Using contexts and R-R interval estimation in lossless ECG compression
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Ciprian Doru Giurcăneanu1, Ioan Tăbuş, Serban Mereuţă
1Signal Processing Laboratory, Tampere University of Technology, P.O. Box 553, Tampere 33101, Finland.
Abstract:
The paper presents a new lossless ECG compression scheme. The short-term predictor and the coder use conditioning on a small number of contexts. The long-term prediction is based on an algorithm for R-R interval estimation. Several QRS detection algorithms are investigated to select a low complexity and reliable detection algorithm. The coding of prediction residuals uses primarily the Golomb-Rice (GR) codes, but, to improve the coding results, escape codes GR-ESC are used in some contexts for a limited number of samples. Experimental results indicate the good overall performance of the lossless ECG compression algorithms (reducing the storage needs from 12 to about 3-4 bits per sample). The scheme consistently outperforms other waveform or general purpose coding algorithms.
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