CN108392220A - A method of obtaining cardiechema signals derived components - Google Patents
A method of obtaining cardiechema signals derived components Download PDFInfo
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- CN108392220A CN108392220A CN201810101338.4A CN201810101338A CN108392220A CN 108392220 A CN108392220 A CN 108392220A CN 201810101338 A CN201810101338 A CN 201810101338A CN 108392220 A CN108392220 A CN 108392220A
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- A61B7/02—Stethoscopes
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Abstract
The invention discloses a kind of methods obtaining cardiechema signals derived components, have the characteristic of " timesharing generation " according to cardiechema signals, first to carrying out denoising and segment processing by the roads multichannel synchronousing collection N cardiechema signals；Then mathematical model of the structure cardiechema signals in thoracic cavity transmittance process；Cardiechema signals derived components are obtained based on fourth-order cumulant quantity algorithm.Using the present invention can obtain not only include cardiechema signals physiologic information, it can also include the location information that heart sound generates, and the information of the correlation between each channel signal, the characteristics of being occurred using cardiechema signals timesharing, first heart sound S1 is resolved into 4 derived components to state, second heart sound S2, which resolves into 2 derived components, to be stated, successfully obtain the more single cardiechema signals derived components of ingredient, be conducive to analyse in depth cardiechema signals, explained and classified, and final application is to clinical practice and further scientific research.
Description
Technical field
The present invention relates to a kind of method obtaining cardiechema signals derived components, more particularly to a kind of four-ways using synchronous acquisition
Road heart sound obtains the acquisition methods of cardiechema signals derived components.
Background technology
Cardiechema signals carry the important physiologic information of human heart activity, such as heart rate, the rhythm of the heart, atrium, ventricle and heart
The movement of valve and functional status etc..With the development of science and technology cardiophony starts to turn to intelligent heart sound by traditional cardiophony
Cardiechema signals are converted to electric signal to handle, from the angle of " signal " by auscultation, so-called heart sound intelligence auscultation using electronic equipment
It spends to obtain and further analyze the various features of cardiechema signals, to achieve the purpose that auscultation.Cardiechema signals have high
Medical value, the cardiechema signals of acquisition should retain all information of heart sound as much as possible, and distortion is the smaller the better.In fact,
The cardiechema signals that body surface is acquired not are which corresponding original heart sound ingredient of heart, but the mixing of heart sound various composition
Object, heart sound experienced a complicated communication process from generating and reaching body surface.The primitive component for obtaining heart sound will be one non-
Often significant work, is advantageous in that the various information that effectively, nondestructively can include heart, is the positioning of heart sound occurring source
Important foundation.
It is few about the acquisition of cardiechema signals primitive component research both at home and abroad, but two classes can be divided into：First, by miniature biography
Sensor is inserted directly into endocardial to acquire heart sound, and this method difficulty for obtaining heart sound is high, risk is big, thus only from animal body
On obtain the primitive component of heart sound；Second is that using the method for blind source separating, that is, independent component analysis come obtain heart sound it is original at
Point, but the part primitive component of heart sound can only be obtained.It would therefore be desirable to a kind of acquisition methods are simple, risk is small and obtain
The distortionless cardiechema signals derived components acquisition methods of cardiechema signals.
Invention content
Goal of the invention：The present invention proposes that a kind of using synchronous acquisition multichannel heart sound to obtain ingredient single, undistorted
Cardiechema signals derived components method.
Technical solution：The method of the present invention for obtaining cardiechema signals derived components, includes the following steps：
(1) pass through the roads multichannel synchronousing collection n cardiechema signals；
(2) denoising and segment processing are carried out to the roads n cardiechema signals；
(3) mathematical model of the structure cardiechema signals in thoracic cavity transmittance process；
(4) it is based on fourth-order cumulant quantity algorithm and obtains cardiechema signals derived components.
The roads n cardiechema signals described in step (1) include mainly aorta petal cardiechema signals, pulmonary valve cardiechema signals, two
Cusp cardiechema signals, tricuspid valve cardiechema signals.
Segment processing described in step (2) is broadly divided into heart sound S1With heart sound S2Two sections.Interim heart sound S1It is divided into myocardium receipts
Contracting, heart valve are closed, blood hits ventricle wall and blood hits 4 derived components of main artery wall；Heart sound S2It is divided into aorta petal
It closes and pulmonary valve closes 2 derived components.
Mathematical model described in step (3) is obtained by following formula：
Wherein, aijFor aliased coefficient of the heart sound in the transmittance process of thoracic cavity, wijFor heart sound thoracic cavity biography
Echo coefficient during passing；
Being write as matrix form is：
Y=AX+WY
I.e.：
Y=(I-W)-1AX=BX
Wherein, B=(I-W)-1。
The step (4) includes the following steps：
(41) observation signal Y is subjected to spheroidising, calculates sphering matrix W：
Enable C=YYT=U Λ UT, C is the covariance matrix of Y, is had：
Wherein, sphering matrix
(43) four-dimension for calculating Z adds up moment matrix QZ(M)：
If M is arbitrary 4 × 4 matrix, then：
(44) " mixing-nodularization " matrix is sought：
V=WB is enabled, then is had：
VVT=VTV=I4
Wherein V=[v1,v2,v3,v4], vm=[vm1,vm2,vm3,vm4]T,
Then have：
Qz(M)=λ M
I.e.：
[Qz(M)]ij=λ Mij
λ=k in formula4(xm) be heart sound derived components kurtosis, M is known as Qz(M) eigenmatrix
Qz(M) it is diagonal matrix, that is, meets：
Qij=Qji
And
Qz(m)=k4(xm)M
(44) estimated matrix is solved, the derived components of cardiechema signals are obtained：
With V gusts to Qz(M) diagonal matrix Λ (M) will be obtained by making quadratic form processing, then can be in the hope of the estimated matrix of matrix B
I.e.：
Then estimating system C is:
Then：
Advantageous effect：Compared with prior art, beneficial effects of the present invention：1, compared with previous single channel heart sound acquires
Compared with the cardiechema signals obtained using multi-channel synchronous are had a clear superiority, and are included not only the physiologic information of cardiechema signals, also may be used
With the information of the correlation between the location information generated comprising heart sound and each channel signal；2, it is with heart sound sounding feature
First heart sound S1 the characteristics of generation using cardiechema signals timesharing, is resolved into 4 sources by starting point in conjunction with the model that heart sound is propagated
Ingredient is stated, and second heart sound S2, which resolves into 2 derived components, to be stated, and the more single cardiechema signals source of ingredient is successfully obtained
Ingredient is conducive to analyse in depth cardiechema signals, explained and classified, and final application is to clinical practice and further section
Learn research.
Description of the drawings
Fig. 1 is the generation process of first heart sound S1 and second heart sound S2；
Fig. 2 is " timesharing generation " schematic diagram of cardiechema signals；
Fig. 3 is cardiechema signals communication process schematic diagram.
Specific implementation mode
Invention is further described in detail below in conjunction with the accompanying drawings：
Heart sound is a kind of voice signal generated when heart valve and associated vasculature mechanical oscillation.Cardiechema signals are main
Including first heart sound S1 and second heart sound S2, first heart sound S1 generates the systole phase for starting from ventricle, mainly because of the pass of atrioventricular valve
It closes and generates.
As shown in Figure 1, S1 is mainly made of four parts, the first time that first part results from ventricle shrinks, blood adds
The process in flow speed and direction atrium is happened at before atrioventricular valve closing；Second part is hit as caused by bloodstream invasion to atrioventricular valve
It hits and when blood rinse-back to ventricle is produced；Part III is between the bottom and ventricle wall of main artery (pulmonary artery)
Vibration caused by blood flow；Part IV vibrates caused by mainly causing turbulent flow when blood is projected by aorta.
Second heart sound S2 results from the end of ventricular contraction to the incipient stage of auricular diastole, mainly by aorta petal and pulmonary valve
It closes and generates, S2 mainly consists of two parts, first, by the part A generated when aortic valve closing, second is that being closed by pulmonary valve
The portion P composition generated when closing.
According to the generation principle of heart sound, we are it can be found that the generation of cardiechema signals derived components has apparent " timesharing production
It is raw " feature, for first heart sound S1, always " 1 → 2 → 3 → 4 → 1 ... " is as shown in Figure 2 for the generation process of S1.Similarly,
The generation process of two heart sound S2 is also the result that the cycle of its derived components generates：" A → P → A → P → A ... " is shown apparent
" timesharing generation " feature.
There is the characteristics of aliasing, feedback (echo) and timesharing according to communication process of the cardiechema signals in thoracic cavity, establishes such as Fig. 3
Mathematical model：
If heart sound is X (t)=[x1(t),x2(t),…,xn(t)]T, xi(t) derived components of heart sound are represented, body surface detection arrives
Cardiechema signals be Y (t)=[y1(t),y2(t),…,yn(t)]T, yi(t) cardiechema signals all the way are represented.
Have in the case that on the roads n, cardiechema signals have been removed ambient noise：
y1=a11x1+a12x2+…+a1nxn
+w11y1+w12y2+…+w1nyn
y2=a21x1+a22x2+…+a2nxn+
w21y1+w22y2+…+w2nyn
yn=an1x1+an2x2+…+annxn+
wn1y1+wn2y2+…+wnnyn
I.e.：
Being write as matrix form is：
Y=AX+WY
I.e.：
Y=(I-W)-1AX=BX
Wherein, B=(I-W)-1。
Y is known acquisition signal, and matrix B and X are all unknown, it is assumed that the derived components x of cardiechema signalsi(t) three ranks, quadravalence
Cumulant exists, xi(t) stationary random process subject to, and mutual statistical is independent.If
For the primitive component matrix of cardiechema signals, if its each component is mutual indepedent,As heart sound source at
Point, therefore, and if only if there is a Matrix C, per a line and each one and only one element of row for nonzero element when, it is right
Matrix Y is done such as down conversion：CY can then obtain derived components, i.e.,：
Cardiechema signals are a kind of typical biomedicine signals, have non-linear, non-stationary, non-gaussian, uncertainty etc.
Inherent feature, higher order statistic analysis can provide characteristic information amount in the certain applications of signal processing, have certain advantage；
Furthermore being generated by heart sound described previously herein has " timesharing " feature, therefore, cardiechema signals derived components
Must mutual statistical it is independent, have n=4 to four-way cardiechema signals.Therefore, the heart sound source based on fourth order cumulant is devised herein
Ingredient acquisition algorithm, algorithm are as follows：
(1) sphering matrix W is calculated, observation signal Y is subjected to spheroidising
Enable C=YYT=U Λ UT, C is referred to as the covariance matrix of Y, is had：
Wherein sphering matrixBy spheroidising, the second order correlation between original each channel data is eliminated,
So that further analysis can concentrate on signal on high-order statistic.
(2) fourth order cumulant is calculated
If M is arbitrary 4 × 4 matrix, then the four-dimension of Z adds up moment matrix QZ(M) it is defined as follows：
(3) " mixing --- nodularization " matrix is sought
V=WB is enabled, then is had：
VVT=VTV=I4
Wherein V=[v1,v2,v3,v4], vm=[vm1,vm2,vm3,vm4]T, M=vmvm T
Then have：
Qz(M)=λ M
I.e.：
[Qz(M)]ij=λ Mij
λ=k in formula4(xm) be heart sound derived components kurtosis, M is known as Qz(M) eigenmatrix, by four-dimensional cumulative amount above
Matrix Qz(M) definition is it is found that Qz(M) it is diagonal matrix, that is, meets：
Qij=Qji
And
Qz(m)=k4(xm)M
(4) estimated matrix is solved, the primitive component of cardiechema signals is obtained
Theoretical, the cumulative amount battle array Q constituted as weight using M by the feature decomposition of matrixz(M) V Λ (M) V must be decomposed intoT's
Form：
This formula explanation：With V gusts to Qz(M) diagonal matrix Λ (M) will be obtained by making quadratic form processing, then can be in the hope of matrix B
Estimated matrixI.e.：
Then estimating system C is:
Then：
To can get the derived components of cardiechema signals.
Claims (7)
1. a kind of method obtaining cardiechema signals derived components, which is characterized in that include the following steps：
(1) pass through the roads multichannel synchronousing collection n cardiechema signals；
(2) denoising and segment processing are carried out to the roads n cardiechema signals；
(3) mathematical model of the structure cardiechema signals in thoracic cavity transmittance process；
(4) it is based on fourth-order cumulant quantity algorithm and obtains cardiechema signals derived components.
2. the method according to claim 1 for obtaining cardiechema signals derived components, which is characterized in that the roads n described in step (1)
Cardiechema signals include mainly aorta petal cardiechema signals, pulmonary valve cardiechema signals, bicuspid valve cardiechema signals, tricuspid valve heart sound letter
Number.
3. the method according to claim 1 for obtaining cardiechema signals derived components, which is characterized in that point described in step (2)
Section processing is broadly divided into heart sound S1With heart sound S2Two sections.
4. the method according to claim 3 for obtaining cardiechema signals derived components, which is characterized in that the heart sound S1It is divided into the heart
Flesh is shunk, heart valve is closed, blood hits ventricle wall and blood hits 4 derived components of main artery wall.
5. the method according to claim 3 for obtaining cardiechema signals derived components, which is characterized in that the heart sound S2It is divided into master
Arterial valve is closed and pulmonary valve closes 2 derived components.
6. the method according to claim 1 for obtaining cardiechema signals derived components, which is characterized in that the number described in step (3)
Model is learned to be obtained by following formula：
Wherein, aijFor aliased coefficient of the heart sound in the transmittance process of thoracic cavity, wijFor heart sound thoracic cavity transmission
Echo coefficient in journey；
Being write as matrix form is：
Y=AX+WY
I.e.：
Y=(I-W)-1AX=BX
Wherein, B=(I-W)-1。
7. the method according to claim 1 for obtaining cardiechema signals derived components, which is characterized in that the step (4) includes
Following steps：
(41) observation signal Y is subjected to spheroidising, calculates sphering matrix W：
Enable C=YYT=U Λ UT, C is the covariance matrix of Y, is had：
Wherein, sphering matrix
(42) four-dimension for calculating Z adds up moment matrix QZ(M)：
If M is arbitrary 4 × 4 matrix, then：
(43) " mixing-nodularization " matrix is sought：
V=WB is enabled, then is had：
VVT=VTV=I4
Wherein V=[v1,v2,v3,v4], vm=[vm1,vm2,vm3,vm4]T,
Then have：
Qz(M)=λ M
I.e.：
[Qz(M)]ij=λ Mij
λ=k in formula4(xm) be heart sound derived components kurtosis, M is known as Qz(M) eigenmatrix
Qz(M) it is diagonal matrix, that is, meets：
Qij=Qji
And
Qz(m)=k4(xm)M
(44) estimated matrix is solved, the derived components of cardiechema signals are obtained：
With V gusts to Qz(M) diagonal matrix Λ (M) will be obtained by making quadratic form processing, then can be in the hope of the estimated matrix of matrix BI.e.：
Then estimating system C is:
Then：
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| CN109793533A (en) * | 2019-01-04 | 2019-05-24 | 东南大学 | A kind of Simple electronic stethoscope |
| CN110010145A (en) * | 2019-02-28 | 2019-07-12 | 广东工业大学 | A method of eliminating electronic auscultation device grating |
| CN112336369A (en) * | 2020-11-30 | 2021-02-09 | 山东大学 | Coronary heart disease risk index evaluation system of multichannel heart sound signals |
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Application publication date: 20180814 |