A New Time Varying Adaptive Filtering System (TVAFS) for Ambulatory ECG Signals

Ambulatory ECG signal gets coupled with various noises. Noise and ECG signal are non-stationary in nature. Filtering system, an essential part of the ambulatory ECG system, needs to be less complex so as to minimize the overall processing cost. Present paper proposed time varying adaptive filtering system comprising of complexity reduced variable step size algorithm and a cascaded digital FIR filter. The MIT/BIH arrhythmia dataset has been used to evaluate the proposed system. Results obtained in terms of improved SNR and fast converging learning rate demonstrate that the proposed system can effectively remove noise compared with other popular adaptive filters.

[1]  Junghsi Lee,et al.  A New Variable Step-Size NLMS Algorithm and Its Performance Analysis , 2012, IEEE Transactions on Signal Processing.

[2]  C. Van Hoof,et al.  Motion artifact removal using cascade adaptive filtering for ambulatory ECG monitoring system , 2012, 2012 IEEE Biomedical Circuits and Systems Conference (BioCAS).

[3]  Yunfeng Wu,et al.  Filtering electrocardiographic signals using an unbiased and normalized adaptive noise reduction system. , 2009, Medical engineering & physics.

[4]  Alireza K. Ziarani,et al.  A nonlinear adaptive method of elimination of power line interference in ECG signals , 2002, IEEE Transactions on Biomedical Engineering.

[5]  Roland Maas,et al.  The NLMS Algorithm with Time-Variant Optimum Stepsize Derived from a Bayesian Network Perspective , 2014, IEEE Signal Processing Letters.

[6]  H. B. Riley,et al.  Performance Study of Different Denoising Methods for ECG Signals , 2014, EUSPN/ICTH.

[7]  Mohammad Pooyan,et al.  ECG SIGNALS NOISE REMOVAL: SELECTION AND OPTIMIZATION OF THE BEST ADAPTIVE FILTERING ALGORITHM BASED ON VARIOUS ALGORITHMS COMPARISON , 2015 .

[8]  Henning Puder,et al.  Step-size control for acoustic echo cancellation filters - an overview , 2000, Signal Process..

[9]  P.S. Hamilton,et al.  Comparison of methods for adaptive removal of motion artifact , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[10]  Steven L. Grant,et al.  Novel variable step size nlms algorithms for echo cancellation , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[11]  Dinesh Kumar,et al.  Performance Comparison and Applications of Sparsity Based Techniques for Denoising of ECG Signal , 2019, 2019 6th International Conference on Signal Processing and Integrated Networks (SPIN).

[12]  Jacob Benesty,et al.  A Nonparametric VSS NLMS Algorithm , 2006, IEEE Signal Processing Letters.

[13]  J. Mahil,et al.  Optimization algorithms for adaptive filtering of interferences in corrupted signal , 2015 .

[14]  Reeta Devi,et al.  A novel multi-class approach for early-stage prediction of sudden cardiac death , 2019, Biocybernetics and Biomedical Engineering.

[15]  Radek Martinek,et al.  Least Mean Squares and Recursive Least Squares Algorithms for Total Harmonic Distortion Reduction Using Shunt Active Power Filter Control , 2019, Energies.

[16]  Ronald Wilders,et al.  Effects of the transient outward potassium current on action potential upstroke velocities tested using the dynamic clamp technique , 2016, 2016 Computing in Cardiology Conference (CinC).

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

[18]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[19]  Jian Yang,et al.  Motion artifact suppression in ambulatory ECG with feed forward combined adaptive filter , 2016, 2016 Computing in Cardiology Conference (CinC).