Title: ECG signal compression using the optimised wavelet filter banks

Authors: A. Kumar; K. Ranjeet

Addresses: PDPM-Indian Institute of Information Technology Design and Manufacturing, Jabalpur 482005, MP, India ' PDPM-Indian Institute of Information Technology Design and Manufacturing, Jabalpur 482005, MP, India

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.

Keywords: ECG signals; electrocardiograms; signal compression; DWT; discrete wavelet transform; DCT; discrete cosine transform; Huffman encoding; wavelet filter banks; simulation; biomedical signal processing.

DOI: 10.1504/IJSISE.2012.049855

International Journal of Signal and Imaging Systems Engineering, 2012 Vol.5 No.3, pp.187 - 195

Available online: 17 Oct 2012 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article