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Muscle and electrode motion artifacts reduction in ECG using adaptive fourier decomposition
Wang Z.; Wong C.M.; Da Cruz J.N.; Wan F.; Mak P.-I.; Mak P.U.; Vai M.I.
Conference NameIEEE International Conference on Systems, Man, and Cybernetics (SMC)
Source PublicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Conference DateOCT 05-08, 2014
Conference PlaceSan Diego, CA

The reduction of the muscle and electrode motion artifacts in ECG using the adaptive Fourier decomposition (AFD) is investigated. This is an extension of our previous work, in which AFD is first proposed for ECG denoising and its effectiveness in filtering out the additive Gaussian white noise is tested. This paper studies the AFD-based ECG denoising method for two types of ECG noise due to the electrode movement and the muscle contraction which are common and important in practice. In addition, some rules on the selection and adjustment of the AFD decomposition level are proposed. The tests on the MIT-BIH Arrhythmia Database indicate that this AFD-based denoising scheme performs better than the Butterworth lowpass filter, the wavelet transform and the empirical mode decomposition methods for ECG denoising with the muscle movement and electrode motion artifacts.

KeywordAdaptive Fourier Decomposition Ecg Signal Denoising Electrode Motion Artifact Muscle Artifact
URLView the original
Indexed BySCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics ; Computer Science, Information Systems
WOS IDWOS:000370963701097
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Cited Times [WOS]:8   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Wang Z.,Wong C.M.,Da Cruz J.N.,et al. Muscle and electrode motion artifacts reduction in ECG using adaptive fourier decomposition[C],2014:1456-1461.
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