Key result
Adaptive Run Length Encoding with optimized wavelets improves ECG compression efficiency over other techniques.
Why the study?
A method to compress electrocardiograms with minimized distortion by optimizing wavelet selection and encoding significant coefficients was needed.
The proposed Adaptive Run Length Encoding method using optimized wavelets provides efficient compression of electrocardiograms.
New adaptive wavelet ECG compression may reduce distortion; leaves open clinical validation before routine adoption.
A compression method, based on the choice of a wavelet that minimizes the distortion of compression for each electrocardiogram considered, is proposed in this paper. The scaling filter used on the determination of the wavelet function is obtained from the resolution of an optimization problem, which is unconstrained since the scaling filter is parametrized in a way that the constraints applied to the scaling filter are embedded on the parameters. The coefficients of projection of the signal over the wavelet subspaces are calculated and only the most significant ones are retained, being the significant coefficients determined in order to satisfy a pre-specified distortion measure. The bitmap that informs the positions of the retained coefficients is encoded along with the values of the coefficients by using an improved version of the Run Length Encoding technique. Experiments that compare the proposed approach with other techniques illustrate the efficiency of the method.
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Agulhari et al. (2010) studied Electrocardiograms. Adaptive Run Length Encoding method with wavelet optimization vs. Other techniques was evaluated on Compression efficiency and distortion measure. An Adaptive Run Length Encoding method combined with optimized wavelet selection efficiently compressed electrocardiograms while satisfying pre-specified distortion measures compared to other techniques.
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