On-line Local Mean Decomposition and its application to ECG signal denoising

Author

Hsea-Ching Hsueh ; Shao-Yi Chien

Author_Institution

Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan

fYear

2014

fDate

22-24 Oct. 2014

Firstpage

17

Lastpage

20

Abstract

Local Mean Decomposition (LMD) has long been proven as an effective method for the analysis of non-linear and non-stationary time series. In this work, an on-line version of LMD, called extended Sliding Local Mean Decomposition (eSLMD), is proposed. The property of eSLMD is examined through numerical simulations, and the performance is evaluated through the ECG noise removal with the test signal obtained from MIT-BIH arrhythmia ECG database. The results show that the proposed eSLMD has better decomposition performance than conventional LMD, and is potentially well suited for on-line and real-time biomedical applications.

Keywords

electrocardiography; medical signal processing; signal denoising; time series; ECG noise removal; ECG signal denoising; MIT-BIH arrhythmia ECG database; eSLMD method; extended Sliding Local Mean Decomposition; nonlinear time series; nonstationary time series; online local mean decomposition; Electrocardiography; Empirical mode decomposition; Loading; Noise; Noise measurement; Power demand; Signal denoising; ECG signal denoising; eSLMD; extended Sliding Local Mean Decomposition; on-line EMD; on-line LMD; sliding EMD; sliding LMD;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Circuits and Systems Conference (BioCAS), 2014 IEEE

Conference_Location

Lausanne

Type

conf

DOI

10.1109/BioCAS.2014.6981634

Filename

6981634