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Extended Kalman smoother with differential evolution technique for denoising of ECG signal.

Abstract：

:Electrocardiogram (ECG) signal gives a lot of information on the physiology of heart. In reality, noise from various sources interfere with the ECG signal. To get the correct information on physiology of the heart, noise cancellation of the ECG signal is required. In this paper, the effectiveness of extended Kalman smoother (EKS) with the differential evolution (DE) technique for noise cancellation of the ECG signal is investigated. DE is used as an automatic parameter selection method for the selection of ten optimized components of the ECG signal, and those are used to create the ECG signal according to the real ECG signal. These parameters are used by the EKS for the development of the state equation and also for initialization of the parameters of EKS. EKS framework is used for denoising the ECG signal from the single channel. The effectiveness of proposed noise cancellation technique has been evaluated by adding white, colored Gaussian noise and real muscle artifact noise at different SNR to some visually clean ECG signals from the MIT-BIH arrhythmia database. The proposed noise cancellation technique of ECG signal shows better signal to noise ratio (SNR) improvement, lesser mean square error (MSE) and percent of distortion (PRD) compared to other well-known methods.

journal_name

Australas Phys Eng Sci Med

journal_title

Australasian physical & engineering sciences in medicine

authors

Panigrahy D,Sahu PK

doi

10.1007/s13246-016-0468-4

subject

Has Abstract

pub_date

2016-09-01 00:00:00

pages

783-95

issue

3

eissn

0158-9938

issn

1879-5447

pii

10.1007/s13246-016-0468-4

journal_volume

39

pub_type

杂志文章

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