Performance analysis of adaptive filtering algorithms for denoising of ECG signals

Electrocardiogram (ECG) can help to diagnose range of diseases including heart arrhythmias, heart enlargement, heart inflammation (pericarditis or myocarditis) and coronary heart disease. ECG consists of noise which is non stationary that affects the reliability of ECG waveform. In this paper an adaptive filter for denoising ECG signal based on Least Mean Squares (LMS), Normalized Least Mean Square (NLMS), Affine Projection LMS (APA-LMS) and Recursive least Squares algorithm (RLS) is presented with experimental results and the results are found to be encouraging. The performances of these algorithms are compared in terms of various parameters such as SNR, PSNR, MSE and SD. To validate the proposed methods, real time recorded data from the MIT-BIH database is used. RLS algorithm is found to exhibit lower MSE, and higher SNR compared to other algorithms. Therefore the results demonstrate superior performance of adaptive RLS filter for denoising of ECG signal.

[1]  Wei Zhang,et al.  Enhancement of ECG Signals by Multi-Resolution Sub-Band Filter , 2008, 2008 2nd International Conference on Bioinformatics and Biomedical Engineering.

[2]  PooGyeon Park,et al.  An Affine Projection Algorithm Based on Reuse Time of Input Vectors , 2010, IEEE Signal Processing Letters.

[3]  Kazuhiko Ozeki,et al.  An adaptive filtering algorithm using an orthogonal projection to an affine subspace and its properties , 1984 .

[4]  P. de Chazel,et al.  A comparison of the ECG classification performance of different feature sets , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[5]  Javier Calpe-Maravilla,et al.  An easy demonstration of the optimum value of the adaptation constant in the LMS algorithm [FIR filt , 1998 .

[6]  H. T. Nagle,et al.  A comparison of the noise sensitivity of nine QRS detection algorithms , 1990, IEEE Transactions on Biomedical Engineering.

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

[9]  Jeih-Weih Hung,et al.  Data-driven temporal filters based on multi-eigenvectors for robust features in speech recognition , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[10]  Dennis R. Morgan,et al.  On a class of computationally efficient, rapidly converging, generalized NLMS algorithms , 1996, IEEE Signal Processing Letters.

[11]  S. G. Sankaran.  STEREOPHONIC ACOUSTIC ECHO CANCELLATION USING NLMS WITH ORTHOGONAL CORRECTION FACTORS , 1999 .

[12]  R. Mehra.  Global public health problem of sudden cardiac death. , 2007, Journal of electrocardiology.

[13]  Paulo S. R. Diniz,et al.  Adaptive Filtering: Algorithms and Practical Implementation , 1997 .

[14]  S. Thomas Alexander,et al.  Adaptive Signal Processing , 1986, Texts and Monographs in Computer Science.

[15]  A. Bhavani Sankar,et al.  Performance Study of Various Adaptive Filter Algorithms for Noise Cancellation in Respiratory Signals , 2010 .

[16]  Piet C. W. Sommen,et al.  Realization of an acoustic echo canceller on a single DSP , 1996, 1996 8th European Signal Processing Conference (EUSIPCO 1996).

[17]  A. A. Beex,et al.  Convergence behavior of affine projection algorithms , 2000, IEEE Trans. Signal Process..

[18]  P. H. Zope,et al.  Filtering Techniques for Reduction of Power Line Interference in Electrocardiogram Signals , 2012 .

[19]  I. Ahmad,et al.  CANCELLATION OF MOTION ARTIFACT NOISE AND POWER LINE INTERFERENCE IN ECG USING ADAPTIVE FILTERS , 2013 .

[20]  Jean-Yves Tourneret,et al.  An affine combination of two NLMS adaptive filters - Transient mean-square analysis , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

[21]  Christian Callegari,et al.  Advances in Computing, Communications and Informatics (ICACCI) , 2015 .

[22]  Li Xiang-chen,et al.  An Improved RLS Adaptive Filter Algorithm Used to Process Human Body Balance Signal , 2011, 2011 International Conference on Future Computer Science and Education.

[23]  Jyoti Dhiman,et al.  Comparison between Adaptive filter Algorithms (LMS, NLMS and RLS) , 2013 .

[24]  R. Warlar,et al.  Integer coefficient bandpass filter for the simultaneous removal of baseline wander, 50 and 100 Hz interference from the ECG , 1991, Medical and Biological Engineering and Computing.