CN110063726A - A kind of electrocardiosignal list lead f wave extracting method and device - Google Patents
A kind of electrocardiosignal list lead f wave extracting method and device Download PDFInfo
- Publication number
- CN110063726A CN110063726A CN201910477520.4A CN201910477520A CN110063726A CN 110063726 A CN110063726 A CN 110063726A CN 201910477520 A CN201910477520 A CN 201910477520A CN 110063726 A CN110063726 A CN 110063726A
- Authority
- CN
- China
- Prior art keywords
- signal
- heart
- claps
- wave
- electrocardiosignal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
- A61B5/346—Analysis of electrocardiograms
- A61B5/349—Detecting specific parameters of the electrocardiograph cycle
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Molecular Biology (AREA)
- Biomedical Technology (AREA)
- Veterinary Medicine (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Animal Behavior & Ethology (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Surgery (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Signal Processing (AREA)
- Cardiology (AREA)
- Artificial Intelligence (AREA)
- Psychiatry (AREA)
- Physiology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Power Engineering (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
The embodiment of the invention discloses a kind of electrocardiosignal list lead f wave extracting method and devices to be cut into multiple individually initial hearts for electrocardiosignal and clap signal according to the peak position R of electrocardiosignal detected；Signal is clapped to each initial heart and carries out Gauss enhancing, the enhanced heart of Gauss is obtained and claps signal；Using the nearest neighbor algorithm based on DTW distance, determine that each heart claps K neighbour's heart bat of signal.It calculates each heart and claps the DTW residual vector that its corresponding K neighbour heart of signal is clapped, and according to DTW residual vector, obtain the f wave signal that each heart claps signal；Splice each f wave signal, to complete the extraction to electrocardiosignal f wave.Clapped with K neighbour's heart is that template claps signal progress DTW reconstruct to the corresponding heart, resulting K residual vector is averagely obtained into f wave, realize the correction to R blob detection error, reduce the influence of distortion QRS wave, the accuracy of f wave extraction is improved, provides reliable foundation for atrial fibrillation clinical diagnosis.
Description
Technical field
The present invention relates to electrocardiosignal technical field, more particularly to a kind of electrocardiosignal list lead f wave extracting method and
Device.
Background technique
Atrial fibrillation is a kind of common cardiac arrhythmia.With advancing age, the incidence of atrial fibrillation can be constantly increasing.
Atrial fibrillation may cause apoplexy and heart failure, seriously endanger public health.In cardiac, the death rate of patients with atrial fibrillation is
Twice of other patients.When atrial fibrillation occurs, the frequency of atrial impulses reaches 300~600 times per minute, and normal cardiac electrical P wave disappears
It loses, instead the f wave continuously, irregularly trembleed.The physical parameter of f wave, such as amplitude and frequency spectrum are commonly used for atrial fibrillation
Clinical diagnosis, have important meaning to the research of atrial fibrillation bioelectrical activity mechanism.
But ventricle QRS wave and atrium f wave have part aliasing in time domain and frequency domain, constrain the detection accuracy of f wave.
In order to solve this problem, researcher proposes many methods, can be divided into multi-lead and single lead two major classes.
Multi-lead method is using technologies such as independent component analysis, sparse component analysis, using between multichannel electrocardiosignal
Correlation separation QRS wave and f wave need to arrange multiple electrodes although detection accuracy is higher, be not easy to mobile electrocardio prison
Equipment is protected to use.Single lead method rejects QRS wave or according to priori mould using technologies such as average template elimination, Bayesian filters
Type carries out parameter Estimation to f wave, to realize the extraction of f wave.The although cardiac monitoring easy to remove of single lead method, but to different
The normal heart claps the heart caused by such as ventricular premature beat and claps metamorphosis sensitivity, and detection accuracy is lower.
It is those skilled in the art's urgent problem to be solved as it can be seen that how to improve the precision that single lead f wave extracts.
Summary of the invention
The purpose of the embodiment of the present invention is that providing a kind of electrocardiosignal list lead f wave extracting method and device, can be improved
The precision that single lead f wave extracts.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of electrocardiosignal list lead f wave extracting method, packet
It includes:
The peak position R of electrocardiosignal is detected, and according to each peak position R, the electrocardiosignal is cut into multiple lists
Only initial heart claps signal；
Signal is clapped to each initial heart and carries out Gauss enhancing, the enhanced heart of Gauss is obtained and claps signal；
Using the nearest neighbor algorithm based on DTW distance, determine that each heart claps K neighbour's heart bat of signal；
It calculates each heart and claps the DTW residual vector that its corresponding K neighbour heart of signal is clapped, and is residual according to the DTW
Difference vector obtains the f wave signal that each heart claps signal；
Splice each f wave signal, to complete the extraction to the electrocardiosignal f wave.
Optionally, described to clap signal progress Gauss enhancing to each heart, obtaining the enhanced heart bat signal of Gauss includes:
According to following formula, signal is clapped to each heart and carries out Gauss enhancing,
Wherein, xi(t) indicate that i-th of heart claps the wave amplitude vector of signal, i=1,2,3..., N, N indicates that the heart claps of signal
Number, t indicate that the heart claps the sampling instant of signal,Indicate that i-th of enhanced heart claps the wave amplitude vector of signal, μ indicates high
The expectation of this weighting function, at the time of μ is located at corresponding to the peak R, σ indicates the variance of gaussian weighing function.
Optionally, described according to the DTW residual vector, obtaining the f wave signal that each heart claps signal includes:
K target DTW residual vector corresponding to signal is clapped to the target heart to be averaged, and is obtained the target heart and is clapped signal
F wave signal；Wherein, it is that any one heart that all hearts are clapped in signal claps signal that the target heart, which claps signal,.
Optionally, before the peak position R of the detection electrocardiosignal further include:
The initial electrocardiosignal of acquisition is filtered, filtered electrocardiosignal is obtained.
The embodiment of the invention also provides a kind of electrocardiosignal list lead f wave extraction elements, including cutter unit, enhancing list
Member, determination unit, computing unit and concatenation unit；
The cutter unit, for detecting the peak position R of electrocardiosignal, and according to each peak position R, by the electrocardio
Signal is cut into multiple individually initial hearts and claps signal；
The enhancement unit carries out Gauss enhancing for clapping signal to each initial heart, obtains the enhanced heart of Gauss
Clap signal；
The determination unit determines that each heart claps K of signal closely for using the nearest neighbor algorithm based on DTW distance
The adjacent heart is clapped；
The computing unit, for calculate each heart clap the DTW residual error of its corresponding K neighbour heart bat of signal to
Amount, and according to the DTW residual vector, obtain the f wave signal that each heart claps signal；
The concatenation unit, for splicing each f wave signal, to complete the extraction to the electrocardiosignal f wave.
Optionally, the enhancement unit is specifically used for clapping signal according to following formula to each heart and carrying out Gauss enhancing,
Wherein, xi(t) indicate that i-th of heart claps the wave amplitude vector of signal, i=1,2,3..., N, N indicates that the heart claps of signal
Number, t indicate that the heart claps the sampling instant of signal,Indicate that i-th of enhanced heart claps the wave amplitude vector of signal, μ indicates high
The expectation of this weighting function, at the time of μ is located at corresponding to the peak R, σ indicates the variance of gaussian weighing function.
Optionally, the computing unit be specifically used for the target heart clap signal corresponding to K target DTW residual vector into
Row is average, obtains the f wave signal that the target heart claps signal；Wherein, it is that all hearts clap signal that the target heart, which claps signal,
In any one heart clap signal.
It optionally, further include filter unit；
The filter unit, for it is described detection electrocardiosignal the peak position R before, to the initial electrocardiosignal of acquisition
It is filtered, obtains filtered electrocardiosignal.
The peak position R of electrocardiosignal is detected it can be seen from above-mentioned technical proposal, and according to each peak position R, by the heart
Electric signal is cut into multiple individually initial hearts and claps signal；Signal is clapped to each initial heart and carries out Gauss enhancing, obtains Gauss enhancing
The heart afterwards claps signal；Using the nearest neighbor algorithm based on DTW distance, determine that each heart claps K neighbour's heart bat of signal.DTW away from
From the morphic similarity that can be well reflected between heart bat signal, variation and R blob detection to QRS complex form are brought
Error it is insensitive, have good robustness, reduce time sampling deviation bring influence.It is improved by Gauss enhancing
Electrocardio claps the weight in calculating in neighbour's heart around the peak R, can find more accurate neighbour's heart and clap, and improves DTW calculation
Correction capability of the method to R blob detection deviation.It calculates each heart and claps the DTW residual vector that its corresponding K neighbour heart of signal is clapped, and
According to the DTW residual vector, the f wave signal that each heart claps signal is obtained；Splice each f wave signal, to complete to the heart
The extraction of electric signal f wave.In the technical scheme, clapped with K neighbour's heart is that template claps signal progress DTW weight to the corresponding heart
Resulting K residual vector is averagely obtained f wave, realizes the correction to R blob detection error by structure, reduces distortion QRS
The influence of wave improves the accuracy of f wave extraction, provides reliable foundation for atrial fibrillation clinical diagnosis.
Detailed description of the invention
In order to illustrate the embodiments of the present invention more clearly, attached drawing needed in the embodiment will be done simply below
It introduces, it should be apparent that, drawings in the following description are only some embodiments of the invention, for ordinary skill people
For member, without creative efforts, it is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of flow chart of electrocardiosignal list lead f wave extracting method provided in an embodiment of the present invention；
Fig. 2 is a kind of structural schematic diagram of electrocardiosignal list lead f wave extraction element provided in an embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, rather than whole embodiments.Based on this
Embodiment in invention, those of ordinary skill in the art are without making creative work, obtained every other
Embodiment belongs to the scope of the present invention.
In order to enable those skilled in the art to better understand the solution of the present invention, with reference to the accompanying drawings and detailed description
The present invention is described in further detail.
Next, a kind of electrocardiosignal list lead f wave extracting method provided by the embodiment of the present invention is discussed in detail.Fig. 1
For a kind of flow chart of electrocardiosignal list lead f wave extracting method provided in an embodiment of the present invention, this method comprises:
S101: detecting the peak position R of electrocardiosignal, and according to each peak position R, electrocardiosignal is cut into multiple individual
The initial heart claps signal.
In the concrete realization, 1 minute patient's electrocardiosignal can be acquired.Then according to the peak position R, by 1 minute heart
Electric signal is divided into one by one individually initial heart bat signal x1,x2,...,xN。
In embodiments of the present invention, it can be calculated using priori knowledge calibration R blob detection algorithm or using pan tompkin
Method realizes the R blob detection of electrocardiosignal.
S102: clapping signal to each initial heart and carry out Gauss enhancing, obtains the enhanced heart of Gauss and claps signal.
In embodiments of the present invention, clapped to find more accurate neighbour's heart, can first to each initial heart clap signal into
Row Gauss enhancing obtains the enhanced heart of Gauss and claps signal.
Because relatively stable in the distribution that the single heart claps f wave energy in signal, and the cardiac electrical wave amplitude of ventricle reaches most at the peak R
Big value, so the cardiac electrical noise of ventricle is relatively high around the peak R.Therefore, in the embodiment of the present invention, can be enhanced by Gauss
To improve weight of the electrocardio in the bat of neighbour's heart calculates around the peak R.
Specifically, signal can be clapped to each initial heart and carry out Gauss enhancing according to following formula,
Wherein, xi(t) indicate that i-th of heart claps the wave amplitude vector of signal, i=1,2,3..., N, N indicates that the heart claps of signal
Number, t indicate that the heart claps the sampling instant of signal,Indicate that i-th of enhanced heart claps the wave amplitude vector of signal, μ indicates high
The expectation of this weighting function, at the time of μ is located at corresponding to the peak R, σ indicates the variance of gaussian weighing function.In practical applications, may be used
To enable σ=20.
Due to the energy highest at the peak R in electrocardiosignal, the signal-to-noise ratio of the electrocardiosignal of surrounding is also higher, is increased by Gauss
It is strong to clap the weight in calculating to improve around the peak R ecg wave form in neighbour's heart, it not only improves and finds more accurate neighbour's heart and clap,
Nearest neighbor algorithm, that is, DTW algorithm pair based on dynamic time warping (Dynamic Time Warping, DTW) distance can be improved again
The correction capability of R blob detection deviation.
S103: using the nearest neighbor algorithm based on DTW distance, determines that each heart claps K neighbour's heart bat of signal.
Because f wave and distortion QRS wave will affect the precision of the peak R positioning, the time between heart bat is clapped so as to cause the heart
Asynchronous sampling, DTW distance can be well reflected the heart clap between morphic similarity, to the variation of QRS complex form with
And R blob detection bring error is insensitive, has good robustness, therefore, in embodiments of the present invention using DTW distance meter
It calculates neighbour's heart to clap, to reduce the influence of time sampling deviation.
Routine techniques is belonged to using K neighbour's heart bat that DTW distance calculates each heart bat signal, details are not described herein.
It should be noted that in embodiments of the present invention, the heart for not carrying out Gauss enhancing bat signal being referred to as the initial heart and is clapped
Signal, the heart mentioned in subsequent content clap signal and each mean that the enhanced heart of Gauss claps signal.Correspondingly, each heart claps signal
The bat of K neighbour's heart refer to that the enhanced heart of Gauss claps signal.
S104: calculating the DTW residual vector that each heart claps its corresponding K neighbour heart bat of signal, and according to DTW residual error to
Amount obtains the f wave signal that each heart claps signal.
The processing mode that each heart claps signal is similar, in embodiments of the present invention intentionally to clap any one in signal
The heart, which is clapped for signal, that is, target heart claps signal, is unfolded explanation.Correspondingly, the target heart can be clapped K neighbour's heart corresponding to signal
It claps and is referred to as K target neighbor heart bat, the target heart is clapped into K DTW residual vector corresponding to signal and is referred to as K target DTW residual error
Vector.
In the concrete realization, can be clapped with the K target neighbor heart is that template claps signal progress DTW reconstruct to the target heart, is asked
The target heart claps the K target DTW residual vector that signal and the K target neighbor heart are clapped out.And to K target DTW residual vector into
Row is average, obtains the f wave signal that the target heart claps signal.
By taking i-th of heart claps signal as an example, its corresponding K neighbour heart bat can be denoted as
The f wave of traditional template opposition method based on KNN is estimated are as follows:
Wherein, [xi-xi,k] it is the residual vector that the target heart claps that corresponding k-th of neighbour heart is clapped.Since each neighbour's heart is clapped
Time sampling it is asynchronous, can not the accurate QRS template of direct estimation, therefore in embodiments of the present invention, with each target neighbor
It is that template claps signal progress DTW reconstruct to the target heart that the heart, which is clapped, and resulting K target DTW residual vector is denoted asK=1,2 ..., K；Then finally estimating for the f wave of i-th of heart bat signal is obtained by mean residual
Meter:
S105: splicing each f wave signal, to complete the extraction to electrocardiosignal f wave.
It is not in apparent distorted signals to make each heart clap the f wave of signal at splicing edge, in the embodiment of the present invention
In, the Bonding Problem of signal edge can be handled using cross-mixing (crossfading) algorithm.It specifically can be according to as follows
The splicing of formula progress f wave:
Wherein, j indicates that j-th of sampled point, L indicate that a heart claps the length of signal, and c indicates boundary parameter.
It emulates and the results showed that with average template method (ABS), optimal template opposition method (WABS), neighbour's template
(KNN-BS) compare, the extracted f wave precision of method used in the embodiment of the present invention is higher.Gauss will not be added enhances operation
F wave extracting method based on DTW distance is named as DTW-BS, and addition Gauss used in the embodiment of the present invention is enhanced to the base of operation
GDTW-BS is named as in the f wave extracting method of DTW distance.It is extracted in emulation in f wave, electrocardiosignal is folded by normal electrocardiosignal
Emulation atrial fibrillation signal is added to generate, wherein emulation f wave is using Stridh M et al. in paper " Spatiotemporal QRST
Cancellation techniques for analysis of atrial fibrillation " in propose method next life
At normal electrocardiosignal is derived from the electrocardiogram (ECG) data of non-patients with atrial fibrillation in PTB database.Using normalized mean squared error
(Normalized mean square error, NMSE) indicates to emulate the accuracy of extracted atrial fibrillation signal.
Wherein, l indicates that the heart claps the sampling length of signal, and S indicates emulation atrial fibrillation signal,Indicate the atrial fibrillation that algorithm extracts
Signal, the value of NMSE can be used to judge the similarity degree between two signals.
It is extracted in experiment in f wave, true atrial fibrillation signal is derived from the electrocardiogram (ECG) data of patients with atrial fibrillation in PTB database.Using institute
The spectrum concentration degree (Spectral Concentration, SC) for extracting f wave signal is used as evaluation index.
Wherein, fFIndicate the centre frequency of the atrial fibrillation signal extracted, FSIndicate sample frequency, fiIndicate frequency value, PAATable
Show the power spectral density of signal.Ventricle of the centre frequency of atrial fibrillation signal generally between 3~10Hz, in the atrial fibrillation signal of extraction
The residual component of signal is generally except the centre frequency of atrial fibrillation signal, therefore SC is higher, shows that the extraction effect of algorithm is better.
Emulation with true atrial fibrillation signal extraction experiment the result shows that, the embodiment of the present invention propose singly leading based on DTW
Connection f wave extracting method can extract more clean f wave from electrocardiosignal, and robustness is higher.
The peak position R of electrocardiosignal is detected it can be seen from above-mentioned technical proposal, and according to each peak position R, by the heart
Electric signal is cut into multiple individually initial hearts and claps signal；Signal is clapped to each initial heart and carries out Gauss enhancing, obtains Gauss enhancing
The heart afterwards claps signal；Using the nearest neighbor algorithm based on DTW distance, determine that each heart claps K neighbour's heart bat of signal.DTW away from
From the morphic similarity that can be well reflected between heart bat signal, variation and R blob detection to QRS complex form are brought
Error it is insensitive, have good robustness, reduce time sampling deviation bring influence.It is improved by Gauss enhancing
Electrocardio claps the weight in calculating in neighbour's heart around the peak R, can find more accurate neighbour's heart and clap, and improves DTW calculation
Correction capability of the method to R blob detection deviation.It calculates each heart and claps the DTW residual vector that its corresponding K neighbour heart of signal is clapped, and
According to the DTW residual vector, the f wave signal that each heart claps signal is obtained；Splice each f wave signal, to complete to the heart
The extraction of electric signal f wave.In the technical scheme, clapped with K neighbour's heart is that template claps signal progress DTW weight to the corresponding heart
Resulting K residual vector is averagely obtained f wave, realizes the correction to R blob detection error by structure, reduces distortion QRS
The influence of wave improves the accuracy of f wave extraction, provides reliable foundation for atrial fibrillation clinical diagnosis.
The various methods of table 1 extract the normalized mean squared error of emulation atrial fibrillation signal:
| NMSE | ABS | WABS | KNN-BS | DTW-BS | GDTW-BS |
| 1 | 0.2674 | 0.2786 | 0.2075 | 0.2209 | 0.2068 |
| 2 | 0.5654 | 0.3501 | 0.4432 | 0.3565 | 0.3411 |
| 3 | 0.3622 | 0.4219 | 0.2523 | 0.2269 | 0.2229 |
| 4 | 0.7107 | 0.6335 | 0.3887 | 0.3154 | 0.3146 |
| 5 | 0.4103 | 0.5317 | 0.3164 | 0.3811 | 0.3049 |
| 6 | 0.6447 | 0.3944 | 0.5572 | 0.5134 | 0.4425 |
| 7 | 0.8325 | 0.7405 | 0.5152 | 0.4174 | 0.4082 |
| 8 | 0.4017 | 0.3411 | 0.3226 | 0.2849 | 0.2744 |
| 9 | 0.2430 | 0.2368 | 0.2573 | 0.2791 | 0.2591 |
| 10 | 0.4677 | 0.4329 | 0.3696 | 0.3738 | 0.3402 |
| Average value | 0.4906 | 0.4361 | 0.3630 | 0.3369 | 0.3115 |
| Standard deviation | 0.1935 | 0.1576 | 0.1152 | 0.0903 | 0.0754 |
The various methods of table 2 extract the spectrum concentration degree of true atrial fibrillation signal:
| SC | ABS | WABS | KNN-BS | DTW-BS | GDTW-BS |
| 1 | 0.4036 | 0.4377 | 0.4064 | 0.3833 | 0.3750 |
| 2 | 0.1726 | 0.1907 | 0.1701 | 0.3995 | 0.4121 |
| 3 | 0.4651 | 0.4745 | 0.4594 | 0.5306 | 0.5446 |
| 4 | 0.5869 | 0.5825 | 0.5647 | 0.5850 | 0.6051 |
| 5 | 0.2944 | 0.1681 | 0.2909 | 0.4127 | 0.4063 |
| 6 | 0.4158 | 0.4153 | 0.4200 | 0.4794 | 0.4823 |
| 7 | 0.3974 | 0.3968 | 0.3969 | 0.4546 | 0.4596 |
| 8 | 0.2677 | 0.3324 | 0.2608 | 0.2908 | 0.2981 |
| 9 | 0.1445 | 0.1063 | 0.1454 | 0.1927 | 0.1851 |
| 10 | 0.3572 | 0.2926 | 0.4196 | 0.4249 | 0.4305 |
| Average value | 0.3505 | 0.3397 | 0.3534 | 0.4155 | 0.4199 |
| Standard deviation | 0.1343 | 0.1506 | 0.1328 | 0.1127 | 0.1191 |
It should be noted that having carried out overstriking processing to data corresponding to optimal index in above table.
In embodiments of the present invention, the accuracy extracted in order to further enhance f wave, can be in the R of detection electrocardiosignal
Before peak position, the initial electrocardiosignal of acquisition is filtered, filtered electrocardiosignal is obtained.
By filtering baseline drift and the T wave that can remove in electrocardiosignal.It can be filtered in practical applications using high pass
Wave device, Butterworth filter, Chebyshev filter or Bessel filter complete the filtering to electrocardiosignal.
For acquiring 1 minute patient's electrocardiosignal, filter can be realized using 4 hertz of high-pass filter accordingly
Wave.
Fig. 2 is a kind of structural schematic diagram of electrocardiosignal list lead f wave extraction element provided in an embodiment of the present invention, including
Cutter unit 21, enhancement unit 22, determination unit 23, computing unit 24 and concatenation unit 25；
Electrocardiosignal is cut by cutter unit 21 for detecting the peak position R of electrocardiosignal, and according to each peak position R
Multiple individually initial hearts clap signal；
Enhancement unit 22 carries out Gauss enhancing for clapping signal to each initial heart, obtains the enhanced heart of Gauss and claps signal；
Determination unit 23 determines that each heart claps K neighbour of signal for using the nearest neighbor algorithm based on DTW distance
The heart is clapped；
Computing unit 24, the DTW residual vector clapped for calculating its corresponding K neighbour heart of each heart bat signal, and according to
According to DTW residual vector, the f wave signal that each heart claps signal is obtained；
Concatenation unit 25, for splicing each f wave signal, to complete the extraction to electrocardiosignal f wave.
Optionally, enhancement unit is specifically used for clapping signal according to following formula to each heart and carrying out Gauss enhancing,
Wherein, xi(t) indicate that i-th of heart claps the wave amplitude vector of signal, i=1,2,3..., N, N indicates that the heart claps of signal
Number, t indicate that the heart claps the sampling instant of signal,Indicate that i-th of enhanced heart claps the wave amplitude vector of signal, μ indicates high
The expectation of this weighting function, at the time of μ is located at corresponding to the peak R, σ indicates the variance of gaussian weighing function.
Optionally, computing unit is specifically used for carrying out K target DTW residual vector corresponding to target heart bat signal flat
, the f wave signal that the target heart claps signal is obtained；Wherein, the target heart is clapped signal and is clapped intentionally to clap any one heart in signal
Signal.
It optionally, further include filter unit；
Filter unit, for being filtered to the initial electrocardiosignal of acquisition before the peak position R of detection electrocardiosignal
Wave obtains filtered electrocardiosignal.
The explanation of feature may refer to the related description of embodiment corresponding to Fig. 1 in embodiment corresponding to Fig. 2, here no longer
It repeats one by one.
The peak position R of electrocardiosignal is detected it can be seen from above-mentioned technical proposal, and according to each peak position R, by the heart
Electric signal is cut into multiple individually initial hearts and claps signal；Signal is clapped to each initial heart and carries out Gauss enhancing, obtains Gauss enhancing
The heart afterwards claps signal；Using the nearest neighbor algorithm based on DTW distance, determine that each heart claps K neighbour's heart bat of signal.DTW away from
From the morphic similarity that can be well reflected between heart bat signal, variation and R blob detection to QRS complex form are brought
Error it is insensitive, have good robustness, reduce time sampling deviation bring influence.It is improved by Gauss enhancing
Electrocardio claps the weight in calculating in neighbour's heart around the peak R, can find more accurate neighbour's heart and clap, and improves DTW calculation
Correction capability of the method to R blob detection deviation.It calculates each heart and claps the DTW residual vector that its corresponding K neighbour heart of signal is clapped, and
According to the DTW residual vector, the f wave signal that each heart claps signal is obtained；Splice each f wave signal, to complete to the heart
The extraction of electric signal f wave.In the technical scheme, clapped with K neighbour's heart is that template claps signal progress DTW weight to the corresponding heart
Resulting K residual vector is averagely obtained f wave, realizes the correction to R blob detection error by structure, reduces distortion QRS
The influence of wave improves the accuracy of f wave extraction, provides reliable foundation for atrial fibrillation clinical diagnosis.
It is provided for the embodiments of the invention a kind of electrocardiosignal list lead f wave extracting method above and device has carried out in detail
It is thin to introduce.Each embodiment is described in a progressive manner in specification, the highlights of each of the examples are with other realities
The difference of example is applied, the same or similar parts in each embodiment may refer to each other.For device disclosed in embodiment
Speech, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is referring to method part illustration
?.It should be pointed out that for those skilled in the art, without departing from the principle of the present invention, also
Can be with several improvements and modifications are made to the present invention, these improvement and modification also fall into the protection scope of the claims in the present invention
It is interior.
Professional further appreciates that, unit described in conjunction with the examples disclosed in the embodiments of the present disclosure
And algorithm steps, can be realized with electronic hardware, computer software, or a combination of the two, in order to clearly demonstrate hardware and
The interchangeability of software generally describes each exemplary composition and step according to function in the above description.These
Function is implemented in hardware or software actually, the specific application and design constraint depending on technical solution.Profession
Technical staff can use different methods to achieve the described function each specific application, but this realization is not answered
Think beyond the scope of this invention.
The step of method described in conjunction with the examples disclosed in this document or algorithm, can directly be held with hardware, processor
The combination of capable software module or the two is implemented.Software module can be placed in random access memory (RAM), 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.
Claims (8)
1. a kind of electrocardiosignal list lead f wave extracting method characterized by comprising
The peak position R of electrocardiosignal is detected, and according to each peak position R, the electrocardiosignal is cut into multiple individual
The initial heart claps signal；
Signal is clapped to each initial heart and carries out Gauss enhancing, the enhanced heart of Gauss is obtained and claps signal；
Using the nearest neighbor algorithm based on DTW distance, determine that each heart claps K neighbour's heart bat of signal；
Calculate the DTW residual vector that each heart claps its corresponding K neighbour heart bat of signal, and according to the DTW residual error to
Amount obtains the f wave signal that each heart claps signal；
Splice each f wave signal, to complete the extraction to the electrocardiosignal f wave.
2. being obtained the method according to claim 1, wherein described clap signal progress Gauss enhancing to each heart
Clapping signal to the enhanced heart of Gauss includes:
According to following formula, signal is clapped to each heart and carries out Gauss enhancing,
Wherein, xi(t) indicate that i-th of heart claps the wave amplitude vector of signal, i=1,2,3..., N, N indicates that the heart claps the number of signal, t
Indicate that the heart claps the sampling instant of signal,Indicate that i-th of enhanced heart claps the wave amplitude vector of signal, μ indicates that Gauss adds
The expectation of weight function, at the time of μ is located at corresponding to the peak R, σ indicates the variance of gaussian weighing function.
3. obtaining each heart the method according to claim 1, wherein described according to the DTW residual vector
Clap signal f wave signal include:
K target DTW residual vector corresponding to signal is clapped to the target heart to be averaged, and obtains the f that the target heart claps signal
Wave signal；Wherein, it is that any one heart that all hearts are clapped in signal claps signal that the target heart, which claps signal,.
4. method according to claim 1 to 3, which is characterized in that in the R peak position of the detection electrocardiosignal
Before setting further include:
The initial electrocardiosignal of acquisition is filtered, filtered electrocardiosignal is obtained.
5. a kind of electrocardiosignal list lead f wave extraction element, which is characterized in that including cutter unit, enhancement unit, determine list
Member, computing unit and concatenation unit；
The cutter unit, for detecting the peak position R of electrocardiosignal, and according to each peak position R, by the electrocardiosignal
It is cut into multiple individually initial hearts and claps signal；
The enhancement unit carries out Gauss enhancing for clapping signal to each initial heart, obtains the enhanced heart of Gauss and clap letter
Number；
The determination unit determines that each heart claps K neighbour's heart of signal for using the nearest neighbor algorithm based on DTW distance
It claps；
The computing unit claps the DTW residual vector that its corresponding K neighbour heart of signal is clapped for calculating each heart, and
According to the DTW residual vector, the f wave signal that each heart claps signal is obtained；
The concatenation unit, for splicing each f wave signal, to complete the extraction to the electrocardiosignal f wave.
6. device according to claim 5, which is characterized in that the enhancement unit is specifically used for according to following formula, right
Each heart claps signal and carries out Gauss enhancing,
Wherein, xi(t) indicate that i-th of heart claps the wave amplitude vector of signal, i=1,2,3..., N, N indicates that the heart claps the number of signal, t
Indicate that the heart claps the sampling instant of signal,Indicate that i-th of enhanced heart claps the wave amplitude vector of signal, μ indicates that Gauss adds
The expectation of weight function, at the time of μ is located at corresponding to the peak R, σ indicates the variance of gaussian weighing function.
7. device according to claim 5, which is characterized in that the computing unit is specifically used for clapping signal institute to the target heart
Corresponding K target DTW residual vector is averaged, and the f wave signal that the target heart claps signal is obtained；Wherein, the target
It is that any one heart that all hearts are clapped in signal claps signal that the heart, which claps signal,.
8. according to device described in claim 5-7 any one, which is characterized in that further include filter unit；
The filter unit, for being carried out to the initial electrocardiosignal of acquisition before the peak position R of the detection electrocardiosignal
Filtering, obtains filtered electrocardiosignal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910477520.4A CN110063726B (en) | 2019-06-03 | 2019-06-03 | Electrocardiosignal single-lead f-wave extraction method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910477520.4A CN110063726B (en) | 2019-06-03 | 2019-06-03 | Electrocardiosignal single-lead f-wave extraction method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110063726A true CN110063726A (en) | 2019-07-30 |
| CN110063726B CN110063726B (en) | 2021-08-13 |
Family
ID=67372400
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910477520.4A Active CN110063726B (en) | 2019-06-03 | 2019-06-03 | Electrocardiosignal single-lead f-wave extraction method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110063726B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112244861A (en) * | 2020-10-09 | 2021-01-22 | 广东工业大学 | Single-lead electrocardiosignal f-wave extraction method |
| CN112716498A (en) * | 2020-12-29 | 2021-04-30 | 北京理工大学 | Electrocardiosignal feature extraction method based on dynamic time warping and symbolic dynamics |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070021679A1 (en) * | 2002-09-19 | 2007-01-25 | Narayan Sanjiv M | Method and apparatus for classifying and localizing heart arrhythmias |
| US20140249424A1 (en) * | 2012-12-04 | 2014-09-04 | University Of Winnipeg | Cardiovascular pulse wave analysis method and system |
| CN108926348A (en) * | 2018-08-06 | 2018-12-04 | 广东工业大学 | A kind of extracting method and device of atrial fibrillation signal |
| CN109645985A (en) * | 2019-02-22 | 2019-04-19 | 南京大学 | The method that a kind of pair of peak single channel pregnant woman stomach wall electricity maternal ecg R is detected |
-
2019
- 2019-06-03 CN CN201910477520.4A patent/CN110063726B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070021679A1 (en) * | 2002-09-19 | 2007-01-25 | Narayan Sanjiv M | Method and apparatus for classifying and localizing heart arrhythmias |
| US20140249424A1 (en) * | 2012-12-04 | 2014-09-04 | University Of Winnipeg | Cardiovascular pulse wave analysis method and system |
| CN108926348A (en) * | 2018-08-06 | 2018-12-04 | 广东工业大学 | A kind of extracting method and device of atrial fibrillation signal |
| CN109645985A (en) * | 2019-02-22 | 2019-04-19 | 南京大学 | The method that a kind of pair of peak single channel pregnant woman stomach wall electricity maternal ecg R is detected |
Non-Patent Citations (1)
| Title |
|---|
| 张凯等: "心电信号自动检测的小波变换方法", 《扬州大学学报(自然科学版)》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112244861A (en) * | 2020-10-09 | 2021-01-22 | 广东工业大学 | Single-lead electrocardiosignal f-wave extraction method |
| CN112716498A (en) * | 2020-12-29 | 2021-04-30 | 北京理工大学 | Electrocardiosignal feature extraction method based on dynamic time warping and symbolic dynamics |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110063726B (en) | 2021-08-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US5609158A (en) | Apparatus and method for predicting cardiac arrhythmia by detection of micropotentials and analysis of all ECG segments and intervals | |
| CN101828918B (en) | Electrocardiosignal R peak detection method based on waveform characteristic matching | |
| Sun et al. | An improved morphological approach to background normalization of ECG signals | |
| Jang et al. | A real-time pulse peak detection algorithm for the photoplethysmogram | |
| EP3003140A1 (en) | Electrocardiogram analysis | |
| CN109009073A (en) | Atrial fibrillation detection apparatus and storage medium | |
| Malek et al. | Automated detection of premature ventricular contraction in ECG signals using enhanced template matching algorithm | |
| CN110063726A (en) | A kind of electrocardiosignal list lead f wave extracting method and device | |
| Chin et al. | Bayesian real-time QRS complex detector for healthcare system | |
| CN103054572A (en) | Blind source separation method on basis of late potential signals of single-lead cardiac ventricle | |
| CN109157220B (en) | Respiratory index extraction system based on multi-channel dynamic monitoring and working method | |
| CA2253760A1 (en) | Predicting cardiac arrhythmia by detection of micropotentials | |
| KR20150009843A (en) | System for classification electrocardiogram signals | |
| CN108784683B (en) | ECG machine including filter for feature detection | |
| Hu et al. | Feature extraction and choice in PCG based on Hilbert Transfer | |
| CN103417208A (en) | Atrial fibrillation detection device and detection method | |
| CN109044338A (en) | Atrial fibrillation detection apparatus and storage medium | |
| Ghaffari et al. | Detecting and quantifying T-wave alternans using the correlation method and comparison with the FFT-based method | |
| Jemilehin et al. | Design and Simulation of Electrocardiogram Circuit with Automatic Analysis of ECG Signal. | |
| Atbi et al. | Heart sounds and heart murmurs sepataion | |
| Giordano et al. | A method for the estimation of the timing of heart sound components through blind source separation in multi-source phonocardiography | |
| Ahmad et al. | An improved QRS complex detection for online medical diagnosis | |
| Uddin et al. | ECG Arryhthmia Classifier | |
| Baas et al. | Comparison of three t-wave delineation algorithms based on wavelet filterbank, correlation and pca | |
| Szilágyi et al. | Modifications in Arruda’s localization method in left ventricle analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |