse wave signal to avoid image misalignment and result errors.

The cross power spectrum function is shown in Figure 9, which is the spectrum analysis control in the signal processing toolkit of the labview virtual software. The cross power spectrum reflects the relationship between input signals at different frequency points, and its phase is a commonly used time delay estimation method. , this method can obtain a more accurate time delay estimate in the environment of weak noise and moderate reverberation. The cross power spectrum method obtains the time interval of the corresponding feature points of the ECG signal and the pulse wave signal.

The 15 complete cycle sequences of the electrocardiogram and pulse wave signals are superimposed and processed to obtain a single-cycle waveform of the electrocardiogram signal and pulse wave signal whose amplitude is enlarged by 15 times. The effective signal is strengthened, and the influence of noise on the signal is weakened. The successfully superimposed waveform is shown in Figure 10. The solid line is the pulse wave signal, and the dotted line is the ECG signal. It can be seen that the final waveform signal is very clear and has no delay, so the phase delay of the calculated signal is very accurate, so that Greatly improved measurement accuracy and repeatability. Calculating the PTT by obtaining the time interval of the corresponding feature points of the ECG signal and the pulse wave signal through the cross power spectrum function can greatly improve the calculation accuracy.

To sum up, the method adopted in the present invention is the ECG pulse method, which represents the transmission time by collecting the ECG signal and the pulse signal at the end of the artery, and calculating the time interval between the corresponding feature points of the ECG signal and the pulse signal. The processing technology used is the image ghosting technology, which performs a series of processing on the collected ECG signal and pulse wave signal, and finally obtains the single-cycle ECG signal and pulse wave signal, and uses the cross power spectrum function to obtain the image after alignment and ghosting. The time interval of the corresponding feature points is the pulse wave transmission time.

Claims (9)

1. a kind of pulse wave transfer rate detection method based on image ghost image, it is characterised in that include：

Step S1：Collection electrocardiosignal and pulse wave signal；

Step S2：After respectively step S1 center telecommunications number and pulse wave signal are carried out with pretreatment and period position mark, extract Multiple periodic sequences of electrocardiosignal and pulse wave signal；

Step S3：The peak position feature of multiple periodic sequences of obtaining step S2 center telecommunications number and pulse wave signal, and root respectively The position of each periodic sequence during electrocardiosignal and pulse wave signal are obtained according to peak position feature；

Step S4：Respectively will be every in step S3 center telecommunications number and pulse wave signal according to peak position feature based on image ghost image technology Individual periodic sequence starting point alignment, the value superposition of each the periodic sequence relevant position after alignment obtain electrocardiosignal and pulse wave The respective monocycle sequence waveform of signal, obtains the power spectrum peak of two monocycle sequence waveforms, respectively by electrocardiosignal Transmission time PTT is propagated as pulse wave with the time interval corresponding to pulse wave signal power spectrum peak, obtained by formula (1) To pulse wave transfer rate PWV：

$PWV=\frac{L}{PTT}---\left(1\right)$

Wherein, L is the distance between tremulous pulse had both been pinpointed at two, obtains the value by measuring body surface.

2. a kind of pulse wave transfer rate detection method based on image ghost image according to claim 1, it is characterised in that Pretreatment in step S2 includes that the amplitude of the amplitude to electrocardiosignal, Phase Processing and pulse wave signal is processed；

The amplitude of electrocardiosignal, Phase Processing include：One group of electrocardiosignal is taken, meansigma methodss, the maximum of this group of electrocardiosignal is obtained Value and minima, judge whether meansigma methodss are more than meansigma methodss to the width of minima to the width of maximum, and if so, then electrocardio is believed Number input otherwise, carries out value to electrocardiosignal and negates for forward signal, and the electrocardiosignal after judgement is normalized；

The amplitude of pulse wave signal is processed to be included：Take one group of pulse wave signal to be normalized.

3. a kind of pulse wave transfer rate detection method based on image ghost image according to claim 1, it is characterised in that In step S2, period position mark includes：According to the Changing Pattern of signal, it is identified at the end of each signal period, Erasure signal cycle incomplete part, obtains complete periodic sequence.

4. a kind of pulse wave transfer rate detection method based on image ghost image according to claim 1, it is characterised in that Corresponding 10～20 periodic sequences are extracted in step S2.

5. a kind of pulse wave transfer rate detection method based on image ghost image according to claim 1, it is characterised in that In step S3, peak position feature includes number and the corresponding position of crest and trough.

6. a kind of pulse wave transfer rate detection method based on image ghost image according to claim 1, it is characterised in that In step S4, power spectrum peak is highest crest characteristic point.

7. a kind of pulse wave transfer rate detecting system based on image ghost image for realizing claim 1 methods described, its feature It is, including：

Data acquisition module, for gathering electrocardiosignal and pulse wave signal；

Pretreatment module, for the output of receiving data acquisition module, carries out pre- place to electrocardiosignal and pulse wave signal respectively After reason and period position mark, multiple periodic sequences of electrocardiosignal and pulse wave signal are extracted；

Crest detection module, for receiving the output of pretreatment module, obtains the multiple of electrocardiosignal and pulse wave signal respectively The peak position feature of periodic sequence, and in obtaining electrocardiosignal and pulse wave signal according to peak position feature each periodic sequence position Put；

Image ghost image module, for the output of received wave blob detection module, is distinguished according to peak position feature based on image ghost image technology Each periodic sequence starting point in electrocardiosignal and pulse wave signal is alignd, each the periodic sequence relevant position after alignment Value superposition obtains electrocardiosignal and the respective monocycle sequence waveform of pulse wave signal, obtains the work(of two monocycle sequence waveforms Rate composes peak, the time interval corresponding to electrocardiosignal and pulse wave signal power spectrum peak is propagated as pulse wave and is passed Defeated time PTT, and then obtain pulse wave transfer rate PWV.

8. a kind of pulse wave transfer rate detecting system based on image ghost image according to claim 7, it is characterised in that The data acquisition module includes：

Sensor unit, for gathering electrocardiosignal and pulse wave signal；

Signal condition unit, for receiving the output of sensor unit, carries out one-level successively to electrocardiosignal and pulse wave signal Differential amplification, low-pass filtering, high-pass filtering and two grades of amplifications；

AD conversion unit, manages the output of unit for receiving signal, after being AD converted to electrocardiosignal and pulse wave signal It is sent to pretreatment module.

9. a kind of pulse wave transfer rate detecting system based on image ghost image according to claim 7, it is characterised in that The pretreatment module, crest detection module and image ghost image module are realized by the host computer containing virtual instrument.