CN103876730B - Blind extraction method for electrocatdiogram of mother and electrocardiogram of fetus based on second-order statistical properties - Google Patents

Abstract

The invention discloses a blind extraction method for an electrocardiogram of a mother and an electrocardiogram of a fetus based on second-order statistical properties. The problems that mixed signals with a small signal to noise ratio cannot be extracted well, and the extraction process works in an offline mode are solved. The method comprises the steps that (1) electrophysiological mixed signals are acquired, (2) preprocessing is carried out; (3) one path of mixed signal with a large signal to noise ratio is selected out; (4) a period is estimated; (5) an optimal electrocardiosignal vector quantity is obtained; (6) the electrocardiosignals are extracted. Compared with a mother and fetus electrocardiosignal extraction method in the prior art, the precision of the extracted signals is guaranteed, meanwhile, the method has the advantages of achieving real-time online extraction and being high in extraction efficiency, and the method can be used for extracting the electrocardiosignals of the mother and the fetus from the parent body electrocardiosignals collected by an electrocardiogram monitoring machine.

Description

Based on mother and the Fetal ECG Blind extracting method of second-order statistics

Technical field

The present invention relates to signal processing technology field, further relate to a kind of mother based on second-order statistics in processing of biomedical signals technical field and Fetal ECG signal Blind extracting method.The present invention can be used for extracting mother and Fetal ECG signal in the parent electrocardiosignal collected from cardioelectric monitor machine.

Background technology

Human body electrocardio figure (ECG) is an objective indicator of reflection human physiological activity.The signal of telecommunication obtained from anemia of pregnant woman's body surface measurement generally comprises mother's electrocardio (MECG), the mixed signal of Fetal ECG (FECG) and other signals of telecommunication of human body (such as electromyographic signal EMG etc.) and observation background noise.In the anemia of pregnant woman's body surface measurement signal of telecommunication obtained, because mother's electrocardiosignal common intensity is comparatively large, adopt conventional filtering technique just can extract mother's electrocardiosignal.And Fetal ECG signal is quite faint, its intensity is not as good as 1/10th of mother's electrocardiosignal, and the frequency spectrum of Fetal ECG signal and mother's electrocardiosignal is overlapped, and therefore general filtering technique is difficult to extract steady and audible Fetal ECG signal.

The patented technology " a kind of Fetal ECG Blind extracting method based on time-frequency conversion " (number of patent application: 201110144487.7 authorizes publication No. CN 102160787B) that Guangdong University of Technology has discloses a kind of Fetal ECG Blind extracting method based on time-frequency conversion.The method collection obtains the mixed signal comprising mother and fetus electricity physiological signal, select the sparse time period relative to Fetal ECG signal of mother in mixed signal, ambiguity function is utilized to transform in time-frequency domain by the relatively sparse time period obtained, recycling broad sense Rayleigh entropy structure contrast function, thus extract Fetal ECG signal.This patented technology utilizes mother's sparse characteristic relative to Fetal ECG mixed signal time domain, solve mother's problem of being difficult to be separated overlapped with Fetal ECG signal spectrum, but the deficiency still existed is, the method is operated in offline mode, cannot reflect the time-varying characteristics of Fetal ECG signal.

The patent application " based on generalized eigenvalue maximized Fetal ECG signal adaptive Blind extracting method " (number of patent application: 201310729736.8, publication No. CN 103627796A) that Shanghai Maritime University proposes discloses a kind of Fetal ECG signal adaptive Blind extracting method.The method collection obtains the mixed signal comprising mother and fetus electricity physiological signal, based on self adaptation real time algorithm, calculate interior eigenvalue and the characteristic vector obtaining mixed signal difference and postpone covariance matrix of periodic regime of setting, and select eigenvalue of maximum characteristic of correspondence vector for blind separation vector, thus extract Fetal ECG signal.Although the method utilizes the second-order statistics of signal, simplify computation complexity, improve the efficiency of Fetal ECG blind signal separation, but the deficiency still existed is, the method is accurate not to the phase estimate of electrocardiosignal, and due to the diagonalizable of the parent being too dependent on collection delay covariance matrix different from Fetal ECG mixed signal, cause for the smaller collection mixed signal of noise, extraction effect is not good.

Summary of the invention

The object of the invention is to overcome above-mentioned existing methodical deficiency, propose a kind of method of the electrocardiosignal Blind extracting based on second-order statistics, achieve the self adaptation extract real-time of mother and Fetal ECG signal.

Realizing basic thought of the present invention is first to the Multi-path electricity physiology mixed signal pretreatment obtained, the maximum road mixed signal of signal to noise ratio is selected again from the Multi-path electricity physiology mixed signal obtained, then the cycle of this road mixed signal is estimated, from this road mixed signal, extract optimum separating vector, the optimum separating vector of final utilization extracts electrocardiosignal from pretreated mixed signal.

Concrete steps of the present invention are as follows:

(1) electro physiology mixed signal is obtained:

Obtain parent chest and the abdominal part Multi-path electricity physiology mixed signal of synchronous acquisition;

(2) pretreatment:

(2a) use limited long wave digital lowpass filter, myoelectricity interference and noise filtering are carried out to Multi-path electricity physiology mixed signal, obtain the Multi-path electricity physiology mixed signal after the interference of filtering myoelectricity and noise;

(2b) use limited long digital trap, the filtering of 50Hz Hz noise is carried out to the Multi-path electricity physiology mixed signal after myoelectricity interference and noise filtering, obtains pretreated Multi-path electricity physiology mixed signal;

(3) signal to noise ratio of every road electro physiology mixed signal is obtained:

(3a) using in the electro physiology mixed signal of pretreatment Hou Mei road, mother's electrocardiosignal is as signal, and Fetal ECG signal, as noise, obtains the signal to noise ratio of mother's electrocardiosignal and Fetal ECG signal;

(3b) using in the electro physiology mixed signal of pretreatment Hou Mei road, Fetal ECG signal is as signal, and mother's electrocardiosignal, as noise, obtains the signal to noise ratio of Fetal ECG signal and mother's electrocardiosignal;

(4) cycle estimator:

(4a) select mother's electrocardiosignal and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise, by the interval of wherein adjacent two R ripples of mother's electrocardiosignal, estimate evaluation as mother's electrocardiosignal cycle;

(4b) adopt autocorrelation coefficient formula, calculate the autocorrelation coefficient of mother's electrocardiosignal and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise;

(4c) evaluation of estimating in mother's electrocardiosignal cycle is fluctuated error 0.2 second as section search time, the maximum of the absolute value of search autocorrelation coefficient, gets the fine estimation of moment as mother's electrocardiosignal cycle of maximum using the absolute value of autocorrelation coefficient;

(4d) select Fetal ECG signal and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio, by the interval of wherein adjacent two R ripples of Fetal ECG signal, estimate evaluation as the Fetal ECG signal period;

(4e) adopt autocorrelation coefficient formula, calculate the autocorrelation coefficient of Fetal ECG signal and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio;

(4f) evaluation of estimating of Fetal ECG signal period is fluctuated error 0.15 second as section search time, the maximum of the absolute value of search autocorrelation coefficient, gets the fine estimation of moment as the Fetal ECG signal period of maximum using the absolute value of autocorrelation coefficient;

(5) optimum electrocardiosignal vector is obtained:

(5a) adopt steepest descending method, obtain optimum mother's electrocardiosignal vector;

(5b) adopt correction Newton method, obtain optimum Fetal ECG signal vector;

(6) electrocardiosignal is extracted:

(6a) adopt projecting method, use optimum mother's electrocardiosignal vector to extract mother's electrocardiosignal from pretreated Multi-path electricity physiology mixed signal;

(6b) adopt projecting method, use optimum Fetal ECG signal vector to extract Fetal ECG signal from pretreated Multi-path electricity physiology mixed signal.

The present invention compared with prior art tool has the following advantages:

First, because the present invention is by first carrying out pretreatment to the Multi-path electricity physiology mixed signal obtained, mother and Fetal ECG signal optimal vector is obtained again from pretreated electro physiology mixed signal, overcoming prior art can not the deficiency of better extract mother and Fetal ECG signal to the smaller electro physiology mixed signal of noise, makes the present invention without the need to the additional conditions of electro physiology mixed signal signal to noise ratio size.

Second, because the present invention obtains optimum mother and Fetal ECG signal vector by the second-order statistics of electro physiology mixed signal, overcome the deficiency that prior art is operated in offline mode, the real-time online achieving mother and Fetal ECG signal extracts, make the efficiency extracting mother and Fetal ECG signal high, better can reflect the time-varying characteristics of mother and Fetal ECG signal.

3rd, because the present invention is by first carrying out pre-estimation to the cycle of mother and Fetal ECG signal in the maximum electro physiology mixed signal of signal to noise ratio, step-up error is accurately estimated again, overcoming prior art estimates accurate not enough to mother and Fetal ECG signal period, make the extraction effect of the present invention to mother and Fetal ECG signal better.

Accompanying drawing explanation

Fig. 1 is flow chart of the present invention;

Fig. 2 is the 8 road electro physiology mixed waveform signal figure that the present invention inputs;

Fig. 3 is the autocorrelation coefficient schematic diagram of the 1st road signal adopting the present invention to get;

Fig. 4 is the autocorrelation coefficient schematic diagram of the 8th road signal adopting the present invention to get;

Fig. 5 adopts four kinds of methods of the present invention and prior art to extract parent electro-cardiologic signal waveforms comparison diagram;

Fig. 6 adopts four kinds of methods of the present invention and prior art to extract Fetal ECG signal waveform comparison diagram.

Detailed description of the invention

Below in conjunction with accompanying drawing, the present invention will be further described:

With reference to Fig. 1, specific embodiment of the invention step is as follows:

Step 1, input electro physiology mixed signal.

Embodiments of the invention are input 8 road electro physiology mixed signals, the 5 road electro physiology mixed signals of this electro physiology mixed signal synchronous acquisition from parent chest and 3 road electro physiology mixed signals of parent abdominal part.Have input 8 road electro physiology mixed waveform signal figure with reference to shown in accompanying drawing 2, abscissa representing time in Fig. 2, vertical coordinate represents signal amplitude, Fig. 2 (a), (b), (c), (d), (e) gather the 5 road electro physiology mixed signals from parent chest, and Fig. 2 (f), (g), (h) gather the 3 road electro physiology mixed signals from parent abdominal part.As seen from Figure 2, from 5 road electro physiology mixed signals mainly mother's electrocardiosignal of chest, and faint Fetal ECG signal is had from 3 road electro physiology mixed signals of abdominal part.

Step 2, pretreatment.

The first step, adopts the 8 limited long wave digital lowpass filters in rank based on Hamming window, carries out myoelectricity interference and noise filtering to the multichannel mixed signal got, and obtains the multichannel mixed signal after the interference of filtering myoelectricity and noise;

Second step, adopts the 40 limited long digital traps in rank based on Hamming window, carries out the filtering of 50Hz Hz noise, obtain pretreated multichannel mixed signal to the multichannel mixed signal after myoelectricity interference and noise filtering.

Step 3, obtains the signal to noise ratio of every road electro physiology mixed signal.

The first step, using in the electro physiology mixed signal of pretreatment Hou Mei road, mother's electrocardiosignal is as signal, and Fetal ECG signal, as noise, obtains the signal to noise ratio of mother's electrocardiosignal and Fetal ECG signal;

Second step, using in the electro physiology mixed signal of pretreatment Hou Mei road, Fetal ECG signal is as signal, and mother's electrocardiosignal, as noise, obtains the signal to noise ratio of Fetal ECG signal and mother's electrocardiosignal.

Step 4, cycle estimator.

Estimate mother's electrocardiosignal period alpha, concrete steps comprise:

The first step, mother's electrocardiosignal and the maximum road mixed signal of Fetal ECG Signal-to-Noise is selected from pretreated multichannel mixed signal, this mixed signal of t is designated as x (t), the interval of adjacent two the R ripples of mother's electrocardiosignal in x (t) is estimated evaluation as mother's electrocardiosignal cycle.What from x (t), obtain mother's electrocardiosignal cycle estimates evaluation α ₀=0.8 second;

Second step, the autocorrelation coefficient computing formula of x (t) is as follows:

$r\left(\mathrm{\δ}\right)=\frac{{\∫}_{t}x\left(t\right)x(t-\mathrm{\δ})\mathrm{dt}}{{\∫}_t{x}^2\left(t\right)\mathrm{dt}}$

Wherein, the autocorrelation coefficient of mother's electrocardiosignal when r (δ) represents that time delay is δ and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise, δ represents the time delay of the relative t of a road electro physiology mixed signal that mother's electrocardiosignal and Fetal ECG Signal-to-Noise are maximum, x (t) represents mother's electrocardiosignal and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise, t represents the sampling instant of mother's electrocardiosignal and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise, ∫ () dt represents the integration operation to sampling instant t, [] ²represent squared operation,

3rd step, at α ₀-0.2≤δ≤α ₀in+0.2 time range, the maximum occurrences moment of search r (δ) is α=0.74 second, then α is the fine estimation in mother's electrocardiosignal cycle.

Estimate Fetal ECG signal period β, concrete steps comprise:

The first step, selects Fetal ECG signal and the maximum road mixed signal of mother's electrocardiosignal signal to noise ratio, this mixed signal of t is designated as y (t) from pretreated multichannel mixed signal.The interval of adjacent two the R ripples of Fetal ECG signal in y (t) is estimated evaluation as the Fetal ECG signal period.From y (t), roughly estimate Fetal ECG signal R wave period is β ₀=0.5 second;

Second step, calculates the auto-correlation function of y (t)

$f\left(\mathrm{\ϵ}\right)=\frac{{\∫}_{t}y\left(t\right)y(t-\mathrm{\ϵ})\mathrm{dt}}{{\∫}_t{y}^2\left(t\right)\mathrm{dt}}$

Wherein, the autocorrelation coefficient of Fetal ECG signal when f (ε) represents that time delay is ε and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio, ε represents the time delay of the relative t of a road electro physiology mixed signal that Fetal ECG signal and mother's electrocardiosignal signal to noise ratio are maximum, y (n) represents Fetal ECG signal and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio, n represents the sampling instant of Fetal ECG signal and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio, ∫ () dn represents the integration operation to sampling instant n, [] ²represent squared operation,

3rd step, at β ₀-0.15≤ε≤β ₀in+0.15 time range, the maximum occurrences moment of search f (ε) is β=0.448 second, then β is the fine estimation of Fetal ECG signal period.

Step 5, obtains optimum electrocardiosignal vector.

Adopt steepest descending method to minimize with the degree of approximation of optimum mother's electrocardiosignal vector mother's electrocardiosignal vector, thus obtain the optimal vector e of mother's electrocardiosignal.

According to the following formula, the degree of approximation of mother's electrocardiosignal vector and optimum mother's electrocardiosignal vector is obtained:

$\underset{w}{\min }J\left(w\right)=w^{T}R\left(0\right)w-\log \left[w^{T}R\left(\mathrm{\α}\right)w\right]$

Wherein, J (w) represents the degree of approximation of mother's electrocardiosignal vector and optimum mother's electrocardiosignal vector, and w represents mother's electrocardiosignal vector, expression minimizes operation about mother's electrocardiosignal vector w's, R (0) and R (α) represents that mother's electrocardiosignal and the maximum road electro physiology mixed signal time delay of Fetal ECG Signal-to-Noise are respectively the autocorrelation matrix of 0 and α respectively, α represents the fine estimation in mother's electrocardiosignal cycle, log [] represents operation of taking the logarithm, () ^trepresent matrix transpose operation.

Optimum mother's electrocardiosignal vector e recurrence calculation as follows:

The first step, initialization mother's electrocardiosignal vector w (0)=[1,1 ..., 1] ^t, initialize the autocorrelation matrix R that x (t) time delay is respectively 0 and α ⁰and R ^αfor null matrix;

Second step, according to the following formula, upgrades correlation matrix R ^α:

R ^α(k)＝λR ^α(k-1)+x(k)x ^T(k-α)

Wherein, R ^αk () represents that x (t) time delay of kth time iteration is the autocorrelation matrix of α, k represents the iterations of mother's electrocardiosignal vector, R ^α(k-1) x (t) time delay of expression kth-1 iteration is the autocorrelation matrix of α, the road mixed signal that mother's electrocardio when x (k) express time is k is maximum with other Signal-to-Noise, the road mixed signal that mother's electrocardio when x (k-α) express time is k-α is maximum with other Signal-to-Noise, λ is forgetting factor, this example gets λ=0.96, () ^trepresent matrix transpose operation;

3rd step, according to the following formula, upgrades correlation matrix R ⁰:

R ⁰(k)＝λR ⁰(k-1)+x(k)x ^T(k)

Wherein, R ⁰k () represents that x (t) time delay of kth time iteration is the autocorrelation matrix of 0, k represents the iterations of mother's electrocardiosignal vector, R (k-1) represents that x (t) time delay of kth-1 iteration is the autocorrelation matrix of 0, the road mixed signal that mother's electrocardio when x (k) express time is k is maximum with other Signal-to-Noise, λ is forgetting factor, this example gets λ=0.96, () ^trepresent matrix transpose operation;

4th step, according to the following formula, iterative computation mother electrocardiosignal vector:

w(k+1)＝w(k)-μ[R(0)w(k)-[w(k) ^TR(α)w(k)] ^-1R(α)w(k)]

Wherein, w (k+1) represents mother's electrocardiosignal vector of kth+1 iteration, w (k) represents mother's electrocardiosignal vector of kth time iteration, k represents the iterations of mother's electrocardiosignal vector, μ represents the iteration step length of mother's electrocardiosignal vector, R (0) and R (α) represents that mother's electrocardiosignal and the maximum road electro physiology mixed signal time delay of Fetal ECG Signal-to-Noise are respectively the autocorrelation matrix of 0 and α respectively, α represents the fine estimation in mother's electrocardiosignal cycle, () ^trepresent matrix transpose operation, () ^-1represent inversion operation;

5th step, makes k=k+1, repeats second step to the 5th step until convergence.

Adopt correction Newton method to minimize the degree of approximation of Fetal ECG signal vector with optimum Fetal ECG signal vector, thus obtain optimum Fetal ECG signal vector f.

According to the following formula, the degree of approximation of Fetal ECG signal vector and optimum Fetal ECG signal vector is obtained:

$\underset{u}{\min }L\left(u\right)=u^{T}V\left(0\right)u-\log \left[u^{T}V\left(\mathrm{\β}\right)u\right]$

Wherein, L (u) represents the degree of approximation of Fetal ECG signal vector and optimum Fetal ECG signal vector, and u represents Fetal ECG signal vector, represent and minimize operation about Fetal ECG signal vector u, V (0) and V (β) represents that Fetal ECG signal and the maximum road electro physiology mixed signal time delay of mother's electrocardiosignal signal to noise ratio are respectively the autocorrelation matrix of 0 and β respectively, β represents the fine estimation of Fetal ECG signal period, log [] represents operation of taking the logarithm, () ^trepresent matrix transpose operation.

Optimum Fetal ECG signal vector f recurrence calculation as follows:

The first step, initialization Fetal ECG signal vector w (0)=[1,1 ..., 1] ^t, initializing y (t) time delay is the inverse matrix Q of the autocorrelation matrix of the 0 and autocorrelation matrix V of y (t) time delay β ^βfor unit matrix;

Second step, according to the following formula, upgrades matrix V ^β:

V ^β(η)＝λV ^β(η-1)+x(η)x ^T(η-β)

Wherein, R ^β(η) y (t) time delay representing the η time iteration is the autocorrelation matrix of β, and η represents the iterations of mother's electrocardiosignal vector, R ^β(η-1) represents that y (t) time delay of η-1 iteration is the autocorrelation matrix of β, the road mixed signal that Fetal ECG when x (η) express time is η is maximum with other Signal-to-Noise, the road mixed signal that Fetal ECG when x (η-β) express time is η-β is maximum with other Signal-to-Noise, λ is forgetting factor, this example gets λ=0.96, () ^trepresent matrix transpose operation;

3rd step, according to the following formula, upgrades matrix Q:

$Q\left(\mathrm{\η}\right)=\frac{1}{\mathrm{\λ}}[Q(\mathrm{\η}-1)-\frac{Q(\mathrm{\η}-1)x\left(\mathrm{\η}\right)x^T\left(\mathrm{\η}\right)Q(\mathrm{\η}-1)}{\mathrm{\λ}+x^T\left(\mathrm{\η}\right)Q(\mathrm{\η}-1)x\left(\mathrm{\η}\right)}]$

Wherein, Q (η) represents that y (t) time delay of the η time iteration is the inverse matrix of the autocorrelation matrix of 0, η represents the iterations of mother's electrocardiosignal vector, Q (η-1) represents that y (t) time delay of η-1 iteration is the inverse matrix of the autocorrelation matrix of 0, the road mixed signal that Fetal ECG when x (η) express time is η is maximum with other Signal-to-Noise, λ is forgetting factor, and this example gets λ=0.96, () ^trepresent matrix transpose operation;

4th step, according to the following formula, iterative computation Fetal ECG signal vector:

$u(\mathrm{\η}+1)=\frac{[{\left(u{\left(\mathrm{\η}\right)}^{T}V\left(\mathrm{\β}\right)u\left(\mathrm{\η}\right)\right)}^{-1}+2{\left(u{\left(\mathrm{\η}\right)}^{T}V\left(0\right)u\left(\mathrm{\η}\right)\right)}^{-2}u{\left(\mathrm{\η}\right)}^{T}V\left(\mathrm{\β}\right)u\left(\mathrm{\η}\right)]Q^{-1}V\left(\mathrm{\β}\right)u\left(\mathrm{\η}\right)}{1+2{\left(u{\left(\mathrm{\η}\right)}^{T}V\left(0\right)u\left(\mathrm{\η}\right)\right)}^{-2}u{\left(\mathrm{\η}\right)}^{T}V\left(\mathrm{\β}\right)Q^{-1}V\left(\mathrm{\β}\right)u\left(\mathrm{\η}\right)}$

Wherein, u (η+1) represents the Fetal ECG signal vector of η+1 iteration, u (η) represents the Fetal ECG signal vector of the η time iteration, η represents the iterations of Fetal ECG signal vector, V (0) and V (β) represents that Fetal ECG and the maximum road mixed signal time delay of other Signal-to-Noise are respectively the autocorrelation matrix of 0 and β respectively, β represents the fine estimation of Fetal ECG signal period, Q represents that Fetal ECG and the maximum road mixed signal time delay of other Signal-to-Noise are the inverse matrix of the autocorrelation matrix of 0, () ^trepresent matrix transpose operation, () ^-1represent inversion operation, () ^-2represent the operation of negate quadratic power;

5th step, makes η=η+1, repeats second step to the 5th step until convergence.

Step 6, extracts electrocardiosignal.

Adopt projecting method, use optimum mother's electrocardiosignal vector to extract mother's electrocardiosignal from pretreated Multi-path electricity physiology mixed signal.According to the following formula, mother's electrocardiosignal is obtained:

h(t)＝e ^Td(t)

Wherein, h (t) represents mother's electrocardiosignal vector that mother's electrocardiosignal that t is extracted, e represent optimum, and d (t) represents the pretreated mixed signal of t, () ^trepresent matrix transpose operation.

Adopt projecting method, use optimum Fetal ECG signal vector to extract Fetal ECG signal from pretreated Multi-path electricity physiology mixed signal.According to the following formula, Fetal ECG signal is obtained:

z(t)＝f ^Td(t)

Wherein, z (t) represents the Fetal ECG signal vector that the Fetal ECG signal that t is extracted, f represent optimum, and d (t) represents the pretreated mixed signal of t, () ^trepresent matrix transpose operation.

Below in conjunction with accompanying drawing, effect of the present invention is further described.

1. simulated conditions

Simulated running system of the present invention is Intel (R) Core (TM) i7-2600CPU 650@3.40GHz, 32-bit Windows operating system, and simulation software adopts MATLAB (R2008a).

2. emulate content and interpretation of result

The fine estimation emulating search mother's electrocardiosignal cycle is carried out to the 1st road electro physiology mixed signal in 8 road electro physiology mixed signals of the input shown in accompanying drawing 2, setting pre-evaluation period value α ₀=0.8 second, section search time 0.6≤δ≤1.0, obtained the autocorrelation coefficient schematic diagram of the 1st road electro physiology mixed signal as shown in Figure 3.

The fine estimation emulating the search Fetal ECG signal period is carried out to the 8th road electro physiology mixed signal in 8 road electro physiology mixed signals of the input shown in accompanying drawing 2, setting pre-evaluation period value β ₀=0.5 second, section search time 0.35≤ε≤0.45, obtained the autocorrelation coefficient schematic diagram of the 8th road electro physiology mixed signal as shown in Figure 4.

The 8 road electro physiology mixed signal simulations of four kinds of methods to the input shown in accompanying drawing 2 of the present invention and prior art are adopted to extract mother and Fetal ECG signal, extract mother's electro-cardiologic signal waveforms comparison diagram as shown in Figure 5, extract Fetal ECG signal waveform comparison diagram as shown in Figure 6.

With reference to the autocorrelation coefficient schematic diagram of the 1st road electro physiology mixed signal shown in Fig. 3, the vertical coordinate in Fig. 3 represents the size of autocorrelation coefficient, abscissa representing time.Can see that in time range 0.6≤δ≤1.0 represented by abscissa the maximum of autocorrelation coefficient is mark point position in figure, then abscissa α=0.74 second marked in figure is a little the fine estimation in mother's electrocardiosignal cycle.

With reference to the autocorrelation coefficient schematic diagram of the 8th road electro physiology mixed signal shown in Fig. 4, the vertical coordinate in Fig. 4 represents the size of autocorrelation coefficient, abscissa representing time.The maximum that can obtain autocorrelation coefficient in time range 0.35≤ε≤0.45 represented by abscissa is mark point position in figure, then abscissa β=0.448 second marked in figure is a little the fine estimation of Fetal ECG signal period.

With reference to accompanying drawing 5, mother's electro-cardiologic signal waveforms comparison diagram of four kinds of method simulated extraction of the present invention and prior art, with reference to accompanying drawing 6, the Fetal ECG signal waveform comparison diagram of four kinds of method simulated extraction of the present invention and prior art.Curve in Fig. 5 (a) and Fig. 6 (a) is respectively and adopts A.K.Barros and A.Cichocki at article " Extraction of specific signals with temporal structure " (Neural Comput., vol.13, no.9, pp.1995 – 2003,2001) batch processing method of singular value decomposition disclosed in, mother of extraction and the waveform of Fetal ECG signal.Curve in Fig. 5 (b) and Fig. 6 (b) is respectively and adopts X.-L.Li and X.-D.Zhang at article " Sequential blind extraction adopting second-order statistics " (IEEE Signal Process.Lett., vol.14, no.1, pp.58 – 61,2007) based on the sequential Joint diagonalization method of second-order statistic disclosed in, mother of extraction and the waveform of Fetal ECG signal.Curve in Fig. 5 (c) and Fig. 6 (c) is respectively and adopts W.Liu, D.P.Mandic, and A.Cichocki is at article " Analysis and online realization of theCCA approach for blind source separation " (IEEE Trans.Neural Netw., vol.18, no.5, pp.1505 – 1510,2007) the self-adaption gradient descending method based on classical CCA criterion announced in, mother of extraction and the waveform of Fetal ECG signal.Curve in Fig. 5 (d) and Fig. 6 (d) is respectively and adopts A.Cichockiand R.Thawonmas at article " On-line algorithm for blind signal extraction of arbitrarilydistributed but temporally correlated sources using second order statistics " (NeuralProcess.Lett., vol.12, no.1, pp.91 – 98,2000) self-adaptation extraction method based on minimum forecast error standard announced in, mother of extraction and the waveform of Fetal ECG signal.The curve of Fig. 5 (e) and Fig. 6 (e) is respectively the waveform of mother and the Fetal ECG signal adopting the present invention to extract.

Mother's electro-cardiologic signal waveforms comparison diagram of four kinds of method simulated extraction of reference the present invention shown in accompanying drawing 5 and prior art.Abscissa representing time in Fig. 5 (a), (b), (c), (d), (e), vertical coordinate represents signal amplitude.Can be found out by contrast, the waveform of mother's electrocardiosignal that other four kinds of methods are extracted is clear not, and has distortion, and mother's electrocardiosignal that the inventive method is extracted inhibits Fetal ECG signal and noise well.

The Fetal ECG signal waveform comparison diagram of four kinds of method simulated extraction of reference the present invention shown in accompanying drawing 6 and prior art.Abscissa representing time in Fig. 6 (a), (b), (c), (d), (e), vertical coordinate represents signal amplitude.Can be found out by contrast, the waveform of the Fetal ECG signal that other four kinds of methods are extracted is clear not, Fetal ECG signal noise is comparatively large, and doping mother electrocardiosignal, the Fetal ECG signal that the inventive method is extracted inhibits parent electrocardiosignal and noise better.

Claims (7)

1., based on mother and the Fetal ECG Blind extracting method of second-order statistics, comprise the steps:

(1) electro physiology mixed signal is obtained:

Obtain parent chest and the abdominal part Multi-path electricity physiology mixed signal of synchronous acquisition;

(2) pretreatment:

(2a) use limited long wave digital lowpass filter, myoelectricity interference and noise filtering are carried out to Multi-path electricity physiology mixed signal, obtain the Multi-path electricity physiology mixed signal after the interference of filtering myoelectricity and noise;

(2b) use limited long digital trap, the filtering of 50Hz Hz noise is carried out to the Multi-path electricity physiology mixed signal after myoelectricity interference and noise filtering, obtains pretreated Multi-path electricity physiology mixed signal;

(3) signal to noise ratio of every road electro physiology mixed signal is obtained:

(3a) using in the electro physiology mixed signal of pretreatment Hou Mei road, mother's electrocardiosignal is as signal, and Fetal ECG signal, as noise, obtains the signal to noise ratio of mother's electrocardiosignal and Fetal ECG signal;

(3b) using in the electro physiology mixed signal of pretreatment Hou Mei road, Fetal ECG signal is as signal, and mother's electrocardiosignal, as noise, obtains the signal to noise ratio of Fetal ECG signal and mother's electrocardiosignal;

(4) cycle estimator:

(4a) select mother's electrocardiosignal and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise, by the interval of wherein adjacent two R ripples of mother's electrocardiosignal, estimate evaluation as mother's electrocardiosignal cycle;

(4b) adopt autocorrelation coefficient formula, calculate the autocorrelation coefficient of mother's electrocardiosignal and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise;

(4c) evaluation of estimating in mother's electrocardiosignal cycle is fluctuated error 0.2 second as section search time, the maximum of the absolute value of search autocorrelation coefficient, gets the fine estimation of moment as mother's electrocardiosignal cycle of maximum using the absolute value of autocorrelation coefficient;

(4d) select Fetal ECG signal and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio, by the interval of wherein adjacent two R ripples of Fetal ECG signal, estimate evaluation as the Fetal ECG signal period;

(4e) adopt autocorrelation coefficient formula, calculate the autocorrelation coefficient of Fetal ECG signal and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio;

(4f) evaluation of estimating of Fetal ECG signal period is fluctuated error 0.15 second as section search time, the maximum of the absolute value of search autocorrelation coefficient, gets the fine estimation of moment as the Fetal ECG signal period of maximum using the absolute value of autocorrelation coefficient;

(5) optimum electrocardiosignal vector is obtained:

(5a) adopt steepest descending method, obtain optimum mother's electrocardiosignal vector;

(5b) adopt correction Newton method, obtain optimum Fetal ECG signal vector;

(6) electrocardiosignal is extracted:

(6a) adopt projecting method, use optimum mother's electrocardiosignal vector to extract mother's electrocardiosignal from pretreated Multi-path electricity physiology mixed signal;

(6b) adopt projecting method, use optimum Fetal ECG signal vector to extract Fetal ECG signal from pretreated Multi-path electricity physiology mixed signal.

2. mother based on second-order statistics according to claim 1 and Fetal ECG Blind extracting method, it is characterized in that, the autocorrelation coefficient formula described in step (4b) is as follows:

$r\left(\mathrm{\δ}\right)=\frac{{\∫}_{t}x\left(t\right)x(t-\mathrm{\δ})\mathrm{dt}}{{\∫}_t{x}^2\left(t\right)\mathrm{dt}}$

Wherein, the autocorrelation coefficient of mother's electrocardiosignal when r (δ) represents that time delay is δ and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise, δ represents the time delay of the relative t of a road electro physiology mixed signal that mother's electrocardiosignal and Fetal ECG Signal-to-Noise are maximum, x (t) represents mother's electrocardiosignal and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise, t represents the sampling instant of mother's electrocardiosignal and the maximum road electro physiology mixed signal of Fetal ECG Signal-to-Noise, ∫ () dt represents the integration operation to sampling instant t, [] ²represent squared operation.

3. mother based on second-order statistics according to claim 1 and Fetal ECG Blind extracting method, it is characterized in that, the autocorrelation coefficient formula described in step (4e) is as follows:

$f\left(\mathrm{\ϵ}\right)=\frac{{\∫}_{n}y\left(n\right)y(n-\mathrm{\ϵ})\mathrm{dn}}{{\∫}_n{y}^2\left(n\right)\mathrm{dn}}$

Wherein, the autocorrelation coefficient of Fetal ECG signal when f (ε) represents that time delay is ε and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio, ε represents the time delay of the relative t of a road electro physiology mixed signal that Fetal ECG signal and mother's electrocardiosignal signal to noise ratio are maximum, y (n) represents Fetal ECG signal and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio, n represents the sampling instant of Fetal ECG signal and the maximum road electro physiology mixed signal of mother's electrocardiosignal signal to noise ratio, ∫ () dn represents the integration operation to sampling instant n, [] ²represent squared operation.

4. mother based on second-order statistics according to claim 1 and Fetal ECG Blind extracting method, it is characterized in that, the step of the steepest descending method described in step (5a) is as follows:

The first step, according to the following formula, obtains the degree of approximation of mother's electrocardiosignal vector and optimum mother's electrocardiosignal vector:

$\underset{w}{\min }J\left(w\right)=w^{T}R\left(0\right)w-\log \left[w^{T}R\left(\mathrm{\α}\right)w\right]$

Wherein, J (w) represents the degree of approximation of mother's electrocardiosignal vector and optimum mother's electrocardiosignal vector, and w represents mother's electrocardiosignal vector, expression minimizes operation about mother's electrocardiosignal vector w's, R (0) and R (α) represents that mother's electrocardiosignal and the maximum road electro physiology mixed signal time delay of Fetal ECG Signal-to-Noise are respectively the autocorrelation matrix of 0 and α respectively, α represents the fine estimation in mother's electrocardiosignal cycle, log [] represents operation of taking the logarithm, () ^trepresent matrix transpose operation;

Second step, according to the following formula, iterative computation mother electrocardiosignal vector:

w(k+1)＝w(k)-μ[R(0)w(k)-[w(k) ^TR(α)w(k)] ^-1R(α)w(k)]

Wherein, w (k+1) represents mother's electrocardiosignal vector of kth+1 iteration, w (k) represents mother's electrocardiosignal vector of kth time iteration, k represents the iterations of mother's electrocardiosignal vector, μ represents the iteration step length of mother's electrocardiosignal vector, R (0) and R (α) represents that mother's electrocardiosignal and the maximum road electro physiology mixed signal time delay of Fetal ECG Signal-to-Noise are respectively the autocorrelation matrix of 0 and α respectively, α represents the fine estimation in mother's electrocardiosignal cycle, () ^trepresent matrix transpose operation, () ^-1represent inversion operation;

3rd step, iteration mother electrocardiosignal, until convergence, obtains optimum mother's electrocardiosignal vector.

5. mother based on second-order statistics according to claim 1 and Fetal ECG Blind extracting method, is characterized in that, the correction Newton method step described in step (5b) is as follows:

The first step, according to the following formula, obtains the degree of approximation of Fetal ECG signal vector and optimum Fetal ECG signal vector:

$\underset{u}{\min }L\left(u\right)=u^{T}V\left(0\right)u-\log \left[u^{T}V\left(\mathrm{\β}\right)u\right]$

Wherein, L (u) represents the degree of approximation of Fetal ECG signal vector and optimum Fetal ECG signal vector, and u represents Fetal ECG signal vector, represent and minimize operation about Fetal ECG signal vector u, V (0) and V (β) represents that Fetal ECG signal and the maximum road electro physiology mixed signal time delay of mother's electrocardiosignal signal to noise ratio are respectively the autocorrelation matrix of 0 and β respectively, β represents the fine estimation of Fetal ECG signal period, log [] represents operation of taking the logarithm, () ^trepresent matrix transpose operation;

Second step, according to the following formula, iterative computation Fetal ECG signal vector:

$u(\mathrm{\η}+1)=\frac{[{\left(u{\left(\mathrm{\η}\right)}^{T}V\left(\mathrm{\β}\right)u\left(\mathrm{\η}\right)\right)}^{-1}+2{\left(u{\left(\mathrm{\η}\right)}^{T}V\left(0\right)u\left(\mathrm{\η}\right)\right)}^{-2}u{\left(\mathrm{\η}\right)}^{T}V\left(\mathrm{\β}\right)u\left(\mathrm{\η}\right)]{\left(V\left(0\right)\right)}^{-1}V\left(\mathrm{\β}\right)u\left(\mathrm{\η}\right)}{1+2{\left(u{\left(\mathrm{\η}\right)}^{T}V\left(0\right)u\left(\mathrm{\η}\right)\right)}^{-2}u{\left(\mathrm{\η}\right)}^{T}V\left(\mathrm{\β}\right){\left(V\left(0\right)\right)}^{-1}V\left(\mathrm{\β}\right)u\left(\mathrm{\η}\right)}$

Wherein, u (η+1) represents the Fetal ECG signal vector of η+1 iteration, u (η) represents the Fetal ECG signal vector of the η time iteration, η represents the iterations of Fetal ECG signal vector, V (0) and V (β) represents that Fetal ECG signal and the maximum road electro physiology mixed signal time delay of mother's electrocardiosignal signal to noise ratio are respectively the autocorrelation matrix of 0 and β respectively, β represents the fine estimation of Fetal ECG signal period, () ^trepresent matrix transpose operation, () ^-1represent inversion operation, () ^-2represent the operation of negate quadratic power;

3rd step, iteration Fetal ECG signal, until convergence, obtains optimum Fetal ECG signal vector.

6. mother based on second-order statistics according to claim 1 and Fetal ECG Blind extracting method, it is characterized in that, the projecting method described in step (6a) refers to according to the following formula, obtains mother's electrocardiosignal:

h(t)＝e ^Td(t)

Wherein, h (t) represents mother's electrocardiosignal vector that mother's electrocardiosignal that t is extracted, e represent optimum, and d (t) represents the pretreated electro physiology mixed signal of t, () ^trepresent matrix transpose operation.

7. mother based on second-order statistics according to claim 1 and Fetal ECG Blind extracting method, it is characterized in that, the projecting method described in step (6b) refers to according to the following formula, obtains Fetal ECG signal:

z(t)＝f ^Td(t)

Wherein, z (t) represents that t extracts the Fetal ECG signal obtained, and f represents optimum Fetal ECG signal vector, and d (t) represents the pretreated electro physiology mixed signal of t, () ^trepresent matrix transpose operation.