A Method for Eliminating the Baseline Drift of ECG Signal Based on Sparse Matrix
A sparse matrix and baseline drift technology, applied in medical science, diagnosis, diagnostic recording/measurement, etc., can solve problems such as difficulty in threshold value selection, loss of decomposition results, and great signal influence, so as to maximize the use of data and reduce data loss. Complexity, the effect of eliminating baseline drift
Active Publication Date: 2019-04-05
SHANDONG COMP SCI CENTNAT SUPERCOMP CENT IN JINAN
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Problems solved by technology
[0003] The design of the high-pass filtering method requires a particularly large number of filtering orders and a large amount of calculation. At the same time, it is easy to cause distortion of the ECG waveform. Among them, the wavelet threshold method based on wavelet theory has a great influence on the signal and the operation is complicated.
Although the EMD decomposition method overcomes the difficulty of threshold value selection in wavelet transform, the distortion of the decomposed and recombined ECG signal is relatively serious, making the decomposition result meaningless
The fitting base drift method is not effective when dealing with large drift ECG waveform signals, and cannot achieve a good effect of eliminating baseline drift.
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[0023] This embodiment discloses a method for eliminating baseline drift of an ECG signal based on a sparse matrix, which specifically includes the following steps:
[0024] S01), load the ECG data, the ECG data is input in the form of matrix S, the matrix S is the data of N rows and 1 column, and all the data of the extracted matrix S is y, N=length(y), indicating the length of the loaded data ;
[0025] S02), setting the cutoff frequency fc of the filter, the filter order d, the ratio coefficient r, and setting the constraint parameters α and λ;
[0026] S03), calculate banded sparse matrix A, B, calculation process is: set parameter matrix a1, b1, define Omc=2*π*fc, t=((1-cos(omc)) / (1+cos(omc ))) d , and then perform d convolution operations on matrix a1, b1 respectively to obtain a2, b2, and then perform convolution operation on b2 and [-1 1] to obtain matrix b, matrix a=b+t*a2, use matrix a, b Perform sparse operations on A and B matrices to obtain two sparse banded ma...
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The invention discloses a method for eliminating ECG signal baseline drift based on a sparse matrix. The method comprises the following steps: modeling the sparse matrix based on ECG peak signals, andmodeling low-pass signals from baseline signals; and calculating ECG signals and a baseline after baseline drift through a sparse matrix algorithm. The method provided by the invention has the advantages of being easy to operate, high in running speed and capable of avoiding easy distortion of an electrocardiogram; the baseline drift can be eliminated by taking zero graduation as a baseline; therefore, a purpose of eliminating baseline drift of the ECG signals can be actually achieved; and the method makes use of QSR wave detection. Data complexity can be reduced based upon sparse representation of the sparse matrix; and all information in the data can be fully developed and redundant data information can be removed, so that the maximum utilization of the data is achieved.
Description
technical field [0001] The invention relates to a method for eliminating baseline drift in ECG signals, in particular to a method for eliminating baseline drift of ECG signals based on a sparse matrix. Background technique [0002] An electrocardiogram (ECG) is a graph of potential changes related to heart activity. The baseline drift noise interference problem in ECG signals has a long history, mainly caused by the person being recorded breathing, and cannot be avoided. Baseline drift will elevate the ST band of the ECG electrocardiogram, causing serious distortion of the ECG trace, thereby affecting normal medical judgment. At present, many methods to eliminate the baseline drift of ECG signals have been proposed and applied at home and abroad. The filtering method and the fitting base drift method are the two main methods. Among them, the filter method is an important algorithm for suppressing and preventing interference, and the fitting base drift method is an algorith...
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IPC IPC(8): A61B5/0402A61B5/04
CPCA61B5/316A61B5/318
Inventor 舒明雷王枭王英龙朱清杨美红杨明董安明
Owner SHANDONG COMP SCI CENTNAT SUPERCOMP CENT IN JINAN