UNITED STATES
Performance Analysis of different filters for power line interface reduction in ECG signal
|
10.5120/746-1055 |
Yatindra Kumar and Gorav Kumar Malik. Article:Performance Analysis of different filters for power line interface reduction in ECG signal. International Journal of Computer Applications 3(7):1–6, June 2010. Published By Foundation of Computer Science. BibTeX
@article{key:article,
author = {Yatindra Kumar and Gorav Kumar Malik},
title = {Article:Performance Analysis of different filters for power line interface reduction in ECG signal},
journal = {International Journal of Computer Applications},
year = {2010},
volume = {3},
number = {7},
pages = {1--6},
month = {June},
note = {Published By Foundation of Computer Science}
}
Abstract
Over the years Computer aided analysis of ECG signal is gaining with tremendous amount of work being carried out all over the world. This paper is a small step on our part in that direction, ECG Electrocardiogram signal most comely known recognized and used biomedical signal, the ECG signal is very sensitive in nature, and even if small noise mixed with original signal the various characteristics of the signal changes, Data corrupted with noise must either filtered or discarded, filtering is important issue for design consideration of real time heart monitoring systems. The purpose of this paper is to quantify relative performance analysis of different filtering methods for power line interface reduction.
The data base for the performance analysis is created by simulation of ECG signal , an ideal ECG signal is best for performance analysis, then data base is corrupted with 50 Hz power line interface ,the ability of different filter (use IIR Notch , Wiener, adaptive filter) are checked by changes in filtered signal, signal to noise ratio, Power of the signal, Power spectral density ,spectrogram of the signal , The location of peaks and its amplitude also measured by Pan Tompkins algorithm for performance analysis of filters. The results have clearly indicated that there is reduction in Power line noise in the ECG signal changes according to filter, and the best result is shown by adaptive filter we can see it easily in spectrogram, The results have been concluded using Mat lab and Simulated ECG database.
Reference
-
Rangaraj M. Rangayyan, 2005, Bio Medical signal analysis a case study approach, IEEE Press, JOHN WILEY & SONS, INC
Tompkins WJ. Biomedical Digital Signal Processing. Prentice-Hall, Upper Saddle River, NJ, 1995.
Peter handel “Analysis of notch filter with constrained pole zero” IEEE Transactions on signal processing, vol. 42 1994.
J.C.Huhta and J.G.Webster, 60-Hz interference in electrocardiography. IEEE Trans. Biomedical. Eng. 1973; 43:91–101.
S.Pooranchandra, N.Kumaravel, ‘A novel method for elimination of power line frequency in ECG signal using hyper shrinkage function’, Digital Signal Processing.Volume18, Issue 2, March 2008, pp. 116-126.
D.C Raddy, Biomedical signal processing Tata McGraw -Hill2008.
Haykin S. Adaptive Filter Theory Prentic hall, Upper Saddle River, NJ, 3rd edition, 1996.
Widrow B, Glover Jr. JR, McCool JM, Kaunitz J, Williams CS, Hearn RH, Zeidler JR, Dong Jr. E, and Goodlin RC. Adaptive noise cancelling: Principles and applications. Proceedings of the IEEE, 63(12): 1692-17 16, 1975
Pan J and Tompkins WJ. A real-time QRS detection algorithm. IEEE Transactions on Biomedical Engineering, 32-230-236, 1985
Ju-Won-Lee, Gun-Ki Lee, ‘Design of an Adaptive Filter with a Dynamic Structure for ECG signal Processing’ International Journal of Control, Automation and Systems, vol.3, no.1, March 2005, pp. 137-42.
M. Souden, J. Benesty, and S. Affes.On the Global Output SNR of the Parameterized Frequency-Domain Multichannel Noise Reduction Wiener Filter, IEEE SIGNAL PROCESSING LETTERS, VOL. 17, NO. 5, MAY 2010
GD Clifford, A Shoeb, PE McSharry, BA Janz .Model based filtering, compression and classification of the ECG. IJBEM
Vol. 7, No. 1, 2005
E.Cromwell, F.J.Weibell, E.A.Pfeiffer, ‘Biomedical Instrumentation and Measurements’, 2nd Ed., Pearson Education
Key words
