CN104757959A - Pulse wave transmission velocity detecting method and system based on image foldover - Google Patents
Pulse wave transmission velocity detecting method and system based on image foldover Download PDFInfo
- Publication number
- CN104757959A CN104757959A CN201510187721.2A CN201510187721A CN104757959A CN 104757959 A CN104757959 A CN 104757959A CN 201510187721 A CN201510187721 A CN 201510187721A CN 104757959 A CN104757959 A CN 104757959A
- Authority
- CN
- China
- Prior art keywords
- pulse wave
- electrocardiosignal
- wave signal
- signal
- image
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Abstract
The invention relates to a pulse wave transmission velocity detecting method and system based on image foldover. The method comprises the steps of acquiring an electrocardiosignal and a pulse wave signal; after pretreatment and period position identification, extracting multiple corresponding period sequences; acquiring the peak position feature of the period sequences of each signal, and obtaining the position of each period sequence according to the peak position features; aligning the start points of all the period sequences of the electrocardiosignal and the pulse wave signal according to the peak position features based on image foldover, obtaining a single-period-sequence waveform after the values of corresponding positions of the aligned period sequences are superimposed, obtaining the power spectrum peak of the single-period-sequence waveform, taking the time corresponding to the power spectrum peak of the electrocardiosignal and the pulse wave signal as pulse wave transmission time PTT, and obtaining pulse wave transmission velocity PWV. Compared with the prior art, the method and system have the advantages that measurement time is short, and PWV detection precision is high.
Description
Technical field
The present invention relates to medical signals process field, especially relate to a kind of pulse wave transfer rate detection method based on image ghost image and system.
Background technology
Pulse wave transmission speed (Pulse Wave Velocity, PWV) refers to that pulse wave is transmitted to the speed of another ad-hoc location by an ad-hoc location of tremulous pulse.The index arterial stiffness of arterial elasticity and expansivity increases can make PWV numerical value rise, and arterial elasticity weakens PWV numerical value can be made to decline.So by measuring PWV numerical value, we can estimate elasticity and the expansivity of tremulous pulse.PWV numerical value or an extremely useful Noninvasive index, make the early discovery of the multiple blood vessel kind diseases such as arteriosclerosis, hypertension, hyperlipemia, diabetes and nephropathy and diagnosis become possibility.
Arteriosclerotic detection is more and more subject to the attention of medical circle, and its testing result can remind the arteriosclerotic situation of patient oneself, and treatment in time or the corresponding exercise of increase, change dietary structure.The computing formula of PWV is very simple, and the computational methods of PWV are as formula:
pTT represents the pulse wave transmission time, L represents distance, anything is not had to be worth research, simpler formula, higher to the requirement of calculating parameter, and wherein the measurement of time parameter just requires that detecting instrument provides good detection waveform, this point is very difficult, how the corresponding signal of human body, with very large noise, extracts the problem that actual signal is medical detecting Instrument facing in the signal of critical noisy.The multiplex general filtering technique of traditional PWV detecting instrument, or probability statistics technology carrys out stress release treatment as much as possible.Filtering technique can bring very large time-lag, PWV detects the mainly time in counting period, retardation can bring the very large error of calculation, and probability statistics need a large amount of sample datas, not only greatly can increase Measuring Time, and the sample size effectively will removing signal noise almost can not realize.
Summary of the invention
Object of the present invention is exactly there is the accurate not defect of testing result to overcome above-mentioned prior art and provide a kind of pulse wave transfer rate detection method based on image ghost image and system, adopts image ghost image technology to carry out PWV detection.First pretreatment is carried out to input signal (ECG signal and pulse wave signal); Then carry out the peak position feature extraction of ECG signal, use for image ghost image technology below; Finally adopt image ghost image technology that continuous print signal is divided into corresponding standalone module, with cross-power spectrum method, time delay estimation is carried out to standalone module, not only easy and simple to handle, and also testing result is accurately reliable.
Object of the present invention can be achieved through the following technical solutions:
A kind of pulse wave transfer rate detection method based on image ghost image comprises:
Step S1: gather electrocardiosignal and pulse wave signal;
Step S2: after respectively pretreatment and period position mark being carried out to step S1 center telecommunications number and pulse wave signal, extract multiple periodic sequences of electrocardiosignal and pulse wave signal;
Step S3: the respectively peak position feature of multiple periodic sequences of obtaining step S2 center telecommunications number and pulse wave signal, and the position of each periodic sequence in electrocardiosignal and pulse wave signal is obtained according to peak position feature;
Step S4: respectively step S3 center telecommunications number is alignd with each periodic sequence starting point in pulse wave signal according to peak position feature based on image ghost image technology, the value superposition of each periodic sequence relevant position after alignment obtains electrocardiosignal and pulse wave signal monocycle sequence waveform separately, obtain the power spectrum peak of two monocycle sequence waveforms respectively, using the interval corresponding to electrocardiosignal and pulse wave signal power spectrum peak as pulse wave propagate transmission time PTT, obtain pulse wave transfer rate PWV by formula (1):
Wherein, L is the distance between tremulous pulse had both been fixed a point at two, obtains this value by measuring body surface.
In described step S2, pretreatment comprises the amplitude process of amplitude, Phase Processing and pulse wave signal to electrocardiosignal;
Amplitude, the Phase Processing of electrocardiosignal comprise: get one group of electrocardiosignal, obtain the meansigma methods of this group electrocardiosignal, maximum and minima, judge whether meansigma methods is greater than the width of meansigma methods to minima to the width of maximum, if, then electrocardiosignal is input as forward signal, otherwise carry out value negate to electrocardiosignal, the electrocardiosignal after judgement is normalized;
The amplitude process of pulse wave signal comprises: get one group of pulse wave signal and be normalized.
In described step S2, period position mark comprises: according to the Changing Pattern of signal, identify at the end of each signal period, erasure signal cycle incomplete part, obtains complete periodic sequence.
10 ~ 20 corresponding periodic sequences are extracted in described step S2.
In described step S3, peak position feature comprises the number of crest and trough and corresponding position.
In described step S4, power spectrum peak is the highest crest characteristic point.
A kind of pulse wave transfer rate detection system based on image ghost image realizing said method comprises:
Data acquisition module, for gathering electrocardiosignal and pulse wave signal;
Pretreatment module, for receiving the output of data acquisition module, after carrying out pretreatment and period position mark respectively, extracts multiple periodic sequences of electrocardiosignal and pulse wave signal to electrocardiosignal and pulse wave signal;
Crest detection module, for receiving the output of pretreatment module, obtaining the peak position feature of multiple periodic sequences of electrocardiosignal and pulse wave signal respectively, and obtaining the position of each periodic sequence in electrocardiosignal and pulse wave signal according to peak position feature;
Image ghost image module, for receiving the output of crest detection module, respectively periodic sequence starting point each in electrocardiosignal and pulse wave signal is alignd according to peak position feature based on image ghost image technology, the value superposition of each periodic sequence relevant position after alignment obtains electrocardiosignal and pulse wave signal monocycle sequence waveform separately, obtain the power spectrum peak of two monocycle sequence waveforms, using the time corresponding to electrocardiosignal and pulse wave signal power spectrum peak as pulse wave propagate transmission time PTT, and then obtain pulse wave transfer rate PWV.
Described data acquisition module comprises:
Sensor unit, for gathering electrocardiosignal and pulse wave signal;
Signal condition unit, for the output of receiving sensor unit, carries out one-level differential amplification, low-pass filtering, high-pass filtering and secondary successively to electrocardiosignal and pulse wave signal and amplifies;
AD conversion unit, for the output of Received signal strength conditioning unit, sends to pretreatment module after carrying out AD conversion to electrocardiosignal and pulse wave signal.
Described pretreatment module, crest detection module and image ghost image module realize by the host computer containing virtual instrument.
Compared with prior art, the present invention has the following advantages:
1) the inventive method once only needs the input signal sample of limited periodic sequence, sample is few, thus the collection of signal can be realized fast, reject incomplete periodic sequence simultaneously, after the technical finesse of image ghost image, output waveform change obviously, and have comparative, the interval adopting the crosspower spectrum function monocyclic waveform to ECG signal and pulse wave signal to carry out individual features point is estimated, the interval of the highest crest characteristic point of two signals accurately can be obtained from the successful waveform of ghost image, this interval is exactly required pulse propagation time, the method compares traditional PWV detection method, can the impact of effectively overcoming noise, temporal retardation can not be caused again, improve PWV accuracy of detection.
2) the inventive method carries out phase judgment and periodic sequence station location marker to electrocardiosignal and pulse wave signal, prevents Electrocardiographic reverse signal and affects phase place location and reject incomplete periodic sequence, reduces the error of calculation.
3) the inventive method is to the peak position feature extraction of electrocardiogram and pulse wave signal, obtain input signal crest trough number and corresponding position, for dividing the position of each periodic sequence, bonding periodic sequence divides accurately.
4) the multiple complete periodic sequence that the inventive method extracts electrocardiosignal and pulse wave signal respectively carries out overlap-add procedure, obtain amplitude and expand the electrocardiosignal of many times and the monocycle waveform of pulse wave signal, the monocycle signal wave-shape amplitude change obtained after addition obviously, achieve the reinforcement to useful signal, weaken the impact of noise on signal.
5) the inventive method adopts image ghost image technology and Virtual instrument LabVIEW to devise host computer structure, practical, portable good.
6) present system adopts electrocardioelectrode and pulse wave sensor to gather electrocardiosignal and pulse wave signal, realizes the collection of human body millivolt level signal; Devise signal conditioning circuit and denoising and processing and amplifying are carried out to signal, be met the analogue signal of AD sampling condition; Adopt the USB-6008 data collecting card of NI company, gather while realizing multiple signals and be sent to host computer.Devise the host computer based on virtual instrument simultaneously, make full use of the powerful advantages of virtual instrument on signal testing and analysis, make the checkout gear construction cycle short, flexible and efficient, virtual instrument is utilized to realize image ghost image technology, the impact of effectively overcoming noise, temporal retardation can not be caused again, improve PWV accuracy of detection.
Accompanying drawing explanation
Fig. 1 is data acquisition module structural representation in present system;
Fig. 2 is the host computer structural representation containing virtual instrument in present system;
Fig. 3 is signal condition element circuit schematic diagram in present system;
Fig. 4 is the signal waveform schematic diagram collected in the inventive method;
Fig. 5 is the signal waveform schematic diagram after the inventive method acceptance of the bid " | " process;
Fig. 6 is electrocardiosignal in the inventive method after amplitude Phase Processing and pulse wave signal waveform schematic diagram;
Fig. 7 is the inventive method medium wave peak detection function schematic diagram;
Fig. 8 is waveform alignment function schematic diagram in the inventive method;
Fig. 9 is crosspower spectrum function schematic diagram in the inventive method;
Figure 10 is the signal waveform schematic diagram in the inventive method after ghost image.
In figure: 1, data acquisition module, 2, host computer, 11, sensor unit, 12, signal condition unit, 13, AD conversion unit, 21, pretreatment module, 22, crest detection module, 23, image ghost image module, 121, one-level differential amplifier circuit, 122, low-pass filter circuit, 123, high-pass filtering circuit, 124, second amplifying circuit.
Detailed description of the invention
Below in conjunction with the drawings and specific embodiments, the present invention is described in detail.The present embodiment is implemented premised on technical solution of the present invention, give detailed embodiment and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
As shown in Figure 1 and Figure 2, a kind of pulse wave transfer rate detection system based on image ghost image comprises data acquisition module 1 and host computer 2 two large divisions.Data acquisition module 1, for gathering electrocardiosignal and pulse wave signal, comprises three unit, is respectively sensor unit 11, signal condition unit 12 and AD conversion unit 13; Host computer 2 containing virtual instrument includes three processing modules, is respectively pretreatment module 21, crest detection module 22 and image ghost image module 23.
Operation principle: first, sensor unit 11 gathers electrocardiosignal and pulse wave signal, output signal is the analogue signal with noise and DC component, need to obtain pure ECG simulator signal and pulse wave analogue signal through signal condition unit 12, signal after conditioning carries out AD conversion by AD conversion unit 13 again, the digital signal of the electrocardio collected and pulse wave is uploaded to host computer 2 by AD conversion unit 13, host computer 2 utilizes integrated virtual instrument to process electrocardiosignal, pulse wave signal and analyze, and the result after Treatment Analysis is exported.Below each ingredient is specifically described:
Sensor unit 11 comprises ECG electrode and fluctuation sensor, and fluctuation sensor adopts PVDF piezoelectric membrane, measuring range 0 ~ 50g, trueness error≤5%F.S, sensitivity >=20mV/F.S, the pulse wave signal of extraction is truer, and the human pulse ripple signal surveyed is millivolt level signal.
The outfan of the sensor input connection unit 11 of signal condition unit 12.Signal condition unit 12 is divided into electrocardiosignal modulate circuit and pulse wave signal modulate circuit, and two signal conditioning circuit structures are similar.Pulse wave signal modulate circuit as shown in Figure 3, comprises the one-level differential amplifier circuit 121, low-pass filter circuit 122, high-pass filtering circuit 123 and the second amplifying circuit 124 that connect successively.One-level differential amplifier circuit 121 comprises AD620 difference amplifier and peripheral circuits (comprising resistance R1 and electric capacity C1, C2) thereof.Low-pass filter circuit 122 comprises OPA2277 chip and peripheral circuits (comprising resistance R2, R3, R4, R5 and electric capacity C3) thereof, high-pass filtering circuit 123 comprises OPA2277 chip and peripheral circuits (comprising resistance R6, R7, R8 and electric capacity C4, C5) thereof, and second amplifying circuit 124 comprises OPA2277 chip and peripheral circuits (comprising resistance R9, R10, R11, R12 and electric capacity C6, C7) thereof.Wherein, OPA2277 chip is double operational circuit, U2A and U2B is the different piece in same chip.The acquired signal of ECG electrode, fluctuation sensor is passed through differential amplifier pre-amp output signal by two signal conditioning circuits, improve signal to noise ratio, the high-frequency noise in signal is removed again by low-pass filter circuit 122, removed the DC component in signal again by high-pass filtering circuit 123, then be met the analogue signal of AD sampling condition by second amplifying circuit 124.
The outfan of the input connection signal conditioning unit 12 of AD conversion unit 13, outfan connects the input of host computer 2.AD conversion unit 13 adopts the USB-6008 data collecting card of NI company.This card is the multifunctional data acquisition card based on USB2.0 serial port, and have 8 analog input terminals to can be used for receiving electrocardiosignal and pulse wave signal, every road input range is ± 10V, 10Ks/s, 12 bit resolutions.It is converted analogue signal to digital signal and is sent into the USB interface of host computer 2 by USB data line, processes further.
Host computer 2 is the computers of the LabVIEW software platform be integrated with based on virtual instrument Programming in Digital Image Processing, realize functions such as signal processing, analysis, display, storage, wave shape playback, signal smoothing filtering, Periodic identification, baseline adjustment, Feature point recognition, make full use of the powerful advantages of host computer 2 on signal testing and analysis containing virtual instrument, make the checkout gear construction cycle short, flexible and efficient.As shown in Figure 2,
Pretreatment module 21, for receiving the output of data acquisition module 1, after respectively pretreatment and period position mark being carried out to electrocardiosignal and pulse wave signal, extract electrocardiosignal and pulse wave signal 10 ~ 20 periodic sequences separately, accuracy of detection can be guaranteed like this, reduce Measuring Time, in the present embodiment, choose 15 periodic sequences;
Crest detection module 22, for receiving the output of pretreatment module 21, to the peak position feature of multiple periodic sequences of electrocardiosignal and pulse wave signal, and obtains the position of each periodic sequence according to peak position feature;
Image ghost image module 23, for receiving the output of crest detection module 22, respectively each periodic sequence starting point of electrocardiosignal and pulse wave signal is alignd according to peak position feature based on image ghost image technology, the value superposition of each periodic sequence relevant position after alignment obtains electrocardiosignal and pulse wave signal monocycle sequence waveform separately, obtain the power spectrum peak of two monocycle sequence waveforms, using time as the pulse wave propagate transmission time PTT (namely obtaining the interval of individual features point from the oscillogram of monocyclic electrocardiosignal and pulse wave signal) corresponding to electrocardiosignal and pulse wave signal power spectrum peak, and then obtain pulse wave transfer rate PWV.
As shown in Figure 1 and Figure 2, a kind of said detecting system that utilizes carries out comprising based on the pulse wave transfer rate detection method of image ghost image:
Step S1: data acquisition module 1 gathers electrocardiosignal and pulse wave signal.The electro-physiological signals that electrocardiosignal produces when referring to cardiomotility, pulse wave signal refers to the physiological signal that radial artery blood liquid stream movable property is raw.
The present invention acquires the upper and lower limb of human body and aortal signal, and the signal collected as shown in Figure 4, is followed successively by carotid artery waveform, radial artery waveform, femoral artery waveform, ankle red artery waveform, phonocardiogram, electrocardiogram from top to bottom.Can find out that collectable signal has very large noise from waveform.What the present invention adopted is the method for electrocardiograph pulse, only needs to process the tremulous pulse end pulse wave signal at electrocardiosignal and a place.The present invention extracts electrocardiosignal and the relatively little and signal of the pulse wave of radial artery that is that easily measure of noise, namely extracts the second row and the 6th row signal.
Step S2: after the electrocardiosignal that pretreatment module 21 exports data acquisition module 1 respectively and pulse wave signal carry out pretreatment and period position mark, extract electrocardiosignal and pulse wave signal 15 periodic sequences separately.Wherein, pretreatment comprises the amplitude process of amplitude, Phase Processing and pulse wave signal to electrocardiosignal, is specially:
Get one group of ECG signal and one group of pulse wave signal, obtain the meansigma methods of this group ECG signal, maximum and minima, relatively meansigma methods to maximum and meansigma methods large to which width of minima, if meansigma methods is larger to maximum width, then be input as forward signal, output to next step, otherwise value negate is carried out to input ECG signal, finally to the amplitude process that electrocardiogram and pulse wave signal are normalized.
Period position mark comprises: electrocardiosignal and pulse wave signal compare numerical value in respective signal respectively, obtain the Changing Pattern of signal, identify at the end of each signal period, erasure signal cycle incomplete part, finally obtains the complete periodic sequence of electrocardiosignal and pulse wave signal respectively.As shown in Figure 5, periodic sequence is designated and processes periodic sequence mark " | ", several subsequences are divided into by original pulse wave sequence, two subsequences of removing head and the tail, reject incomplete part, each middle subsequence is a complete pulse cycle, can extract separately a complete periodic sequence, realize the Periodic identification to original pulse wave.Extracting corresponding 15 complete periodic sequences is that the technical finesse of image ghost image is prepared, and can guarantee accuracy of detection like this, reduce Measuring Time.
To electrocardiosignal and radial artery signal, the result of two signal ghost images after pretreatment as shown in Figure 6.
Step S3: crest detection module 22 obtains the peak position feature of the electrocardiosignal of pretreatment module 21 output and the periodic sequence of pulse wave signal respectively, and obtains the position of each periodic sequence according to peak position feature.Peak position feature comprises the number of crest and trough and corresponding position.
Crest detection module 22 adopts the crest detection function of standard, for a waveforms detection control in the signal processing tool kit of labview virtual software, the crest number that waveform is provided can be obtained by this control, the amplitude vector of corresponding crest and the position vector of crest, crest detection function as shown in Figure 7.
Step S4: image ghost image module 23 is based on image ghost image Technology design, the electrocardiosignal exported by crest detection module 22 respectively according to peak position characteristic use waveform alignment function and each periodic sequence of pulse wave signal carry out starting point alignment, time is identical with component value, be convenient to two signals compare, the value superposition of each periodic sequence relevant position after alignment obtains electrocardiosignal and pulse wave signal monocycle sequence waveform separately, the power spectrum peak (power spectrum peak is the highest crest characteristic point) of two monocycle sequence waveforms is obtained again by crosspower spectrum function, using the time corresponding to electrocardiosignal and pulse wave signal power spectrum peak as pulse wave propagate transmission time PTT, pulse wave transfer rate PWV is obtained by formula (1):
Wherein, L is the distance between tremulous pulse had both been fixed a point at two, and such as radial artery, to the distance of femoral artery two measurement point, obtains this value by measuring body surface.
Image ghost image technology refers to by one or more addition of waveforms on another waveform, forms the effect of ghost image, and each waveform of ghost image must be alignment at abscissa time point, before ghost image, also must carry out denoising to waveform.
As shown in Figure 8, be the waveform conditioning control in the signal processing tool kit of labview virtual software, in result, waveform A exports identical with component value with the time of waveform B output waveform alignment function.Waveform alignment function by the alignment of the starting point of the monocycle waveform of electrocardiosignal and pulse wave signal, in order to avoid there is image offset and cause resultant error.
Crosspower spectrum function as shown in Figure 9, for the analysis of spectrum control in the signal processing tool kit of labview virtual software, crosspower spectrum reaction input signal is at the mutual relation of different frequency point, its phase place is a kind of conventional delay time estimation method, the method, under the environment of small noise and moderate reverberation once, can obtain more accurate time delay estimated value.Cross-power spectrum method obtains the interval of electrocardiosignal and pulse wave signal individual features point.
The periodic sequence that electrocardiogram and pulse wave signal 15 are complete carries out overlap-add procedure, obtain amplitude and expand the ECG signal of 15 times and the monocycle waveform of pulse wave signal, the monocycle signal wave-shape amplitude change obtained after addition obviously, achieve the reinforcement to useful signal, weaken the impact of noise on signal.Superpose successful waveform as shown in Figure 10, solid line is pulse wave signal, and dotted line is electrocardiosignal, can find out that last oscillogram signal is very clear, also do not have retardation, the phase place retardation of the signal calculated like this is just very accurate, thus substantially increases certainty of measurement and repeatability.The interval obtaining electrocardiosignal and pulse wave signal individual features point by crosspower spectrum function calculates PTT and just greatly can improve computational accuracy.
To sum up, the method that the present invention adopts is electrocardiograph pulse method, by gathering electrocardiosignal and tremulous pulse end pulse signal, calculating the interval of electrocardio and pulse signal individual features point, representing the transmission time.The treatment technology adopted is image ghost image technology, a series of process is carried out to the electrocardiosignal gathered and pulse wave signal, finally obtain monocyclic electrocardiosignal and pulse wave signal, alignment also utilizes crosspower spectrum function to obtain the interval of individual features point after image ghost image, i.e. the pulse wave transmission time.
Claims (9)
1., based on a pulse wave transfer rate detection method for image ghost image, it is characterized in that, comprising:
Step S1: gather electrocardiosignal and pulse wave signal;
Step S2: after respectively pretreatment and period position mark being carried out to step S1 center telecommunications number and pulse wave signal, extract multiple periodic sequences of electrocardiosignal and pulse wave signal;
Step S3: the respectively peak position feature of multiple periodic sequences of obtaining step S2 center telecommunications number and pulse wave signal, and the position of each periodic sequence in electrocardiosignal and pulse wave signal is obtained according to peak position feature;
Step S4: respectively step S3 center telecommunications number is alignd with each periodic sequence starting point in pulse wave signal according to peak position feature based on image ghost image technology, the value superposition of each periodic sequence relevant position after alignment obtains electrocardiosignal and pulse wave signal monocycle sequence waveform separately, obtain the power spectrum peak of two monocycle sequence waveforms respectively, using the interval corresponding to electrocardiosignal and pulse wave signal power spectrum peak as pulse wave propagate transmission time PTT, obtain pulse wave transfer rate PWV by formula (1):
Wherein, L is the distance between tremulous pulse had both been fixed a point at two, obtains this 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 characterized in that, in described step S2, pretreatment comprises the amplitude process of amplitude, Phase Processing and pulse wave signal to electrocardiosignal;
Amplitude, the Phase Processing of electrocardiosignal comprise: get one group of electrocardiosignal, obtain the meansigma methods of this group electrocardiosignal, maximum and minima, judge whether meansigma methods is greater than the width of meansigma methods to minima to the width of maximum, if, then electrocardiosignal is input as forward signal, otherwise carry out value negate to electrocardiosignal, the electrocardiosignal after judgement is normalized;
The amplitude process of pulse wave signal comprises: get one group of pulse wave signal and be normalized.
3. a kind of pulse wave transfer rate detection method based on image ghost image according to claim 1, it is characterized in that, in described step S2, period position mark comprises: according to the Changing Pattern of signal, identify 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, is characterized in that, extracts 10 ~ 20 corresponding periodic sequences in described step S2.
5. a kind of pulse wave transfer rate detection method based on image ghost image according to claim 1, is characterized in that, in described step S3, peak position feature comprises the number of crest and trough and corresponding position.
6. a kind of pulse wave transfer rate detection method based on image ghost image according to claim 1, it is characterized in that, in described step S4, power spectrum peak is the highest crest characteristic point.
7. realize the pulse wave transfer rate detection system based on image ghost image of method described in claim 1, it is characterized in that, comprising:
Data acquisition module, for gathering electrocardiosignal and pulse wave signal;
Pretreatment module, for receiving the output of data acquisition module, after carrying out pretreatment and period position mark respectively, extracts multiple periodic sequences of electrocardiosignal and pulse wave signal to electrocardiosignal and pulse wave signal;
Crest detection module, for receiving the output of pretreatment module, obtaining the peak position feature of multiple periodic sequences of electrocardiosignal and pulse wave signal respectively, and obtaining the position of each periodic sequence in electrocardiosignal and pulse wave signal according to peak position feature;
Image ghost image module, for receiving the output of crest detection module, respectively periodic sequence starting point each in electrocardiosignal and pulse wave signal is alignd according to peak position feature based on image ghost image technology, the value superposition of each periodic sequence relevant position after alignment obtains electrocardiosignal and pulse wave signal monocycle sequence waveform separately, obtain the power spectrum peak of two monocycle sequence waveforms, using the time corresponding to electrocardiosignal and pulse wave signal power spectrum peak as pulse wave propagate transmission time PTT, and then obtain pulse wave transfer rate PWV.
8. a kind of pulse wave transfer rate detection system based on image ghost image according to claim 7, it is characterized in that, described data acquisition module comprises:
Sensor unit, for gathering electrocardiosignal and pulse wave signal;
Signal condition unit, for the output of receiving sensor unit, carries out one-level differential amplification, low-pass filtering, high-pass filtering and secondary successively to electrocardiosignal and pulse wave signal and amplifies;
AD conversion unit, for the output of Received signal strength conditioning unit, sends to pretreatment module after carrying out AD conversion to electrocardiosignal and pulse wave signal.
9. a kind of pulse wave transfer rate detection system based on image ghost image according to claim 7, it is characterized in that, described pretreatment module, crest detection module and image ghost image module realize by the host computer containing virtual instrument.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510187721.2A CN104757959B (en) | 2015-04-20 | 2015-04-20 | Pulse wave transmission velocity detecting method and system based on image foldover |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510187721.2A CN104757959B (en) | 2015-04-20 | 2015-04-20 | Pulse wave transmission velocity detecting method and system based on image foldover |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104757959A true CN104757959A (en) | 2015-07-08 |
| CN104757959B CN104757959B (en) | 2017-05-03 |
Family
ID=53640316
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510187721.2A Active CN104757959B (en) | 2015-04-20 | 2015-04-20 | Pulse wave transmission velocity detecting method and system based on image foldover |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104757959B (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106073742A (en) * | 2013-05-13 | 2016-11-09 | 天津点康科技有限公司 | A kind of blood pressure measuring system and method |
| CN106073745A (en) * | 2016-06-15 | 2016-11-09 | 西北工业大学 | Heart rate detection method based on smart mobile phone |
| CN107049269A (en) * | 2017-03-06 | 2017-08-18 | 武汉嫦娥医学抗衰机器人股份有限公司 | A kind of Pulse Signals Treatment Analysis system |
| CN107174197A (en) * | 2016-03-10 | 2017-09-19 | 深圳市理邦精密仪器股份有限公司 | Custodial care facility and its method for displaying waveform, device |
| CN107806933A (en) * | 2017-12-08 | 2018-03-16 | 中国工程物理研究院激光聚变研究中心 | The measurement apparatus and its method of optical material induced with laser shock wave velocity of wave |
| CN109350036A (en) * | 2018-10-15 | 2019-02-19 | 广东宝莱特医用科技股份有限公司 | A kind of blood oxygen, ecg wave form Overlapping display method and device thereof |
| CN110960199A (en) * | 2019-12-24 | 2020-04-07 | 中国人民解放军陆军军医大学第一附属医院 | System for double-variable measurement of arteriosclerosis degree |
| CN112057041A (en) * | 2020-08-07 | 2020-12-11 | 中国科学院深圳先进技术研究院 | Polarized photoacoustic imaging probe and photoacoustic imaging device |
| CN113205518A (en) * | 2021-07-05 | 2021-08-03 | 雅安市人民医院 | Medical vehicle image information processing method and device |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1820703A (en) * | 2006-01-26 | 2006-08-23 | 中国人民解放军空军航空医学研究所 | Measuring method and system for achieving blood pressure continuous measurement of pulse wave conduction time |
| CN101229058A (en) * | 2007-01-26 | 2008-07-30 | 香港中文大学 | Initial calibrating equipment for using pulse wave transmitting time method to measure arteriotony |
| TW201021763A (en) * | 2008-09-29 | 2010-06-16 | Qualcomm Inc | Method and apparatus for non-invasive cuff-less blood pressure estimation using pulse arrival time and heart rate with adaptive calibration |
| US20110066010A1 (en) * | 2009-09-15 | 2011-03-17 | Jim Moon | Body-worn vital sign monitor |
| DE102010014761A1 (en) * | 2010-04-13 | 2011-10-13 | Dräger Medical GmbH | Method for determining heart rate, respiration rate, pulse wave running time and medium blood pressure of patient, involves preparing control-and-evaluation unit to determine pressure of patient and output at control-and display unit |
| CN104188637A (en) * | 2014-09-24 | 2014-12-10 | 中国科学院合肥物质科学研究院 | Aorta pulse wave conduction time acquiring method based on waveform matching method |
| WO2014208289A1 (en) * | 2013-06-28 | 2014-12-31 | 株式会社村田製作所 | Biological state-estimating device |
-
2015
- 2015-04-20 CN CN201510187721.2A patent/CN104757959B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1820703A (en) * | 2006-01-26 | 2006-08-23 | 中国人民解放军空军航空医学研究所 | Measuring method and system for achieving blood pressure continuous measurement of pulse wave conduction time |
| CN101229058A (en) * | 2007-01-26 | 2008-07-30 | 香港中文大学 | Initial calibrating equipment for using pulse wave transmitting time method to measure arteriotony |
| TW201021763A (en) * | 2008-09-29 | 2010-06-16 | Qualcomm Inc | Method and apparatus for non-invasive cuff-less blood pressure estimation using pulse arrival time and heart rate with adaptive calibration |
| US20110066010A1 (en) * | 2009-09-15 | 2011-03-17 | Jim Moon | Body-worn vital sign monitor |
| DE102010014761A1 (en) * | 2010-04-13 | 2011-10-13 | Dräger Medical GmbH | Method for determining heart rate, respiration rate, pulse wave running time and medium blood pressure of patient, involves preparing control-and-evaluation unit to determine pressure of patient and output at control-and display unit |
| WO2014208289A1 (en) * | 2013-06-28 | 2014-12-31 | 株式会社村田製作所 | Biological state-estimating device |
| CN105377137A (en) * | 2013-06-28 | 2016-03-02 | 株式会社村田制作所 | Biological state-estimating device |
| CN104188637A (en) * | 2014-09-24 | 2014-12-10 | 中国科学院合肥物质科学研究院 | Aorta pulse wave conduction time acquiring method based on waveform matching method |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106073742A (en) * | 2013-05-13 | 2016-11-09 | 天津点康科技有限公司 | A kind of blood pressure measuring system and method |
| CN107174197A (en) * | 2016-03-10 | 2017-09-19 | 深圳市理邦精密仪器股份有限公司 | Custodial care facility and its method for displaying waveform, device |
| CN106073745A (en) * | 2016-06-15 | 2016-11-09 | 西北工业大学 | Heart rate detection method based on smart mobile phone |
| CN107049269A (en) * | 2017-03-06 | 2017-08-18 | 武汉嫦娥医学抗衰机器人股份有限公司 | A kind of Pulse Signals Treatment Analysis system |
| CN107806933B (en) * | 2017-12-08 | 2023-06-13 | 中国工程物理研究院激光聚变研究中心 | Device and method for measuring laser-induced shock wave velocity of optical material |
| CN107806933A (en) * | 2017-12-08 | 2018-03-16 | 中国工程物理研究院激光聚变研究中心 | The measurement apparatus and its method of optical material induced with laser shock wave velocity of wave |
| CN109350036A (en) * | 2018-10-15 | 2019-02-19 | 广东宝莱特医用科技股份有限公司 | A kind of blood oxygen, ecg wave form Overlapping display method and device thereof |
| CN110960199A (en) * | 2019-12-24 | 2020-04-07 | 中国人民解放军陆军军医大学第一附属医院 | System for double-variable measurement of arteriosclerosis degree |
| CN110960199B (en) * | 2019-12-24 | 2022-05-27 | 中国人民解放军陆军军医大学第一附属医院 | System for double-variable measurement of arteriosclerosis degree |
| CN112057041B (en) * | 2020-08-07 | 2021-12-28 | 中国科学院深圳先进技术研究院 | Polarized photoacoustic imaging probe and photoacoustic imaging device |
| CN112057041A (en) * | 2020-08-07 | 2020-12-11 | 中国科学院深圳先进技术研究院 | Polarized photoacoustic imaging probe and photoacoustic imaging device |
| CN113205518A (en) * | 2021-07-05 | 2021-08-03 | 雅安市人民医院 | Medical vehicle image information processing method and device |
| CN113205518B (en) * | 2021-07-05 | 2021-09-07 | 雅安市人民医院 | Medical vehicle image information processing method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104757959B (en) | 2017-05-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104757959B (en) | Pulse wave transmission velocity detecting method and system based on image foldover | |
| CN102144916B (en) | Multi-channel pulse signal detecting method and device capable of automatically regulating pressure | |
| CN101732040B (en) | Non-invasive multipath pulse wave detection device, system and analytical system | |
| US11006885B2 (en) | Apparatus for determining blood pressure | |
| CN103892818B (en) | A kind of non-invasive central arterial blood pressure measuring method and equipment | |
| US20150057506A1 (en) | Arrayed electrodes in a wearable device for determining physiological characteristics | |
| CN103584919B (en) | Multi-modal bio signal synchronous detecting system and method | |
| CN103054562B (en) | Cardiovascular function detection method based on multi-channel pulse wave form analysis and device thereof | |
| CN104382571A (en) | Method and device for measuring blood pressure upon radial artery pulse wave conduction time | |
| CN109008999B (en) | Method for measuring heart sound and pulse wave conduction time and portable measuring device | |
| CN104367344A (en) | Method and device for detecting instant heart rate of fetus on basis of Shanon envelope | |
| CN103989463B (en) | A kind of radial artery pulse wave detection system based on fingertip pulse wave and method | |
| CN101919704B (en) | Heart sound signal positioning and segmenting method | |
| CN202960481U (en) | Traditional Chinese medicine pulse condition acquisition device | |
| CN202920160U (en) | Traditional Chinese medicine pulse condition collection system | |
| CN110840405A (en) | Manufacturing method of flexible array sensor and pulse condition detection system based on flexible array sensor | |
| CN109330581A (en) | A kind of wearable pulse information acquisition device | |
| CN103284703B (en) | Aortic pulse wave transfer time measuring method based on upper extremity artery information | |
| CN104068841B (en) | A kind of measuring method and device measuring Indices of Systolic Time parameter | |
| CN107397542B (en) | Dynamic blood pressure monitoring wearable device based on pulse wave sensor and monitoring method | |
| CN109009004A (en) | A kind of physical examinations method based on Chinese medicine pulse analysis | |
| CN205433676U (en) | Portable many physiological parameters of human body detector based on raspberry group | |
| CN113539522A (en) | Continuous blood pressure monitoring method based on single-path cardiac shock signal | |
| CN105167759A (en) | Human pulse wave velocity measuring method and system based on intelligent mobile phone | |
| KR20190103626A (en) | A portable ECG electrode and an ECG measurement system for small animals |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| EXSB | Decision made by sipo to initiate substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20200429 Address after: No. 1110, floor 1, No. 76, Huadian lane, Xiacheng District, Hangzhou City, Zhejiang Province Patentee after: HANGZHOU HUIXIN MEDICAL TECHNOLOGY Co.,Ltd. Address before: 201620 Shanghai city Songjiang District Dragon Road No. 333 Patentee before: SHANGHAI UNIVERSITY OF ENGINEERING SCIENCE |
|
| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: Room 108, 1 / F, building 3, 1030 Tongpu Road, Putuo District, Shanghai, 200333 Patentee after: Shanghai Huixin Medical Technology Co., Ltd Address before: No. 1110, floor 1, No. 76, Huadian lane, Xiacheng District, Hangzhou City, Zhejiang Province Patentee before: HANGZHOU HUIXIN MEDICAL TECHNOLOGY Co.,Ltd. |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20210727 Address after: 313200 1 Changhong East Street, Fuxi street, Deqing County, Huzhou, Zhejiang, 926 Patentee after: Zhejiang Huiqin Medical Devices Co.,Ltd. Address before: 200333 room 108, 1st floor, building 3, 1030 Tongpu Road, Putuo District, Shanghai Patentee before: Shanghai Huixin Medical Technology Co., Ltd |