Adaptive data compression of ambulatory ECG using multi templates

This paper proposes a new adaptive method of data compression for digital ambulatory electrocardiogram (ECG), considering diagnostic significance of each segment of ECG. R-wave is detected, followed by multi template matching of the detected beat and judgment of noise level; the templates are successively created during processing. The residual signal (difference between the original ECG and the best-fit template) is approximated with FAN (SAPA2) method and then encoded. The error threshold of FAN is decreased during P-wave segments and increased during noise segments; the maximum error of the reconstructed signal at each time is known. This method is applied to ECGs of the AHA (American Heart Association) database and its usefulness is indicated; e.g., bit rate is approximately 400bps at 8% PRD and 200bps at 15% PRD.