An efficient wavelet-based pattern matching scheme for ECG data compression
A novel coding scheme for ECG data compression is proposed in this paper. Following beat delineation, the periods of the beats are normalized by multi-rate processing. Amplitude normalization is performed afterwards, and discrete wavelet transform is applied to each normalized beat. Due to the period and amplitude normalization, the wavelet transform coefficients bear a high correlation across beats. To increase the compression ratio, a pattern matching unit is utilized. The difference between the actual period and the standard period, and amplitude scale factor are also retained for each beat. At the decoder, the inverse wavelet transform is computed from the reconstructed wavelet transform coefficients. The original amplitude and period of each beat are then recovered. The simulation results show that the performance of the proposed compression algorithm is quite satisfactory and achieves significant improvement in comparison with some recent techniques.