CN105686846A - Heart sound signal characteristic automatic extraction method - Google Patents

Abstract

The invention provides a heart sound signal characteristic automatic extraction method comprising the following steps: preprocessing a heart sound signal, and using a viola integration waveform method to extract a signal envelope; segmenting the signal envelope, and positioning so as to obtain a first heart sound segment zone and a second heart sound segment zone; calculating a first heart sound segment zone first heart sound characteristic constant and a second heart sound segment zone second heart sound characteristic constant; extracting heart sound signal characteristics. The heart sound signal characteristic automatic extraction method is simple in calculation, fast in speed, can accurately position a heart sound signal diastole stage and contraction stage, can effectively extract heart sound signal characteristic envelope, can reserve original information on the heart sound signal, and is very suitable for analyzing and processing heart sound signal containing noises and interferences.

Description

Cardiechema signals characteristic automatic extraction method

Technical field

The present invention relates to the technical field that analysis of PCG Signal processes, particularly relate to the characteristic automatic extraction method of a kind of cardiechema signals。

Background technology

Heart sound is in cardiac cycle, and due to myocardial contraction and diastole, valvular keying, and blood flow impacts the mechanical vibration caused by the factor such as ventricle wall and large artery trunks, passes to thoracic wall by surrounding tissue and the Vibration Signal in Frequency Domain that produces。Cardiechema signals contains the information being related to heart physiological and pathology in a large number, before cardiovascular disease not yet develops into and is enough to produce clinic and pathological change, the noise and the distortion that occur in heart sound are significant to the diagnosis of valvular heart disease and some congenital heart disease。

The mode generally detecting heart sound is to pass through cardiophony, whether sufferer can be suffered from heart disease by stethoscope and make tentative diagnosis by doctor or professional person that clinical experience is abundant, but this is easily by the impact of the factors such as the clinical experience of doctor and auscultation level, environment, and result does not have the effect of quantitative analysis。Phonocardiographic subsequently occur compensate for this deficiency, but phonocardiogram is by recording electrocardio and cardiechema signals simultaneously, it is impossible to carries out quantitative analysis, relies on Professional knowledge and the clinical experience of analysis personnel to a great extent。Currently used at most, be considered as Diagnosing Cardiac disease " goldstandard " be ultrasoundcardiogram, carrying out comprehensive descision heart function state by the ejection fraction and various parameter measuring human body, this method accuracy is compared first two method reliability and is improve many, but expense is costly。In sum, diagnosing human heart function by cardiechema signals is the diagnostic method that a kind of cost is low, non-invasive, reliability is high, has great social value and economic worth。

The transverse axis of general cardiechema signals is time shaft, and the longitudinal axis is amplitude。Heart reservation index (on heart sound, show as cardiechema signals feature, i.e. S1/S2, D/S, wherein, S1 is first heart sound eigenvalue, and S2 is second heart sound eigenvalue, and D/S is time limit ratio, the abbreviation of diastole/systole)。When heart is normal, the temporal signatures of cardiechema signals is that the relaxing period of heart is more than systole, heart sound is then reflected as second heart sound start to the persistent period that next cycle first heart sound signal starts more than first heart sound start to second heart sound start time persistent period, then D/S is equal to the persistent period that second heart sound starts to start to next cycle first heart sound signal, with the ratio that first heart sound starts the persistent period started to second heart sound。Medical personnel can pass through These parameters appraiser's systemic heart function status, and then the disease that human heart is relevant can be carried out diagnosis in early days, is conducive to early diagnosis and the treatment of cardiac-related diseases, it is achieved that the Non-invasive detection of heart disease。

But in cardiechema signals feature extraction, traditional is, by reference signal, cardiechema signals is carried out segmentation and location, and conventional reference signal has electrocardiosignal, strength arterial signal。Cardiechema signals is carried out segmentation and location by electrocardiosignal, be based on electrocardiosignal Q, starting point and the cardiechema signals of R, S, T ripple have relation one to one, but it is disadvantageous in that must to obtain premised on effective electrocardiosignal, can not realizing the automatic acquisition to cardiechema signals eigenvalue, it is analyzed and is also required to lean on veteran related personnel based on the artificial determination of reference signal simultaneously。And the segmentation method that the modern times employ up to is exactly the method adopting signal envelope that signal carries out segmentation and location, do not adopt reference signal can realize the automatic segmentation of cardiechema signals, therefore algorithm is required higher, elapsed time is long, it is rough mostly to there is envelope in the current algorithm extracting signal envelope, raw information loses too much deficiency, and the maximum difficulty that presently, there are can not realize the automatic acquisition of cardiechema signals eigenvalue exactly, particularly that the signal accuracy rate bigger containing noise and interference is relatively low, can not accurately to cardiechema signals relaxing period with Syst be accurately positioned。

Summary of the invention

For above shortcomings in prior art, patent purpose of the present invention is in that how to provide a kind of algorithm simple, cardiechema signals relaxing period and systole to be accurately positioned, it is achieved the automatic obtaining method of cardiechema signals feature。

For solving above-mentioned technical problem, it is achieved goal of the invention, the technical solution used in the present invention is as follows:

Cardiechema signals characteristic automatic extraction method, including following several steps:

A), after the cardiechema signals collected being carried out resampling, preprocessed signal X is obtained then through pretreatment_T(k)；

B) utilize viola integrated waveform method, extract preprocessed signal X_TSignal envelope E in (k)_T(m), it may be assumed that

$E_T\left(m\right)=\frac{1}{2L_T+1}\underset{k=m-L_T}{\overset{m+L_T}{\Σ}}{\left(X_T\right(k)-{\stackrel{\‾}{X}}_T(m\left)\right)}^2;$

Wherein, L_TBeing step-length, k is coefficient, m=0,1,2 ..., M, M is preprocessed signal X_TThe length of (k),It is 2 times of L_TPreprocessed signal X in interval_TThe signal average of (k)；

C) signal envelope is carried out segmentation；

D) location obtains first heart sound segment identifier and second heart sound segment identifier, calculates and obtains the first heart sound eigenvalue of first heart sound segment identifier and the second heart sound eigenvalue of second heart sound segment identifier, extracts cardiechema signals feature。

Further, the concretely comprising the following steps of described step a:

A1) obtain sampled signal after the described cardiechema signals collected being carried out resampling, be filtered obtaining filtering signal to sampled signal with high pass filter and notch filter；

A2) filtering signal is carried out wavelet multi_resolution analysis denoising, obtain described preprocessed signal X_T(k)。

Further, the concretely comprising the following steps of described step b:

B1) step-length L is obtained by below equation calculating_T:

L_T=0.5*0.1*F_S；

Wherein, F_sFor the sample frequency of resampling in described step a；

B2) 2 times of L are asked for_TPreprocessed signal X in interval_TThe signal average of (k)That is:

${\stackrel{\‾}{X}}_T\left(m\right)=\frac{1}{2L_T+1}\underset{k=m-L_T}{\overset{m+L_T}{\Σ}}{X}_T\left(k\right);$

B3) utilize viola integrated waveform method, extract preprocessed signal X_TSignal envelope E in (k)_T(m), it may be assumed that

$E_T\left(m\right)=\frac{1}{2L_T+1}\underset{k=m-L_T}{\overset{m+L_T}{\Σ}}{\left(X_T\right(k)-{\stackrel{\‾}{X}}_T(m\left)\right)}^2.$

Further, the concretely comprising the following steps of described step c):

C1) to signal envelope E_TM () carries out windowing sub-frame processing after, intercept the signal envelope in n smooth cycle for processing signal envelope；Setting threshold line Level=0.01 intercepting and process signal envelope, the method that i-th periodic signal in process n the cycle of signal envelope carries out segmentation is as follows:

C2) threshold line Level=0.01 and the i-th periodic signal processing signal envelope have 4 joinings, on transverse axis, the left envelope waypoint of these 4 joinings from left to right called after i-th cycle first heart sound successively, the right envelope waypoint of i-th cycle first heart sound, the left envelope waypoint of i-th cycle second heart sound, the right envelope waypoint of i-th cycle second heart sound；On transverse axis, these 4 joining coordinates are from left to right saved in i-th group of data of envelope segmentation array C successively；

C3) in envelope segmentation array C, extract the left envelope waypoint coordinate of i-th cycle first heart sound and the left envelope waypoint coordinate of i-th cycle second heart sound successively and be saved in left envelope segmentation array C_LI-th group of data in, extract the right envelope waypoint coordinate of i-th cycle first heart sound and the right envelope waypoint of i-th cycle second heart sound successively and coordinate be saved in right envelope segmentation array C_RI-th group of data in；

C4) segmentation is carried out according to the method for above-mentioned steps c2, c3 to processing all the other periodic signals in n the cycle of signal envelope。

Further, the concretely comprising the following steps of described step d): do following process to processing i-th periodic signal in n the cycle of signal envelope:

D1) left envelope segmentation array C is left in acquisition in_LIn i-th group of data and right envelope segmentation array C_RIn i-th group of data: the left envelope waypoint of i-th cycle first heart sound, the right envelope waypoint of i-th cycle first heart sound, the left envelope waypoint of i-th cycle second heart sound, the right envelope waypoint of i-th cycle second heart sound；The left envelope waypoint of location i-th cycle first heart sound is i-th cycle first heart sound segment identifier with the interval of the right envelope waypoint of i-th cycle first heart sound, and the left envelope waypoint of location i-th cycle second heart sound is i-th cycle second heart sound segment identifier with the interval of the right envelope waypoint of i-th cycle second heart sound；

D2) local maximum in i-th cycle in process signal envelope is asked for by peak successively algorithm, determine that the maximum being positioned at i-th cycle first heart sound segment identifier is i-th cycle first heart sound eigenvalue, it is determined that the maximum being positioned at i-th cycle second heart sound segment identifier is i-th cycle second heart sound eigenvalue；And abscissa corresponding for these 2 maximum points is saved in i-th group of data of array peak；

D3) split fix is carried out according to the method for above-mentioned steps d1, d2 to processing all the other periodic signals in n the cycle of signal envelope；

D4) in conjunction with cardiechema signals temporal signatures, it is determined that all first heart sound eigenvalues and second heart sound eigenvalue, cardiechema signals feature is extracted。

Further, described step c4) further comprising the steps of below:

C5) preprocessed signal X is obtained_TK time period signal that in (), abscissa scope is identical with processing signal envelope abscissa scope is for processing signal；

C6) ask for the short-time energy signal processing signal and short-time zero-crossing rate signal, then set threshold value M_H, it may be assumed that

$M_H=\underset{0}{\overset{M}{\∫}}{X}_T\left(k\right)dk;$

Use threshold value M_HIntercept short-time energy signal, to short-time energy signal and in n the cycle of short-time zero-crossing rate signal i-th periodic signal be handled as follows:

C7) threshold value M_H4 joinings are had with the i-th periodic signal of short-time energy signal, on transverse axis, the left energy subsection point of these 4 joinings from left to right called after i-th cycle first heart sound successively, the right energy subsection point of i-th cycle first heart sound, the left energy subsection point of i-th cycle second heart sound, the right energy subsection point of i-th cycle second heart sound；On transverse axis, these 4 joining coordinates are from left to right saved in i-th group of data of energy subsection array A successively；

C8) in energy subsection array A, extract the left energy subsection point coordinates of i-th cycle first heart sound and the left energy subsection point coordinates of i-th cycle second heart sound successively and be saved in left energy subsection array A_LI-th group of data in, extract the right energy subsection point coordinates of i-th cycle first heart sound and the right energy subsection point coordinates of i-th cycle second heart sound successively and be saved in right energy subsection array A_RI-th group of data in；

C9) on the i-th periodic signal of short-time zero-crossing rate signal, obtaining between left envelope waypoint and the right envelope waypoint of i-th cycle first heart sound of i-th cycle first heart sound, abscissa is equal to 3 times of Z less than left energy subsection point abscissa and the short-time zero-crossing rate of i-th cycle first heart sound_SThe left zero-crossing rate waypoint of i-th cycle first heart sound, and abscissa more than the right energy subsection point abscissa of i-th cycle first heart sound and short-time zero-crossing rate equal to 3 times of Z_SThe right zero-crossing rate waypoint of i-th cycle first heart sound；Obtaining between left envelope waypoint and the right envelope waypoint of i-th cycle second heart sound of i-th cycle second heart sound, abscissa is equal to 3 times of Z less than left energy subsection point abscissa and the short-time zero-crossing rate of i-th cycle second heart sound_SThe left zero-crossing rate waypoint of i-th cycle second heart sound, and abscissa more than the right energy subsection point abscissa of i-th cycle second heart sound and short-time zero-crossing rate equal to 3 times of Z_SThe right zero-crossing rate waypoint of i-th cycle second heart sound；

Wherein Z_SFor there is no short-time zero-crossing rate during signal fluctuation；

C10) on transverse axis, the left zero-crossing rate waypoint coordinate of the left zero-crossing rate waypoint coordinate of i-th cycle first heart sound and i-th cycle second heart sound is from left to right saved in left zero-crossing rate segmentation array B successively_LI-th group of data in, the right zero-crossing rate waypoint coordinate of the right zero-crossing rate waypoint coordinate of i-th cycle first heart sound and i-th cycle second heart sound is from left to right saved in right zero-crossing rate segmentation array B successively_RI-th group of data in；

C11) process processing all the other periodic signals in n the cycle of signal according to the method for above-mentioned steps c7-c10。

Further, the concretely comprising the following steps of described step d):

D11) according to left envelope segmentation array C_L, right envelope segmentation array C_R, left zero-crossing rate segmentation array B_LWith right zero-crossing rate segmentation array B_RDetermine final waypoint array R, the L of signal envelope, namely

$\begin{array}{cc}R=\frac{C_R+B_R}{2},& L=\frac{C_L+B_L}{2}\end{array};$

Wherein, in array L, each two data are one group of data, successively the left waypoint of the left waypoint of called after i-th cycle first heart sound and i-th cycle second heart sound；In array R, each two data are one group of data, successively the right waypoint of the right waypoint of called after i-th cycle first heart sound and i-th cycle second heart sound；The left waypoint of location i-th cycle first heart sound is i-th cycle first heart sound segment identifier with the interval of the right waypoint of i-th cycle first heart sound, and the left waypoint of location i-th cycle second heart sound is i-th cycle second heart sound segment identifier with the interval of the right waypoint of i-th cycle second heart sound；

D12) local maximum in i-th cycle in process signal envelope is asked for by peak successively algorithm, determine that the maximum being positioned at i-th cycle first heart sound segment identifier is i-th cycle first heart sound eigenvalue, it is determined that the maximum being positioned at i-th cycle second heart sound segment identifier is i-th cycle second heart sound eigenvalue；And abscissa corresponding for these 2 maximum points is saved in i-th group of data of array peak；

D13) split fix is carried out according to the method for above-mentioned steps d11, d12 to processing all the other periodic signals in n the cycle of signal envelope；

D14) in conjunction with cardiechema signals temporal signatures, it is determined that all first heart sound eigenvalues and second heart sound eigenvalue, cardiechema signals feature is extracted。Compared to prior art, present invention have the advantage that

1) present invention adopts viola integrated waveform method to extract cardiechema signals envelope, calculate simple, speed is fast, can effectively extract the characteristic envelope of cardiechema signals, time domain can retain the raw information of cardiechema signals, being particularly suited for the analyzing and processing to the cardiechema signals containing noise and interference, the early diagnosis for heart disease clinically provides, with treatment, the aided analysis method that a kind of cost is low, reliability is high。

2) in conjunction with viola integrated waveform method in the present invention, signal envelope is positioned by short-time energy and zero-crossing rate, improves the effectiveness of signal subsection and the accuracy of eigenvalue。

Accompanying drawing explanation

Fig. 1 is the step block diagram of cardiechema signals characteristic automatic extraction method in embodiment。

Detailed description of the invention

Cardiechema signals characteristic automatic extraction method, as it is shown in figure 1, include following several step:

A), after the cardiechema signals collected being carried out resampling, preprocessed signal X is obtained then through pretreatment_T(k)；

B) utilize viola integrated waveform method, extract preprocessed signal X_TSignal envelope E in (k)_T(m), it may be assumed that

$E_T\left(m\right)=\frac{1}{2L_T+1}\underset{k=m-L_T}{\overset{m+L_T}{\Σ}}{\left(X_T\right(k)-{\stackrel{\‾}{X}}_T(m\left)\right)}^2;$

Wherein, L_TBeing step-length, k is coefficient, m=0,1,2 ..., M, M is preprocessed signal X_TThe length of (k), preprocessed signal X_TK () is discrete signal, its length refers to X_TData amount check in (k)。It is 2 times of L_TPreprocessed signal X in interval_TThe signal average of (k)；

C) signal envelope is carried out segmentation；

D) location obtains first heart sound segment identifier and second heart sound segment identifier, calculates and obtains the first heart sound eigenvalue of first heart sound segment identifier and the second heart sound eigenvalue of second heart sound segment identifier, extracts cardiechema signals feature。

Described step a concretely comprises the following steps:

A1) obtain sampled signal after the described cardiechema signals collected being carried out resampling, with high pass filter and notch filter, sampled signal is filtered obtaining filtering signal, reduces computation complexity。

A2) filtering signal is carried out wavelet multi_resolution analysis denoising, obtain described preprocessed signal X_T(k)。

Described Signal Pretreatment part processes for signal is filtered denoising etc., and less noise disturbs, and improves signal to noise ratio。

Described step b concretely comprises the following steps:

B1) step-length L is obtained by below equation calculating_T:

L_T=0.5*0.1*F_S；

Wherein, F_sFor the sample frequency of resampling in described step a；0.1 is an empirical value, determines according to the duration of first heart sound。The duration of first heart sound is generally 0.1s～0.16s, by suitably changing L_TBig I change signal envelope smoothness, if L_TExcessive, the signature waveform of the excessively smooth loss, particularly abnormal signal that then can cause part useful signal of signal envelope；If L_TToo small, signal envelope is coarse, is unfavorable for signal is carried out segmentation and location, the L that therefore present invention selects_TIt is 0.1。

B2) 2 times of L are asked for_TPreprocessed signal X in interval_TThe signal average of (k)That is:

${\stackrel{\‾}{X}}_T\left(m\right)=\frac{1}{2L_T+1}\underset{k=m-L_T}{\overset{m+L_T}{\Σ}}{X}_T\left(k\right);$

B3) utilize viola integrated waveform method, extract preprocessed signal X_TSignal envelope E in (k)_T(m), it may be assumed that

$E_T\left(m\right)=\frac{1}{2L_T+1}\underset{k=m-L_T}{\overset{m+L_T}{\Σ}}{\left(X_T\right(k)-{\stackrel{\‾}{X}}_T(m\left)\right)}^2.$

Described signal envelope extracts part and adopts viola integrated waveform method to realize the extraction of signal envelope, and envelope is relatively smooth, particularly that the signal effect that signal to noise ratio is relatively low is obvious, works for follow-up split fix and feature extraction and lays the first stone。

Below in conjunction with embodiment, the present invention is described in further detail, but embodiments of the present invention are not limited to this。

Embodiment 1:

Described step c) concretely comprises the following steps:

C1) to signal envelope E_TM () carries out windowing sub-frame processing after, intercept the signal envelope in n smooth cycle for processing signal envelope；Setting threshold line Level=0.01 intercepting and process signal envelope, the method that i-th periodic signal in process n the cycle of signal envelope carries out segmentation is as follows:

C2) threshold line Level=0.01 and the i-th periodic signal processing signal envelope have 4 joinings, on transverse axis, the left envelope waypoint of these 4 joinings from left to right called after i-th cycle first heart sound successively, the right envelope waypoint of i-th cycle first heart sound, the left envelope waypoint of i-th cycle second heart sound, the right envelope waypoint of i-th cycle second heart sound；On transverse axis, these 4 joining coordinates are from left to right saved in i-th group of data of envelope segmentation array C successively；

C3) in envelope segmentation array C, extract the left envelope waypoint coordinate of i-th cycle first heart sound and the left envelope waypoint coordinate of i-th cycle second heart sound successively and be saved in left envelope segmentation array C_LI-th group of data in, extract the right envelope waypoint coordinate of i-th cycle first heart sound and the right envelope waypoint of i-th cycle second heart sound successively and coordinate be saved in right envelope segmentation array C_RI-th group of data in；

C4) segmentation is carried out according to the method for above-mentioned steps c2, c3 to processing all the other periodic signals in n the cycle of signal envelope。

This step is that signal envelope is carried out first split fix。

In the present embodiment, the concretely comprising the following steps of described step d): do following process to processing i-th periodic signal in n the cycle of signal envelope:

D1) left envelope segmentation array C is left in acquisition in_LIn i-th group of data and right envelope segmentation array C_RIn i-th group of data: the left envelope waypoint of i-th cycle first heart sound, the right envelope waypoint of i-th cycle first heart sound, the left envelope waypoint of i-th cycle second heart sound, the right envelope waypoint of i-th cycle second heart sound；The left envelope waypoint of location i-th cycle first heart sound is i-th cycle first heart sound segment identifier with the interval of the right envelope waypoint of i-th cycle first heart sound, and the left envelope waypoint of location i-th cycle second heart sound is i-th cycle second heart sound segment identifier with the interval of the right envelope waypoint of i-th cycle second heart sound；

D2) local maximum in i-th cycle in process signal envelope is asked for by peak successively algorithm, determine that the maximum being positioned at i-th cycle first heart sound segment identifier is i-th cycle first heart sound eigenvalue, it is determined that the maximum being positioned at i-th cycle second heart sound segment identifier is i-th cycle second heart sound eigenvalue；And abscissa corresponding for these 2 maximum points is saved in i-th group of data of array peak；

D3) split fix is carried out according to the method for above-mentioned steps d1, d2 to processing all the other periodic signals in n the cycle of signal envelope；

D4) in conjunction with cardiechema signals temporal signatures, it is determined that all first heart sound eigenvalues and second heart sound eigenvalue, cardiechema signals feature is extracted。

Embodiment 1 adopts viola integrated waveform method to extract cardiechema signals envelope, calculates simple, and speed is fast, can effectively extract the characteristic envelope of cardiechema signals, can retain the raw information of cardiechema signals in time domain。

Embodiment 2:

Step c4 described in embodiment 1) further comprising the steps of below:

C5) preprocessed signal X is obtained_TK time period signal that in (), abscissa scope is identical with processing signal envelope abscissa scope is for processing signal；

C6) ask for the short-time energy signal processing signal and short-time zero-crossing rate signal, then set threshold value M_H, it may be assumed that

$M_H=\underset{0}{\overset{M}{\∫}}{X}_T\left(k\right)dk;$

Use threshold value M_HIntercept short-time energy signal, to short-time energy signal and in n the cycle of short-time zero-crossing rate signal i-th periodic signal be handled as follows:

C7) threshold value M_H4 joinings are had with the i-th periodic signal of short-time energy signal, on transverse axis, the left energy subsection point of these 4 joinings from left to right called after i-th cycle first heart sound successively, the right energy subsection point of i-th cycle first heart sound, the left energy subsection point of i-th cycle second heart sound, the right energy subsection point of i-th cycle second heart sound；On transverse axis, these 4 joining coordinates are from left to right saved in i-th group of data of energy subsection array A successively；

C8) in energy subsection array A, extract the left energy subsection point coordinates of i-th cycle first heart sound and the left energy subsection point coordinates of i-th cycle second heart sound successively and be saved in left energy subsection array A_LI-th group of data in, extract the right energy subsection point coordinates of i-th cycle first heart sound and the right energy subsection point coordinates of i-th cycle second heart sound successively and be saved in right energy subsection array A_RI-th group of data in；

C9) on the i-th periodic signal of short-time zero-crossing rate signal, obtaining between left envelope waypoint and the right envelope waypoint of i-th cycle first heart sound of i-th cycle first heart sound, abscissa is equal to 3 times of Z less than left energy subsection point abscissa and the short-time zero-crossing rate of i-th cycle first heart sound_SThe left zero-crossing rate waypoint of i-th cycle first heart sound, and abscissa more than the right energy subsection point abscissa of i-th cycle first heart sound and short-time zero-crossing rate equal to 3 times of Z_SThe right zero-crossing rate waypoint of i-th cycle first heart sound；Obtaining between left envelope waypoint and the right envelope waypoint of i-th cycle second heart sound of i-th cycle second heart sound, abscissa is equal to 3 times of Z less than left energy subsection point abscissa and the short-time zero-crossing rate of i-th cycle second heart sound_SThe left zero-crossing rate waypoint of i-th cycle second heart sound, and abscissa more than the right energy subsection point abscissa of i-th cycle second heart sound and short-time zero-crossing rate equal to 3 times of Z_SThe right zero-crossing rate waypoint of i-th cycle second heart sound；

Wherein Z_SFor there is no short-time zero-crossing rate during signal fluctuation；

C10) on transverse axis, the left zero-crossing rate waypoint coordinate of the left zero-crossing rate waypoint coordinate of i-th cycle first heart sound and i-th cycle second heart sound is from left to right saved in left zero-crossing rate segmentation array B successively_LI-th group of data in, the right zero-crossing rate waypoint coordinate of the right zero-crossing rate waypoint coordinate of i-th cycle first heart sound and i-th cycle second heart sound is from left to right saved in right zero-crossing rate segmentation array B successively_RI-th group of data in；

C11) process processing all the other periodic signals in n the cycle of signal according to the method for above-mentioned steps c7-c10。

This step is to be accurately positioned in conjunction with short-time energy and short-time zero-crossing rate。

In the present embodiment, the concretely comprising the following steps of described step d):

D11) according to left envelope segmentation array C_L, right envelope segmentation array C_R, left zero-crossing rate segmentation array B_LWith right zero-crossing rate segmentation array B_RDetermine final waypoint array R, the L of signal envelope, namely

$\begin{array}{cc}R=\frac{C_R+B_R}{2},& L=\frac{C_L+B_L}{2}\end{array};$

Wherein, in array L, each two data are one group of data, successively the left waypoint of the left waypoint of called after i-th cycle first heart sound and i-th cycle second heart sound；In array R, each two data are one group of data, successively the right waypoint of the right waypoint of called after i-th cycle first heart sound and i-th cycle second heart sound；The left waypoint of location i-th cycle first heart sound is i-th cycle first heart sound segment identifier with the interval of the right waypoint of i-th cycle first heart sound, and the left waypoint of location i-th cycle second heart sound is i-th cycle second heart sound segment identifier with the interval of the right waypoint of i-th cycle second heart sound；

D12) local maximum in i-th cycle in process signal envelope is asked for by peak successively algorithm, determine that the maximum being positioned at i-th cycle first heart sound segment identifier is i-th cycle first heart sound eigenvalue, it is determined that the maximum being positioned at i-th cycle second heart sound segment identifier is i-th cycle second heart sound eigenvalue；And abscissa corresponding for these 2 maximum points is saved in i-th group of data of array peak；

D13) split fix is carried out according to the method for above-mentioned steps d11, d12 to processing all the other periodic signals in n the cycle of signal envelope；

D14) in conjunction with cardiechema signals temporal signatures, it is determined that all first heart sound eigenvalues and second heart sound eigenvalue, cardiechema signals feature is extracted。

Embodiment 2 is in conjunction with viola integrated waveform method, and signal envelope is positioned by short-time energy and zero-crossing rate, improves the effectiveness of signal subsection and the accuracy of eigenvalue。Being particularly suited for the analyzing and processing to the cardiechema signals containing noise and interference, can improve the end-point detection effect of the low signal of signal to noise ratio, the early diagnosis for heart disease clinically provides, with treatment, the aided analysis method that a kind of cost is low, reliability is high。

Such as two cycles of cardiechema signals are carried out split fix (i.e. n=2), i.e. the 1st cycle of cardiechema signals and the 2nd cycle。

First, step c1-c4 is adopted to obtain the left envelope waypoint C1, the right envelope waypoint C2 of the 1st cycle first heart sound, the left envelope waypoint C3 of the 1st cycle second heart sound, the right envelope waypoint C4 of the 1st cycle second heart sound of the 1st cycle first heart sound；The left envelope waypoint C5 of the 2nd cycle first heart sound, the right envelope waypoint C6 of the 2nd cycle first heart sound, the left envelope waypoint C7 of the 2nd cycle second heart sound, the right envelope waypoint C8 of the 2nd cycle second heart sound；Wherein, the coordinate of C1, C3, C5, C7 is saved in left envelope segmentation array C in order_LIn, C1 and C3 is the 1st group of data, and C5 and C7 is second group of data。The coordinate of C2, C4, C6, C8 is saved in right envelope segmentation array C in order_RIn, C2 and C4 is the 1st group of data, and C6 and C8 is second group of data。

Then step c5-c11 is adopted to obtain the left energy subsection point A1, the right energy subsection point A2 of the 1st cycle first heart sound, the left energy subsection point A3 of the 1st cycle second heart sound, the right energy subsection point A4 of the 1st cycle second heart sound of the 1st cycle first heart sound；The left energy subsection point A5 of the 2nd cycle first heart sound, the right energy subsection point A6 of the 2nd cycle first heart sound, the left energy subsection point A7 of the 2nd cycle second heart sound, the right energy subsection point A8 of the 2nd cycle second heart sound；Wherein, the coordinate of A1, A3, A5, A7 is saved in left energy subsection array A in order_LIn, A1 and A3 is the 1st group of data, and A5 and A7 is second group of data。The coordinate of A2, A4, A6, A8 is saved in right energy subsection array A in order_RIn, A2 and A4 is the 1st group of data, and A6 and A8 is second group of data。

And then obtain the left zero-crossing rate waypoint B1, the right zero-crossing rate waypoint B2 of the 1st cycle first heart sound, the left zero-crossing rate waypoint B3 of the 1st cycle second heart sound, the right zero-crossing rate waypoint B4 of the 1st cycle second heart sound of the 1st cycle first heart sound；The left zero-crossing rate waypoint B5 of the 2nd cycle first heart sound, the right zero-crossing rate waypoint B6 of the 2nd cycle first heart sound, the left zero-crossing rate waypoint B7 of the 2nd cycle second heart sound, the right zero-crossing rate waypoint B8 of the 2nd cycle second heart sound；Wherein, the coordinate of B1, B3, B5, B7 is saved in left zero-crossing rate segmentation array B in order_LIn, B1 and B3 is the 1st group of data, and B5 and B7 is second group of data。The coordinate of B2, B4, B6, B8 is saved in right zero-crossing rate segmentation array B in order_RIn, B2 and B4 is the 1st group of data, and B6 and B8 is second group of data。

By calculatingThe data obtaining array L are followed successively by the left waypoint L1 of the 1st cycle first heart sound, the left waypoint L2 of the 1st cycle second heart sound, the left waypoint L3 of the 2nd cycle first heart sound, the left waypoint L4 of the 2nd cycle second heart sound。The data of array R are followed successively by the right waypoint R1 of the 1st cycle first heart sound, the right waypoint R2 of the 1st cycle second heart sound, the right waypoint R3 of the 2nd cycle first heart sound, the right waypoint R4 of the 2nd cycle second heart sound。L1 and R1 interval, location is the 1st cycle first heart sound segment identifier, and L2 and R2 interval is the 1st cycle second heart sound segment identifier, and L3 and R3 interval is the 2nd cycle first heart sound segment identifier, and L4 and R4 interval is the 2nd cycle second heart sound segment identifier。

Secondly, process signal envelope the 1st, the local maximum in 2 cycles is tried to achieve by peak successively algorithm, determine that the maximum being positioned at the 1st cycle first heart sound segment identifier is the 1st cycle first heart sound eigenvalue S1, the maximum being positioned at the 1st cycle second heart sound segment identifier is the 1st cycle second heart sound eigenvalue S2, and the maximum being positioned at the 2nd cycle first heart sound segment identifier is the 2nd cycle first heart sound eigenvalue S1^/, the maximum being positioned at the 2nd cycle second heart sound segment identifier is the 2nd cycle second heart sound eigenvalue S2^/。

Finally calculate cardiechema signals feature S1/S2, D/S, wherein D/S=(l3-l2)/(l2-l1), l1, l2, l3, l4 respectively put the abscissa of L1, L2, L3, L4, the ratio of S1/S2 and the first heart sound eigenvalue in each cycle and second heart sound eigenvalue, the present embodiment is: for S1/S2 in the period 1, be S1 in second round^//S2^/。

For this, we adopt again in the method for embodiment 2 43 example cardiechema signals as experimental analysis sample, process initially with resampling, high-pass filtering and trap remove in cardiechema signals comprise high frequency and baseline noise etc., then select coif3 small echo that cardiechema signals carries out 6 layers of decomposition and reconstruction, facilitate look at the frequency change of different sub-band cardiechema signals。Processed by Wavelet Denoising Method, eliminate the unwanted contributions in many cardiechema signals and interference, the signal to noise ratio of cardiechema signals increases, viola integrated waveform method is adopted to extract signal envelope the cardiechema signals after denoising, again through setting threshold value, carry out accurate split fix in conjunction with short-time energy and short-time zero-crossing rate, finally adopt local peaking location, and combining the time domain specification according to cardiechema signals so that automatically extracting of cardiechema signals feature is achieved。

Empirical tests, the present invention adopts viola integrated waveform method to extract signal envelope, and to realize automatically obtaining of signal characteristic value in conjunction with the method for short-time energy and short-time zero-crossing rate be a kind of effective method, the especially signal analysis and processing to low signal-to-noise ratio。Signal after Wavelet Denoising Method processes carries out characteristic envelope extraction, decreases amount of calculation, has saved operation time, and capacity of resisting disturbance is strong, and the accuracy of feature is high with reliability。This example adopt the method above-mentioned 43 example cardiechema signals samples carry out the automatic acquisition of feature, and by the inspection of actual specialty stakeholder, to the only 2 unidentified successes of example abnormal signal in this heart sound specimen discerning result。Analyze result show to fail to identify the cause for the success be signal in gatherer process owing to misoperation causes that loss of signal ratio is more serious。

What finally illustrate is, above example is only in order to illustrate technical scheme and unrestricted, although the present invention being described in detail with reference to preferred embodiment, it will be understood by those within the art that, technical scheme can be modified or equivalent replacement, without deviating from objective and the scope of technical solution of the present invention, it all should be encompassed in the middle of scope of the presently claimed invention。

Claims (7)

1. cardiechema signals characteristic automatic extraction method, it is characterised in that include following several step:

A), after the cardiechema signals collected being carried out resampling, preprocessed signal X is obtained then through pretreatment_T(k)；

B) utilize viola integrated waveform method, extract preprocessed signal X_TSignal envelope E in (k)_T(m), it may be assumed that

$E_T\left(m\right)=\frac{1}{2L_T+1}\underset{k=m-L_T}{\overset{m+L_T}{\Σ}}{\left(X_T\right(k)-{\stackrel{\‾}{X}}_T(m\left)\right)}^2;$

Wherein, L_TBeing step-length, k is coefficient, m=0,1,2 ..., M, M is preprocessed signal X_TThe length of (k),It is 2 times of L_TPreprocessed signal X in interval_TThe signal average of (k)；

C) signal envelope is carried out segmentation；

D) location obtains first heart sound segment identifier and second heart sound segment identifier, calculates and obtains the first heart sound eigenvalue of first heart sound segment identifier and the second heart sound eigenvalue of second heart sound segment identifier, extracts cardiechema signals feature。

2. cardiechema signals characteristic automatic extraction method as claimed in claim 1, it is characterised in that described step a concretely comprises the following steps:

A1) obtain sampled signal after the described cardiechema signals collected being carried out resampling, be filtered obtaining filtering signal to sampled signal with high pass filter and notch filter；

A2) filtering signal is carried out wavelet multi_resolution analysis denoising, obtain described preprocessed signal X_T(k)。

3. cardiechema signals characteristic automatic extraction method as claimed in claim 1, it is characterised in that described step b concretely comprises the following steps:

B1) step-length L is obtained by below equation calculating_T:

L_T=0.5*0.1*F_S；

Wherein, F_sFor the sample frequency of resampling in described step a；

B2) 2 times of L are asked for_TPreprocessed signal X in interval_TThe signal average of (k)That is:

${\stackrel{\‾}{X}}_T\left(m\right)=\frac{1}{2L_T+1}\underset{k=m-L_T}{\overset{m+L_T}{\Σ}}{X}_T\left(k\right);$

B3) utilize viola integrated waveform method, extract preprocessed signal X_TSignal envelope E in (k)_T(m), it may be assumed that

$E_T\left(m\right)=\frac{1}{2L_T+1}\underset{k=m-L_T}{\overset{m+L_T}{\Σ}}{\left(X_T\right(k)-{\stackrel{\‾}{X}}_T(m\left)\right)}^2.$

4. cardiechema signals characteristic automatic extraction method as claimed in claim 1, it is characterised in that described step c) concretely comprises the following steps:

C1) to signal envelope E_TM () carries out windowing sub-frame processing after, intercept the signal envelope in n smooth cycle for processing signal envelope；Setting threshold line Level=0.01 intercepting and process signal envelope, the method that i-th periodic signal in process n the cycle of signal envelope carries out segmentation is as follows:

C2) threshold line Level=0.01 and the i-th periodic signal processing signal envelope have 4 joinings, on transverse axis, the left envelope waypoint of these 4 joinings from left to right called after i-th cycle first heart sound successively, the right envelope waypoint of i-th cycle first heart sound, the left envelope waypoint of i-th cycle second heart sound, the right envelope waypoint of i-th cycle second heart sound；On transverse axis, these 4 joining coordinates are from left to right saved in i-th group of data of envelope segmentation array C successively；

C3) in envelope segmentation array C, extract the left envelope waypoint coordinate of i-th cycle first heart sound and the left envelope waypoint coordinate of i-th cycle second heart sound successively and be saved in left envelope segmentation array C_LI-th group of data in, extract the right envelope waypoint coordinate of i-th cycle first heart sound and the right envelope waypoint of i-th cycle second heart sound successively and coordinate be saved in right envelope segmentation array C_RI-th group of data in；

C4) segmentation is carried out according to the method for above-mentioned steps c2, c3 to processing all the other periodic signals in n the cycle of signal envelope。

5. cardiechema signals characteristic automatic extraction method as claimed in claim 4, it is characterised in that described step d) concretely comprises the following steps: do following process to processing i-th periodic signal in n the cycle of signal envelope:

D1) left envelope segmentation array C is left in acquisition in_LIn i-th group of data and right envelope segmentation array C_RIn i-th group of data: the left envelope waypoint of i-th cycle first heart sound, the right envelope waypoint of i-th cycle first heart sound, the left envelope waypoint of i-th cycle second heart sound, the right envelope waypoint of i-th cycle second heart sound；The left envelope waypoint of location i-th cycle first heart sound is i-th cycle first heart sound segment identifier with the interval of the right envelope waypoint of i-th cycle first heart sound, and the left envelope waypoint of location i-th cycle second heart sound is i-th cycle second heart sound segment identifier with the interval of the right envelope waypoint of i-th cycle second heart sound；

D2) local maximum in i-th cycle in process signal envelope is asked for by peak successively algorithm, determine that the maximum being positioned at i-th cycle first heart sound segment identifier is i-th cycle first heart sound eigenvalue, it is determined that the maximum being positioned at i-th cycle second heart sound segment identifier is i-th cycle second heart sound eigenvalue；And abscissa corresponding for these 2 maximum points is saved in i-th group of data of array peak；

D3) split fix is carried out according to the method for above-mentioned steps d1, d2 to processing all the other periodic signals in n the cycle of signal envelope；

D4) in conjunction with cardiechema signals temporal signatures, it is determined that all first heart sound eigenvalues and second heart sound eigenvalue, cardiechema signals feature is extracted。

6. cardiechema signals characteristic automatic extraction method as claimed in claim 4, it is characterised in that described step c4) further comprising the steps of below:

C5) preprocessed signal X is obtained_TK time period signal that in (), abscissa scope is identical with processing signal envelope abscissa scope is for processing signal；

C6) ask for the short-time energy signal processing signal and short-time zero-crossing rate signal, then set threshold value M_H, it may be assumed that

$M_H=\underset{0}{\overset{M}{\∫}}{X}_T\left(k\right)dk;$

Use threshold value M_HIntercept short-time energy signal, to short-time energy signal and in n the cycle of short-time zero-crossing rate signal i-th periodic signal be handled as follows:

C7) threshold value M_H4 joinings are had with the i-th periodic signal of short-time energy signal, on transverse axis, the left energy subsection point of these 4 joinings from left to right called after i-th cycle first heart sound successively, the right energy subsection point of i-th cycle first heart sound, the left energy subsection point of i-th cycle second heart sound, the right energy subsection point of i-th cycle second heart sound；On transverse axis, these 4 joining coordinates are from left to right saved in i-th group of data of energy subsection array A successively；

C8) in energy subsection array A, extract the left energy subsection point coordinates of i-th cycle first heart sound and the left energy subsection point coordinates of i-th cycle second heart sound successively and be saved in left energy subsection array A_LI-th group of data in, extract the right energy subsection point coordinates of i-th cycle first heart sound and the right energy subsection point coordinates of i-th cycle second heart sound successively and be saved in right energy subsection array A_RI-th group of data in；

C9) on the i-th periodic signal of short-time zero-crossing rate signal, obtaining between left envelope waypoint and the right envelope waypoint of i-th cycle first heart sound of i-th cycle first heart sound, abscissa is equal to 3 times of Z less than left energy subsection point abscissa and the short-time zero-crossing rate of i-th cycle first heart sound_SThe left zero-crossing rate waypoint of i-th cycle first heart sound, and abscissa more than the right energy subsection point abscissa of i-th cycle first heart sound and short-time zero-crossing rate equal to 3 times of Z_SThe right zero-crossing rate waypoint of i-th cycle first heart sound；Obtaining between left envelope waypoint and the right envelope waypoint of i-th cycle second heart sound of i-th cycle second heart sound, abscissa is equal to 3 times of Z less than left energy subsection point abscissa and the short-time zero-crossing rate of i-th cycle second heart sound_SThe left zero-crossing rate waypoint of i-th cycle second heart sound, and abscissa more than the right energy subsection point abscissa of i-th cycle second heart sound and short-time zero-crossing rate equal to 3 times of Z_SThe right zero-crossing rate waypoint of i-th cycle second heart sound；

Wherein Z_SFor there is no short-time zero-crossing rate during signal fluctuation；

C10) on transverse axis, the left zero-crossing rate waypoint coordinate of the left zero-crossing rate waypoint coordinate of i-th cycle first heart sound and i-th cycle second heart sound is from left to right saved in left zero-crossing rate segmentation array B successively_LI-th group of data in, the right zero-crossing rate waypoint coordinate of the right zero-crossing rate waypoint coordinate of i-th cycle first heart sound and i-th cycle second heart sound is from left to right saved in right zero-crossing rate segmentation array B successively_RI-th group of data in；

C11) process processing all the other periodic signals in n the cycle of signal according to the method for above-mentioned steps c7-c10。

7. cardiechema signals characteristic automatic extraction method as claimed in claim 6, it is characterised in that described step d) concretely comprises the following steps:

D11) according to left envelope segmentation array C_L, right envelope segmentation array C_R, left zero-crossing rate segmentation array B_LWith right zero-crossing rate segmentation array B_RDetermine final waypoint array R, the L of signal envelope, namely

$R=\frac{C_R+B_R}{2},L=\frac{C_L+B_L}{2};$

Wherein, in array L, each two data are one group of data, successively the left waypoint of the left waypoint of called after i-th cycle first heart sound and i-th cycle second heart sound；In array R, each two data are one group of data, successively the right waypoint of the right waypoint of called after i-th cycle first heart sound and i-th cycle second heart sound；The left waypoint of location i-th cycle first heart sound is i-th cycle first heart sound segment identifier with the interval of the right waypoint of i-th cycle first heart sound, and the left waypoint of location i-th cycle second heart sound is i-th cycle second heart sound segment identifier with the interval of the right waypoint of i-th cycle second heart sound；

D12) local maximum in i-th cycle in process signal envelope is asked for by peak successively algorithm, determine that the maximum being positioned at i-th cycle first heart sound segment identifier is i-th cycle first heart sound eigenvalue, it is determined that the maximum being positioned at i-th cycle second heart sound segment identifier is i-th cycle second heart sound eigenvalue；And abscissa corresponding for these 2 maximum points is saved in i-th group of data of array peak；

D13) split fix is carried out according to the method for above-mentioned steps d11, d12 to processing all the other periodic signals in n the cycle of signal envelope；

D14) in conjunction with cardiechema signals temporal signatures, it is determined that all first heart sound eigenvalues and second heart sound eigenvalue, cardiechema signals feature is extracted。