ECG signal compression using the optimised wavelet filter banks
by A. Kumar; K. Ranjeet
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 5, No. 3, 2012

Abstract: In this paper, an optimised wavelet filter bank based methodology is presented for compression of Electrocardiogram (ECG) signal. The methodology employs new wavelet filter bank whose coefficients are derived with different window techniques such as Kaiser and Blackman windows using simple linear optimisation. A comparative study of performance of different existing wavelet filters and the proposed wavelet filter is made in terms of Compression Ratio (CR), Percent Root mean square Difference (PRD), Mean Square Error (MSE) and Signal-to-Noise Ratio (SNR). When compared, the developed wavelet filter gives better CR and also yields good fidelity parameters as compared to other wavelet filters. The simulation result included in this paper shows the clearly increased efficacy and performance in the field of biomedical signal processing.

Online publication date: Wed, 31-Dec-2014

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