CN108403094A - A method of identification pulse wave wave crest - Google Patents

A method of identification pulse wave wave crest Download PDF

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Publication number
CN108403094A
CN108403094A CN201810249214.0A CN201810249214A CN108403094A CN 108403094 A CN108403094 A CN 108403094A CN 201810249214 A CN201810249214 A CN 201810249214A CN 108403094 A CN108403094 A CN 108403094A
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CN
China
Prior art keywords
pulse wave
signal
wave
local maximum
pulse
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Pending
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CN201810249214.0A
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Chinese (zh)
Inventor
魏永琴
耿兴光
张以涛
张海英
黄成军
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Institute of Microelectronics of CAS
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Institute of Microelectronics of CAS
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Priority to CN201810249214.0A priority Critical patent/CN108403094A/en
Publication of CN108403094A publication Critical patent/CN108403094A/en
Pending legal-status Critical Current

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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/725Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7253Details of waveform analysis characterised by using transforms
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7253Details of waveform analysis characterised by using transforms
    • A61B5/7257Details of waveform analysis characterised by using transforms using Fourier transforms

Abstract

A method of identification pulse wave wave crest, including:(1) waveform signal of pulse wave is acquired;(2) main wave frequency rate distribution is checked;(3) original pulse wave signal is pre-processed, removes noise;(4) frequency range based on main wave selects filter, highlights main wave using the filter of selection, excludes other peaks, pulse wave signal extracts shannon energy envelope to treated, then extracts local maximum;(5) true pulse wave peak point is positioned on original pulse wave signal using the local maximum.For the method for the invention when processing has the signal at high and narrow peak, identification is accurate, in the signal of non-stationary, has better stability to the division in period, and strong to the noise resisting ability of pulse wave signal.

Description

A method of identification pulse wave wave crest
Technical field
The present invention relates to pulse waveform recognition methods, and more particularly, to a kind of side of identification pulse wave wave crest Method.
Background technology
Human pulse wave generally has 6 characteristic points, as shown in Figure 1, a points indicate that actively affectionately valve opening point, c points are to receive Contracting phase pressure peak, d points are aortectasia hypotensive points, and e points are LV Diastolic starting points, and f points are again rich wave trough, g Point is again rich wave wave crest, and b points are pulse wave end point.The characteristic point of arteries and veins figure reflects cardiovascular different conditions respectively, is tool There is the characteristic point of physiological significance.Sphygmogram characteristic point both can be used for calculating cardiovascular function parameter, assistant analysis and judge painstaking effort Tubulose condition can be used for the type and pulse condition that judge arteries and veins figure.To diagnosis by feeling the pulse automation, there are very important for the identification of characteristic point Meaning is an essential ring.At present in the identification of pulse wave characteristic point, common method has slope-threshold arithmetic, small echo to become It changes, the method for the Gauss model of ratio of peak and fitting wrist pulse signal, due to the defect of noise jamming and method itself, these Method generally existing deviation, and robustness is poor.Main wave is most apparent most important feature in pulse wave signal, for identifying arteries and veins Period of fighting is very crucial, determines that the position of main wave divides and identify that other characteristic points have important work to the accurate of period With.Shannon energy envelope has extraordinary performance in the R blob detections of ECG signal, is equally applicable to pulse wave signal, how sharp It is to improve the important breakthrough mouth of accuracy and robustness with the accurate identification of characteristic point is carried out the characteristics of main wave.
Invention content
In order to solve the above-mentioned problems in the prior art, the present invention provides a kind of method of identification pulse wave wave crest.
It is provided by the invention identification pulse wave wave crest method include:
(1) waveform signal of pulse wave is acquired;
(2) main wave frequency rate distribution is checked;
(3) original pulse wave signal is pre-processed, removes noise;
(4) frequency range based on main wave selects filter, highlights main wave using the filter of selection, excludes other peaks, To treated, pulse wave signal extracts shannon energy envelope, then extracts local maximum;
(5) true pulse wave peak point is positioned on original pulse wave signal using the local maximum.
Preferably, check that the method that main wave frequency rate is distributed includes:Fast Fourier Transform (FFT) is carried out to original pulse wave signal, Then the signal broken up checks main wave frequency spectrogram frequency distribution.
Preferably, described to pre-process the baseline drift that original pulse wave signal is removed including the use of high-pass filtering, utilization is low Pass filter is used for handling due to the burr for shaking and breathing generation in waveform, and except carrying out normalizing to pulse wave signal after making an uproar Change.
Preferably, the normalized method is:Wherein d [n] is indicated at n points The amplitude of pulse wave, a [n] are the pulse wave after normalization.
Preferably, the computational methods of the shannon energy envelope are:
Se [n]=- f12[n]log(f12[n])
Wherein, F1 [n] is filtered signal.
Preferably, when extracting the local maximum, pulse wave signal is handled to subtract using low-pass filter The complexity of small search local maximum.
Preferably, the method for local maximum is extracted in Hilbert transform, wavelet transformation and Fourier transformation It is a kind of.
Preferably, the method for extracting local maximum is:Hilbert transform is carried out to pulse wave signal, then using cutting Line approach method finds pulse wave peak point.
Preferably, the method for the Hilbert transform is:
Preferably, the side of true pulse wave peak point is positioned on original pulse wave signal using the local maximum Method includes:The both sides that the local maximum of curve is identified in main wave, local minimum is found on original pulse waveform, Position where the local minimum corresponds to the beginning and end of Pulse period;
Local maximum is found between beginning and end, the local maximum corresponds to main wave in pulse waveform signal Wave crest.
Compared with prior art, the present invention has the following advantages:
(1) when processing has the signal at high and narrow peak, identification is accurate;
(2) in the signal of non-stationary, the present invention has better stability to the division in period;
(3) strong to the noise resisting ability of pulse wave signal.
Description of the drawings
Fig. 1 is the waveform signal of human body pulse wave;
Fig. 2 is flow chart of the method for the present invention;
Fig. 3 is collected original pulse wave signal in the embodiment of the present invention;
Fig. 4 is the pulse wave signal after bandpass filtering in the embodiment of the present invention;
Fig. 5 is the shannon energy envelope extracted in the embodiment of the present invention.
Specific implementation mode
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference Attached drawing, the present invention is described in further detail.
As shown in Fig. 2, the method for the identification pulse wave wave crest of the present invention includes:
1. acquiring pulse wave signal;
Patient's wrist C Pneumoniae is placed in by the sensor of pressure adjustable and obtains pulse voltage signal, segmentation is pressurizeed, via Pulse-tracing collection circuit conversion is digital signal, is stored in computer, as shown in Figure 3.
2. checking main wave frequency rate distribution
Fast Fourier Transform (FFT) (FFT) is carried out to original pulse wave signal, the signal broken up checks main wave frequency spectrogram Frequency distribution, the frequency range based on main wave design subsequent filter;
3. pretreatment
Corresponding noise is removed using high-pass filter and low-pass filter, is specifically included:It is removed using high-pass filtering former The baseline drift of beginning pulse wave signal is used for handling the hair in waveform due to shaking and breathing generation using the low-pass filtering of 30Hz Thorn.Except pulse wave signal being normalized after making an uproar:Wherein d [n] indicates the pulse at n points The amplitude of wave.A [n] is the pulse wave after normalization.
4. finding peak point
According to the frequency range of main wave, suitable bandpass filter (such as 1-4Hz) is designed, for highlighting main wave, is excluded Other peaks, as shown in Figure 4.To treated, pulse wave signal extracts shannon energy envelope, as shown in figure 5, then extracting Local maximum, local maximum correspond to the apparent position of main wave.It can reduce search local maximum using low-pass filter The complexity of value.
Shannon energy envelope Se [n] uses Se [n]=- f12[n]log(f12[n]) it calculates,
Wherein, F1 [n] is filtered signal.
The method for looking for envelope maximum point, which has, is much not limited to Hilbert transform, wavelet transformation and Fourier transformation Deng.
Time-domain signal can be extracted in pulse wave, and frequency-region signal can be extracted by Fourier transformation, pass through wavelet transformation Time frequency signal characteristic point can be extracted.
Important application is detection singular points to wavelet transformation in the signal processing.The rising edge of signal at singular point Failing edge corresponds to a pair of of local extremum of wavelet transformation detail signal.
Hilbert transform determines that the step of local maximum is:
After low pass filtering using Hilbert transform, the method for Hilbert transform is:
Hilbert transform defines the convolution of 1/ π t and x (t).
The moving average filter signal H (n) after HT removes low frequency wonder, passes through positive axis to the zero cross point of negative axis Position the wave crest R (k) of SEE signals (pulse wave signal after extraction shannon energy envelope).Accurate positioning for peak point Moving average filter length is very important.The real peak point of main wave is pulse signal in 0.25s near R (k) Maximum point.The maximum value of signal and main wave based on differentiation can find the starting point of each pulse period.
Pulse wave peak point is found using tangent line approach method, using between adjacent peak point on original pulse wave signal Minimum value positioning pulse wave cycle starting point, finally will be between two neighboring cycle starting point on original pulse wave signal Maximum value is determined as true pulse wave peak point.
Wherein, the partial detection packet on property field is carried out between adjacent cycle starting point on original pulse wave signal It includes:
The both sides that the local maximum of curve is identified in main wave, find local minimum, institute on original pulse waveform Position where stating local minimum corresponds to the starting point of Pulse period, terminal, i.e., this main wave on pulse wave signal curve The trough v2 of trough v1 and next main wave;
Local maximum is found between beginning and end, the local maximum corresponds to main wave in pulse wave signal Wave crest k.
Particular embodiments described above has carried out further in detail the purpose of the present invention, technical solution and advantageous effect Describe in detail bright, it should be understood that the above is only a specific embodiment of the present invention, is not intended to restrict the invention, it is all Within the spirit and principles in the present invention, any modification, equivalent substitution, improvement and etc. done should be included in the protection of the present invention Within the scope of.

Claims (10)

1. a kind of method of identification pulse wave wave crest, including:
(1) waveform signal of pulse wave is acquired;
(2) main wave frequency rate distribution is checked;
(3) original pulse wave signal is pre-processed, removes noise;
(4) frequency range based on main wave selects filter, highlights main wave using the filter of selection, excludes other peaks, to place Pulse wave signal after reason extracts shannon energy envelope, then extracts local maximum;
(5) true pulse wave peak point is positioned on original pulse wave signal using the local maximum.
2. the method for the method for claim 1, wherein checking main wave frequency rate distribution includes:To original pulse wave signal Fast Fourier Transform (FFT) is carried out, then the signal broken up checks main wave frequency spectrogram frequency distribution.
3. the method for claim 1, wherein the pretreatment removes original pulse wave signal including the use of high-pass filtering Baseline drift, be used for handling due to the burr for shaking and breathing generation in waveform using low-pass filtering, and except after making an uproar to arteries and veins Wave signal of fighting is normalized.
4. the method for claim 1, wherein the normalized method is:Its Middle d [n] indicates that the amplitude of the pulse wave at n points, a [n] are the pulse wave after normalization.
5. the method for claim 1, wherein the computational methods of the shannon energy envelope are:
Se [n]=- f12[n]log(f12[n])
Wherein, F1 [n] is filtered signal.
6. the method for claim 1, wherein when extracting the local maximum, using low-pass filter to pulse Wave signal is handled to reduce the complexity of search local maximum.
7. the method for claim 1, wherein the method for extraction local maximum is selected from Hilbert transform, small echo becomes It changes and one kind in Fourier transformation.
8. the method for claim 1, wherein the method for extraction local maximum is:Xi Er is carried out to pulse wave signal Bert converts, and then finds pulse wave peak point using tangent line approach method.
9. method as claimed in claim 8, wherein the method for the Hilbert transform is:
10. the method for claim 1, wherein being positioned on original pulse wave signal very using the local maximum The method of real pulse wave peak point includes:
The both sides that the local maximum of curve is identified in main wave, find local minimum, institute on original pulse waveform Position where stating local minimum corresponds to the beginning and end of Pulse period;
Local maximum is found between beginning and end, the local maximum corresponds to the wave of main wave in pulse waveform signal Peak.
CN201810249214.0A 2018-03-23 2018-03-23 A method of identification pulse wave wave crest Pending CN108403094A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110584624A (en) * 2019-09-18 2019-12-20 中国科学院微电子研究所 Pulse wave feature point identification method based on included angle value
CN113080891A (en) * 2021-03-17 2021-07-09 浙江大学 Method for extracting respiration rate and heart rate based on human body micro-motion signal

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US20070060827A1 (en) * 2005-08-26 2007-03-15 Nihon Kohden Corporation Apparatus and method for measuring pulse rate
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CN104367344A (en) * 2014-10-10 2015-02-25 广东工业大学 Method and device for detecting instant heart rate of fetus on basis of Shanon envelope
CN107432736A (en) * 2017-06-06 2017-12-05 新绎健康科技有限公司 A kind of method for identifying pulse wave signal
CN107616786A (en) * 2017-10-24 2018-01-23 新绎健康科技有限公司 Pulse wave recognition methods and pulse wave identification device

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Publication number Priority date Publication date Assignee Title
CN1251027A (en) * 1997-11-20 2000-04-19 精工爱普生株式会社 Pulse wave diagnostic apparatus, blood pressure monitor, pulse shape monitor and pharmacologic effect moritor
US20070060827A1 (en) * 2005-08-26 2007-03-15 Nihon Kohden Corporation Apparatus and method for measuring pulse rate
US20080167564A1 (en) * 2007-01-10 2008-07-10 Starr Life Sciences Corp. Techniques for accurately deriving physiologic parameters of a subject from photoplethysmographic measurements
CN102824166A (en) * 2012-07-05 2012-12-19 华东师范大学 Device for sorting treatment of pulse wave
CN103284702A (en) * 2013-06-17 2013-09-11 中国科学院苏州纳米技术与纳米仿生研究所 Electrocardiogram and pulse wave relation analysis method and method and device of fusion analysis
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CN107616786A (en) * 2017-10-24 2018-01-23 新绎健康科技有限公司 Pulse wave recognition methods and pulse wave identification device

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110584624A (en) * 2019-09-18 2019-12-20 中国科学院微电子研究所 Pulse wave feature point identification method based on included angle value
CN113080891A (en) * 2021-03-17 2021-07-09 浙江大学 Method for extracting respiration rate and heart rate based on human body micro-motion signal

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