ECG Compression through segment matching and progressive error encoding

This work describes a lossy electrocardiogram (ECG) compression algorithm based on R-R segmentation and segment matching. An ECG can be thought of as a quasi-periodic signal, with many similarities existing between heartbeats acquired from the same source. Through the use of an adaptive dictionary, it is possible to explore the similarities between new and previously encountered patterns, incorporating new patterns when a significant change in morphology has been observed. Algorithm simulation reveals very high compression ratios are possible on very regular signals.