Empirical Mode Decomposition-based Subtraction Techniques for 50 Hz Interference Reduction from Electrocardiogram

Abstract In general, most of the Biomedical signals such as Electrocardiogram (ECG), Electroencephalogram, and Electro-oculogram are nonstationary signals, suffers from different interferences like power line interference (PLI) and with other biomedical signals that gets added with it. Analysis of these signals means the extraction of useful information from the signal, and in this paper it is carried out using a new nonlinear and nonstationary data analysis method called Empirical Mode Decomposition (EMD). The key feature of this method is that it can decompose the signal into different IMFs and makes the analysis simple. Compared with other tools like Fourier analysis and wavelet methods, EMD is purely a data-driven and adaptive technique. Thus, it is well suited to analyze nonstationary signals like biosignals. This paper foregrounds an EMD-based, two-weight adaptive Alter structure to reduce the PLI in ECG signals. Two methodologies are studied based on EMD and the simulations are carried out in a MATLAB environment. The denoised signals are visually impressive and the methodologies are well suited for real-time implementation.

[1]  S. Poornachandra,et al.  A novel method for the elimination of power line frequency in ECG signal using hyper shrinkage function , 2008, Digit. Signal Process..

[2]  Allan Kardec Barros,et al.  independent , 2006, Gumbo Ya Ya.

[3]  P.S. Hamilton,et al.  A comparison of adaptive and nonadaptive filters for reduction of power line interference in the ECG , 1996, IEEE Transactions on Biomedical Engineering.

[4]  Jacek M. Leski,et al.  ECG baseline wander and powerline interference reduction using nonlinear filter bank , 2005, Signal Process..

[5]  N.V. Thakor,et al.  Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection , 1991, IEEE Transactions on Biomedical Engineering.

[6]  Chavdar Levkov,et al.  Removal of power-line interference from the ECG: a review of the subtraction procedure , 2005, Biomedical engineering online.

[7]  Abdel-Ouahab Boudraa,et al.  EMD-Based Signal Filtering , 2007, IEEE Transactions on Instrumentation and Measurement.

[8]  Danilo P. Mandic,et al.  Filter Bank Property of Multivariate Empirical Mode Decomposition , 2011, IEEE Transactions on Signal Processing.

[9]  M. S. Woolfson,et al.  Application of empirical mode decomposition to heart rate variability analysis , 2001, Medical and Biological Engineering and Computing.

[10]  David L. Donoho,et al.  De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.

[11]  N. Huang,et al.  A study of the characteristics of white noise using the empirical mode decomposition method , 2004, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[12]  Manuel Blanco-Velasco,et al.  ECG signal denoising and baseline wander correction based on the empirical mode decomposition , 2008, Comput. Biol. Medicine.

[13]  Gabriel Rilling,et al.  Empirical mode decomposition as a filter bank , 2004, IEEE Signal Processing Letters.

[14]  M. Ferdjallah,et al.  Adaptive digital notch filter design on the unit circle for the removal of powerline noise from biomedical signals , 1994, IEEE Transactions on Biomedical Engineering.

[15]  S. Poornachandra,et al.  Hyper-trim shrinkage for denoising of ECG signal , 2005, Digit. Signal Process..

[16]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[17]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[18]  Peter Strobach.  Single section least squares adaptive notch filter , 1995, IEEE Trans. Signal Process..

[19]  H. Liang,et al.  Artifact reduction in electrogastrogram based on empirical mode decomposition method , 2006, Medical and Biological Engineering and Computing.

[20]  K. M. Kim,et al.  Simple self-tuned notch filter in a bio-potential amplifier , 2006, Medical and Biological Engineering and Computing.