Baseline drift removal and denoising of MCG data using EEMD: role of noise amplitude and the thresholding effect.

Abstract:

:We adopt the Ensemble Empirical Mode Decomposition (EEMD) method, with an appropriate thresholding on the Intrinsic Mode Functions (IMFs), to denoise the magnetocardiography (MCG) signal. To this end, we discuss the two associated problems that relate to: (i) the amplitude of noise added to the observed signal in the EEMD method with a view to prevent mode mixing and (ii) the effect of direct thresholding that causes discontinuities in the reconstructed denoised signal. We then denoise the MCG signals, having various signal-to-noise ratios, by using this method and compare the results with those obtained by the standard wavelet based denoising method. We also address the problem of eliminating the high frequency baseline drift such as the sudden and discontinuous changes in the baseline of the experimentally measured MCG signal using the EEMD based method. We show that the EEMD method used for denoising and the elimination of baseline drift is superior in performance to other standard methods such as wavelet based techniques and Independent Component Analysis (ICA).

journal_name

Med Eng Phys

authors

Mariyappa N,Sengottuvel S,Parasakthi C,Gireesan K,Janawadkar MP,Radhakrishnan TS,Sundar CS

doi

10.1016/j.medengphy.2014.06.023

subject

Has Abstract

pub_date

2014-10-01 00:00:00

pages

1266-76

issue

10

eissn

1350-4533

issn

1873-4030

pii

S1350-4533(14)00185-4

journal_volume

36

pub_type

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