CN107174236A - A kind of Denoising of ECG Signal and device based on optimum theory - Google Patents
A kind of Denoising of ECG Signal and device based on optimum theory Download PDFInfo
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Abstract
The invention discloses a kind of Denoising of ECG Signal based on optimum theory, including：The electrocardiosignal received is pre-processed, the heartbeat matrix of storage heart beat cycle is obtained；Decomposition is optimized to heartbeat matrix based on optimum theory, the electrocardiosignal matrix after denoising is obtained；The present invention obtains the heartbeat matrix of storage heart beat cycle, can obtain the heartbeat matrix comprising electrocardiosignal and myoelectricity noise by being pre-processed to the electrocardiosignal received；By optimizing decomposition to heartbeat matrix based on optimum theory, obtain the electrocardiosignal matrix after denoising, myoelectricity noise in heartbeat matrix can be separated with electrocardiosignal, so as to obtain the electrocardiosignal for removing myoelectricity noise, myoelectricity noise effectively is inhibited, while remaining the effective information of electrocardiosignal.In addition, the invention also discloses a kind of electrocardiosignal denoising device based on optimum theory, equally with above-mentioned beneficial effect.
Description
Technical field
The present invention relates to processing of biomedical signals field, more particularly to a kind of electrocardiosignal denoising based on optimum theory
Method and device.
Background technology
With the development of clinical medicine, electrocardiogram (ECG, electrocardiographic signal, electrocardiosignal) is
Through the most important instrument for being used for Diagnosing Cardiac lesion as one.The acquisition of electrocardiosignal is typically by measurand
Upper torso place corresponding electrode sensor and collect.And electrocardiosignal is inevitably introduced in measurement process
Some noises, such as industrial frequency noise, baseline drift, myoelectricity noise etc..How effectively to remove all kinds of obstacles and noise, it is accurate to extract
Go out useful ecg wave form, be an important content of heart disease intelligent diagnostics.
In the prior art, the denoising method of electrocardiosignal is mainly the method based on wave filter.As high-pass filter can be with
It is effective to suppress baseline drift, and low pass filter effectively can suppress to industrial frequency noise.Wavelet transformation equally also by
Apply in electrocardiosignal denoising field.Method based on wavelet transformation can be regarded as the extension based on filtered method.Recently
Method based on empirical mode decomposition is also applied to electrocardiosignal denoising field.By the way that electrocardiosignal is decomposed into different consolidate
There is mode function (intrinsic mode functions, IMFs), empirical mode decomposition is by selecting corresponding natural mode of vibration
Function is to rebuild clean ECG signal.Although however, the above method can obtain preferable to baseline drift and the denoising of industrial frequency noise
Effect, but be due to that the noise spectrum of myoelectricity noise (EMG, electromyographic noise) can be with the heart after denoising
The frequency spectrum of electric signal occurs overlapping so that the myoelectricity noise of spectrum overlapping effectively can not be removed by the above method, and
Myoelectricity noise can not effectively be suppressed.Therefore, how myoelectricity noise is effectively suppressed, and retains having for electrocardiosignal
Information is imitated, is urgent problem now.
The content of the invention
It is an object of the invention to provide a kind of Denoising of ECG Signal and device based on optimum theory, to utilize optimization
The mode of decomposition, myoelectricity noise is separated with electrocardiosignal, and myoelectricity noise is effectively suppressed, and retains having for electrocardiosignal
Imitate information.
In order to solve the above technical problems, the present invention provides a kind of Denoising of ECG Signal based on optimum theory, including：
The electrocardiosignal received is pre-processed, the heartbeat matrix of storage heart beat cycle is obtained；
Decomposition is optimized to the heartbeat matrix based on optimum theory, the electrocardiosignal matrix after denoising is obtained.
Optionally, the described pair of electrocardiosignal received is pre-processed, and obtains the heartbeat matrix of storage heart beat cycle, bag
Include：
The electrocardiosignal is carried out removing baseline, goes industrial frequency noise and QRS wave shape to detect, QRS wave shape is obtained interval and right
The datum mark answered；
Using predetermined number sample point of the QRS wave shape in interval before the corresponding datum mark of each heart beat cycle as
Starting point, adds 1 sample point by each corresponding datum mark foregoing description predetermined number of heart beat cycle in QRS wave shape interval
As the terminating point of a upper heart beat cycle, the heartbeat matrix M of the whole heart beat cycles of storage is obtained；
Wherein,RRmaxInterval for most long RR, each RR intervals are
Each self-corresponding heart beat cycle, the datum mark is { bj| j=1,2 ... J }, t is the element in the heartbeat matrix M,It is RR for dimensionmax* the real number matrix that J is tieed up.
Optionally, it is described that decomposition is optimized to the heartbeat matrix based on optimum theory, obtain the electrocardio letter after denoising
Number matrix, including：
Make A0=E0=0, Y0=M,μ ＞ 0, ρ ＞ 1 and k=
0；Wherein, k is iterations, A0、E0And Y0Respectively iterations is 0 electrocardiosignal matrix, noise matrix and Lagrange
Multiplier matrix, μ is regulation parameter, and ρ is default scalar value；
It is utilized respectively
Yk+1=Yk+μk(M-Ak+1-Ek+1)、μk+1=ρ μkA is updated with k=k+1k+1、Ek+1、Yk+1、μk+1And k；Wherein, γ is to set in advance
The regulation parameter put；
Judge whether to meet | | M-Ak+1-Ek+1||F≤δ||M||FOr k numerical value reaches default maximum iteration；Its
In, δ=10-7, | | | |FFor Frobenius norms；
If so, then by A nowkIt is used as the electrocardiosignal matrix；
If it is not, being utilized respectively described in then performing Yk+1=Yk+μk(M-Ak+1-Ek+1)、μk+1=ρ μkA is updated with k=k+1k+1、Ek+1、
Yk+1、μk+1And the step of k.
Optionally, it is described that decomposition is optimized to the heartbeat matrix based on optimum theory, obtain the electrocardio letter after denoising
Number matrix, in addition to：
Decomposition is optimized to the heartbeat matrix based on the optimum theory, noise matrix is obtained.
In addition, present invention also offers a kind of electrocardiosignal denoising device based on optimum theory, including：
Acquisition module, for being pre-processed to the electrocardiosignal received, obtains the heartbeat matrix of storage heart beat cycle；
Optimization module, for optimizing decomposition to the heartbeat matrix based on optimum theory, obtains the electrocardio after denoising
Signal matrix.
Optionally, the acquisition module, including：
Submodule is pre-processed, for carrying out removing baseline to the electrocardiosignal, going industrial frequency noise and QRS wave shape to detect, is obtained
Take the interval and corresponding datum mark of QRS wave shape；
Acquisition submodule, for will the QRS wave shape it is interval in it is default before the corresponding datum mark of each heart beat cycle
Quantity sample point is pre- by the corresponding datum mark foregoing description of each heart beat cycle in QRS wave shape interval as starting point
If quantity adds 1 sample point as the terminating point of a upper heart beat cycle, the heartbeat matrix M of the whole heart beat cycles of storage is obtained；
Wherein,RRmaxInterval for most long RR, each RR intervals are
Each self-corresponding heart beat cycle, the datum mark is { bj| j=1,2 ... J }, t is the element in the heartbeat matrix M,It is RR for dimensionmax* the real number matrix that J is tieed up.
Optionally, the optimization module, including：
Initialization submodule, for making A0=E0=0, Y0=M, μ ＞ 0, ρ ＞ 1 and k=0；Wherein, k is iterations, A0、E0And Y0Respectively iterations is 0 electrocardio
Signal matrix, noise matrix and Lagrange multiplier matrix, μ are regulation parameter, and ρ is default scalar value；
Iteration submodule, for being utilized respectively
Yk+1=Yk+μk(M-Ak+1-Ek+1)、μk+1=ρ μkA is updated with k=k+1k+1、Ek+1、Yk+1、μk+1And k；Wherein, γ is to set in advance
The regulation parameter put；
Judging submodule, for judging whether to meet | | M-Ak+1-Ek+1||F≤δ||M||FOr k numerical value reach it is default
Maximum iteration；Wherein, δ=10-7, | | | |FFor Frobenius norms；Opened if it is not, then being sent to the iteration submodule
Dynamic signal；If so, then by A nowkIt is used as the electrocardiosignal matrix.
Optionally, the optimization module, in addition to：
Optimize submodule, for optimizing decomposition to the heartbeat matrix based on the optimum theory, obtain noise square
Battle array.
A kind of Denoising of ECG Signal based on optimum theory provided by the present invention, including：To the electrocardio received
Signal is pre-processed, and obtains the heartbeat matrix of storage heart beat cycle；The heartbeat matrix is optimized based on optimum theory
Decompose, obtain the electrocardiosignal matrix after denoising；
It can be seen that, the present invention obtains the heartbeat square of storage heart beat cycle by being pre-processed to the electrocardiosignal received
Battle array, can obtain the heartbeat matrix comprising electrocardiosignal and myoelectricity noise；It is excellent by being carried out based on optimum theory to heartbeat matrix
Change and decompose, obtain the electrocardiosignal matrix after denoising, myoelectricity noise in heartbeat matrix can be separated with electrocardiosignal, so as to
To obtain the electrocardiosignal for removing myoelectricity noise, myoelectricity noise is effectively inhibited, while remaining effective letter of electrocardiosignal
Breath.In addition, present invention also offers a kind of electrocardiosignal denoising device based on optimum theory, equally with above-mentioned beneficial effect
Really.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the accompanying drawing used required in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
The embodiment of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can also basis
The accompanying drawing of offer obtains other accompanying drawings.
A kind of flow chart for Denoising of ECG Signal based on optimum theory that Fig. 1 is provided by the embodiment of the present invention；
A kind of structure chart for electrocardiosignal denoising device based on optimum theory that Fig. 2 is provided by the embodiment of the present invention.
Embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
A part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
It refer to Fig. 1, a kind of Denoising of ECG Signal based on optimum theory that Fig. 1 is provided by the embodiment of the present invention
Flow chart.This method can include：
Step 101：The electrocardiosignal received is pre-processed, the heartbeat matrix of storage heart beat cycle is obtained.
Wherein, the pretreatment carried out to electrocardiosignal can include removing baseline, go industrial frequency noise and QRS wave shape to detect, obtain
Take a series of QRS and corresponding datum mark { bj| j=1,2 ... J }, on this basis, in order to preferably tackle myoelectricity noise
In unusual spot noise, the present count in interval before the corresponding datum mark of each heart beat cycle by QRS wave shape can also be included
Predetermined number before the corresponding datum mark of each heart beat cycle in QRS wave shape interval is added 1 by amount sample point as starting point
Sample point as the terminating point of a upper heart beat cycle change heart beat cycle the step of, such as selection current heartbeat cycle datum mark
S sample point before as starting point, using next heart beat cycle datum mark before s+1 sample point as terminating point,
So as to which heart beat cycle can be stored in heartbeat matrix.For the concrete mode of the pretreatment carried out to electrocardiosignal, Ke Yiyou
Designer is voluntarily set, as long as the heartbeat matrix of storage heart beat cycle can be obtained, the present embodiment is unrestricted to this.
Specifically, the heartbeat matrix obtained can be the heartbeat matrix for changing heart beat cycle through the above waySuch as：
Wherein,RRmaxInterval for most long RR, each RR intervals are each self-corresponding heartbeat week
Phase, t is the element in heartbeat matrix M,It is RR for dimensionmax* the real number matrix that J is tieed up.
Step 102：Decomposition is optimized to heartbeat matrix based on optimum theory, the electrocardiosignal matrix after denoising is obtained.
Specifically, the concrete mode for optimizing decomposition to heartbeat matrix based on optimum theory, can be for foundation such as
Under Augmented Lagrangian Functions as heartbeat matrix majorized function：
Wherein, L (A, E, Y, μ) is majorized function, and μ is regulation parameter, and Y is Lagrange multiplier matrix, | | A | |W, *=
∑iwiσi(A), w=[w1..., wi..., wn]T, and wi>=0, σi(A) i-th of singular value for being A, | | E | |1For noise matrix E
Middle element absolute value sum, | | | |FFor Frobenius norms, ＜, ＞ are matrix inner products operator.
It is as follows so as to solve acquisition matrix heartbeat A more new formulas：
Other specification updates A in fixed L (A, E, Y, μ)
Formula (3) can be rewritten as to the minimization problem of following form：
Wherein, formula (4) and X and Y in formula (5) are displayingTwo symbols of formula, formula (4) and formula (5)
In Y=U ∑s VT, the Y in the singular value decomposition for being Y (singular value decomposition, SVD) and the present embodimentk
And Yk+1It is unrelated, Sεw[∑] is extensive soft-threshold operator (generalized soft-threholding operator).
Sεw[∑]ii=max (∑sii-εwi, 0) and (6)
Wherein, C is normal parameter in formula (7), and ε is can be with the less parameter of numerical value to avoid denominator as 0.
It is understood that for above mentioned problem solution in σ1≥...≥σn>=0 and 0≤w1≤...≤wnCondition
Under obtain.Therefore, the heartbeat matrix A of (k+1) secondary iterationk+1It can pass throughIt is updated：
Solving noise matrix more new formula can be as follows：
Other specification updates E in fixed L (A, E, Y, μ)
Solution in formula (9) can be obtained by following form：
Wherein, τ is constant and τ ＞ 0, x ∈ R, Sτ[x] be contraction operator (shrinkage operator), formula (10) and
X and Y in formula (11) are displaying SτTwo symbols of [] formula, it is unrelated with the X and Y in formula (4) and formula (5), formula (10) and
The Y in Y and the present embodiment in formula (11)kAnd Yk+1It is unrelated.
Therefore, the noise matrix E of (k+1) secondary iterationk+1S can be passed throughτ[] is updated：
The Lagrange multiplier matrix Y of (k+1) secondary iterationk+1Can be：
Yk+1=Yk+μk(M-Ak+1-Ek+1) (13)
Iteration stopping criterion can be to work as | | M-Ak+1-Ek+1||F≤δ||M||FOr k numerical value reaches default greatest iteration
Stop iteration during number of times.Wherein, δ=10-7。
It is understood that the detailed process of this step can be the initialization of advanced row, A is made0=E0=0, Y0=M,μ ＞ 0, ρ ＞ 1 and k=0；It is iterated again, is utilized respectively formula
(8)、(12)、(13)、μk+1=ρ μkA is updated with k=k+1k+1、Ek+1、Yk+1、μk+1And k；Then judge whether to meet | | M-
Ak+1-Ek+1||F≤δ||M||FOr k numerical value reaches default maximum iteration；If so, then by A nowkIt is used as the heart
Electric signal matrix；If it is not, the step of then performing iteration again.
It should be noted that for the regulation parameter γ pre-set in formula (12) acquisition modes, can be walked to obtain
Rapid 101 obtain after heartbeat matrix M, receive the numerical value inputted by user or designer；Can also be that designer or user set
Put the numerical value stored afterwards；The numerical value that can also be obtained for other modes.As long as regulation parameter γ in formula (12) can be obtained
Numerical value, for specific acquisition modes, the present embodiment does not do any limitation.
It is understood that the specific side for optimizing decomposition in this step to heartbeat matrix based on optimum theory
Formula, can be carried out through the above way, it would however also be possible to employ other Optimal Decomposition modes similar to aforesaid way are carried out, as long as can
To obtain the electrocardiosignal matrix after denoising, that is, the electrocardiosignal of myoelectricity noise is removed, for specific Optimal Decomposition side
Formula, the present embodiment does not do any limitation.For optimizing the content obtained after decomposition, can only it obtain as shown in this embodiment
Remove the electrocardiosignal matrix after making an uproar；The electrocardiosignal matrix after denoising and noise matrix (E can also be obtainedk).This implementation pair
This does not do any limitation equally.
In the present embodiment, the embodiment of the present invention obtains storage heartbeat by being pre-processed to the electrocardiosignal received
The heartbeat matrix in cycle, can obtain the heartbeat matrix comprising electrocardiosignal and myoelectricity noise；By based on optimum theory to the heart
Jump matrix and optimize decomposition, obtain the electrocardiosignal matrix after denoising, myoelectricity noise in heartbeat matrix and electrocardio can be believed
Number separation, so as to obtain remove myoelectricity noise electrocardiosignal, myoelectricity noise is effectively inhibited, while remaining electrocardio
The effective information of signal.
It refer to Fig. 2, a kind of electrocardiosignal denoising device based on optimum theory that Fig. 2 is provided by the embodiment of the present invention
Structure chart.The device can include：
Acquisition module 100, for being pre-processed to the electrocardiosignal received, obtains the heartbeat square of storage heart beat cycle
Battle array；
Optimization module 200, for optimizing decomposition to heartbeat matrix based on optimum theory, obtains the electrocardio letter after denoising
Number matrix.
Optionally, acquisition module 100, can include：
Submodule is pre-processed, for carrying out removing baseline to electrocardiosignal, going industrial frequency noise and QRS wave shape to detect, QRS is obtained
The interval and corresponding datum mark of waveform；
Acquisition submodule, for the predetermined number by QRS wave shape in interval before the corresponding datum mark of each heart beat cycle
Predetermined number before the corresponding datum mark of each heart beat cycle in QRS wave shape interval is added 1 sample by individual sample point as starting point
This terminating point as a upper heart beat cycle, obtains the heartbeat matrix M of the whole heart beat cycles of storage；
Wherein,RRmaxInterval for most long RR, each RR intervals are
Each self-corresponding heart beat cycle, datum mark is { bj| j=1,2 ... J }, t is the element in the heartbeat matrix M,It is RR for dimensionmax* the real number matrix that J is tieed up.
Optionally, optimization module 200, can include：
Initialization submodule, for making A0=E0=0, Y0=M, μ ＞ 0, ρ ＞ 1 and k=0；Wherein, k is iterations, A0、E0And Y0Respectively iterations is 0 electrocardio
Signal matrix, noise matrix and Lagrange multiplier matrix, μ are regulation parameter, and ρ is default scalar value；
Iteration submodule, for being utilized respectively
Yk+1=Yk+μk(M-Ak+1-Ek+1)、μk+1=ρ μkA is updated with k=k+1k+1、Ek+1、Yk+1、μk+1And k；Wherein, γ is to set in advance
The regulation parameter put；
Judging submodule, for judging whether to meet | | M-Ak+1-Ek+1||F≤δ||M||FOr k numerical value reach it is default
Maximum iteration；Wherein, δ=10-7, | | | |FFor Frobenius norms；Start letter if it is not, then being sent to iteration submodule
Number；If so, then by A nowkIt is used as electrocardiosignal matrix.
Optionally, optimization module 200, can also include：
Optimize submodule, for optimizing decomposition to heartbeat matrix based on optimum theory, obtain noise matrix.
In the present embodiment, the embodiment of the present invention is pre-processed by 100 pairs of electrocardiosignals received of acquisition module, is obtained
The heartbeat matrix of storage heart beat cycle is taken, the heartbeat matrix comprising electrocardiosignal and myoelectricity noise can be obtained；By optimizing mould
Block 200 optimizes decomposition to heartbeat matrix based on optimum theory, obtains the electrocardiosignal matrix after denoising, can be by heartbeat square
Myoelectricity noise is separated with electrocardiosignal in battle array, so as to obtain the electrocardiosignal for removing myoelectricity noise, effectively inhibits flesh
Electrical noise, while remaining the effective information of electrocardiosignal.
The embodiment of each in specification is described by the way of progressive, and what each embodiment was stressed is and other realities
Apply the difference of example, between each embodiment identical similar portion mutually referring to.For device disclosed in embodiment
Speech, because it is corresponded to the method disclosed in Example, so description is fairly simple, related part is referring to method part illustration
.
Professional further appreciates that, with reference to the unit of each example of the embodiments described herein description
And algorithm steps, can be realized with electronic hardware, computer software or the combination of the two, in order to clearly demonstrate hardware and
The interchangeability of software, generally describes the composition and step of each example according to function in the above description.These
Function is performed with hardware or software mode actually, depending on the application-specific and design constraint of technical scheme.Specialty
Technical staff can realize described function to each specific application using distinct methods, but this realization should not
Think beyond the scope of this invention.
Directly it can be held with reference to the step of the method or algorithm that the embodiments described herein is described with hardware, processor
Capable software module, or the two combination are implemented.Software module can be placed in random access memory (RAM), internal memory, read-only deposit
Reservoir (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technology
In any other form of storage medium well known in field.
Detailed Jie has been carried out to the Denoising of ECG Signal provided by the present invention based on optimum theory and device above
Continue.Specific case used herein is set forth to the principle and embodiment of the present invention, and the explanation of above example is only
It is the method and its core concept for being used to help understand the present invention.It should be pointed out that for those skilled in the art
For, under the premise without departing from the principles of the invention, some improvement and modification can also be carried out to the present invention, these improve and repaiied
Decorations are also fallen into the protection domain of the claims in the present invention.
Claims (8)
1. a kind of Denoising of ECG Signal based on optimum theory, it is characterised in that including：
The electrocardiosignal received is pre-processed, the heartbeat matrix of storage heart beat cycle is obtained；
Decomposition is optimized to the heartbeat matrix based on optimum theory, the electrocardiosignal matrix after denoising is obtained.
2. the Denoising of ECG Signal according to claim 1 based on optimum theory, it is characterised in that described pair of reception
To electrocardiosignal pre-processed, obtain storage heart beat cycle heartbeat matrix, including：
The electrocardiosignal is carried out removing baseline, goes industrial frequency noise and QRS wave shape to detect, QRS wave shape is obtained interval and corresponding
Datum mark；
It regard predetermined number sample point of the QRS wave shape in interval before the corresponding datum mark of each heart beat cycle as starting
Point, using the QRS wave shape it is interval in each corresponding datum mark foregoing description predetermined number of heart beat cycle add 1 sample point as
The terminating point of a upper heart beat cycle, obtains the heartbeat matrix M of the whole heart beat cycles of storage；
Wherein,RRmaxInterval for most long RR, each RR intervals are each right
The heart beat cycle answered, the datum mark is { bj| j=1,2 ... J }, t is the element in the heartbeat matrix M,
It is RR for dimensionmax* the real number matrix that J is tieed up.
3. the Denoising of ECG Signal according to claim 2 based on optimum theory, it is characterised in that described based on excellent
Change theory and decomposition is optimized to the heartbeat matrix, obtain the electrocardiosignal matrix after denoising, including：
Make A0=E0=0, Y0=M,μ ＞ 0, ρ ＞ 1 and k=0；Its
In, k is iterations, A0、E0And Y0Respectively iterations is 0 electrocardiosignal matrix, noise matrix and Lagrange multiplier
Matrix, μ is regulation parameter, and ρ is default scalar value；
It is utilized respectivelyYk+1=
Yk+μk(M-Ak+1-Ek+1)、μk+1=ρ μkA is updated with k=k+1k+1、Ek+1、Yk+1、μk+1And k；Wherein, γ is pre-set
Regulation parameter；
Judge whether to meet | | M-Ak+1-Ek+1||F≤δ||M||FOr k numerical value reaches default maximum iteration；Wherein, δ
=10-7, | | | |FFor Frobenius norms；
If so, then by A nowkIt is used as the electrocardiosignal matrix；
If it is not, being utilized respectively described in then performing
Yk+1=Yk+μk(M-Ak+1-Ek+1)、μk+1=ρ μkA is updated with k=k+1k+1、Ek+1、Yk+1、μk+1And the step of k.
4. the Denoising of ECG Signal based on optimum theory according to claims 1 to 3, it is characterised in that the base
Decomposition is optimized to the heartbeat matrix in optimum theory, the electrocardiosignal matrix after denoising is obtained, in addition to：
Decomposition is optimized to the heartbeat matrix based on the optimum theory, noise matrix is obtained.
5. a kind of electrocardiosignal denoising device based on optimum theory, it is characterised in that including：
Acquisition module, for being pre-processed to the electrocardiosignal received, obtains the heartbeat matrix of storage heart beat cycle；
Optimization module, for optimizing decomposition to the heartbeat matrix based on optimum theory, obtains the electrocardiosignal after denoising
Matrix.
6. the electrocardiosignal denoising device according to claim 5 based on optimum theory, it is characterised in that the acquisition mould
Block, including：
Submodule is pre-processed, for carrying out removing baseline to the electrocardiosignal, going industrial frequency noise and QRS wave shape to detect, QRS is obtained
The interval and corresponding datum mark of waveform；
Acquisition submodule, for the predetermined number by the QRS wave shape in interval before the corresponding datum mark of each heart beat cycle
Individual sample point is as starting point, by the corresponding datum mark foregoing description present count of each heart beat cycle in QRS wave shape interval
Amount plus 1 sample point obtain the heartbeat matrix M of the whole heart beat cycles of storage as the terminating point of a upper heart beat cycle；
Wherein,RRmaxInterval for most long RR, each RR intervals are each right
The heart beat cycle answered, the datum mark is { bj| j=1,2 ... J }, t is the element in the heartbeat matrix M,
It is RR for dimensionmax* the real number matrix that J is tieed up.
7. the electrocardiosignal denoising device according to claim 6 based on optimum theory, it is characterised in that the optimization mould
Block, including：
Initialization submodule, for making A0=E0=0, Y0=M, μ ＞
0, ρ ＞ 1 and k=0；Wherein, k is iterations, A0、E0And Y0Electrocardiosignal matrix, noise that respectively iterations is 0
Matrix and Lagrange multiplier matrix, μ are regulation parameter, and ρ is default scalar value；
Iteration submodule, for being utilized respectively
Yk+1=Yk+μk(M-Ak+1-Ek+1)、μk+1=ρ μkA is updated with k=k+1k+1、Ek+1、Yk+1、μk+1And k；Wherein, γ is to set in advance
The regulation parameter put；
Judging submodule, for judging whether to meet | | M-Ak+1-Ek+1||F≤δ||M||FOr k numerical value reaches default maximum
Iterations；Wherein, δ=10-7, | | | |FFor Frobenius norms；Start letter if it is not, then being sent to the iteration submodule
Number；If so, then by A nowkIt is used as the electrocardiosignal matrix.
8. the electrocardiosignal denoising device based on optimum theory according to claim 5 to 7, it is characterised in that described excellent
Change module, in addition to：
Optimize submodule, for optimizing decomposition to the heartbeat matrix based on the optimum theory, obtain noise matrix.
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