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This research is concerned with a dynamic mapping electrocardiogram (ECG) compression method that effectively reduces the percent root mean square difference (PRD) and at the same time achieves the satisfactorily high compression ratio (CR). The distinctive characteristic of the proposed technique lies in its applicability to both the regular and irregular ECG signals, compared to existing techniques that are solely applicable to the regular signal. Specifically, in the dynamic mapping, the Period Scaling technique is first applied and the Dynamic Time Warping (DTW) technique is then triggered if the signal error exceeds the maximum beat error. The signal error exceeding the maximum beat error indicates an irregular ECG signal. In the assessment, the proposed technique was applied to a total of 42 MIT-BIH ECG signals. The experiments were conducted using a maximum beat error of 1% and various threshold criteria sets by varying EPEAC and EPEDC1, EPEDC2, EPEDC3 in the ranges of 90-99% and 50-99%, respectively, where EPEAC and EPEDC1-3 are Energy Packing Efficiency’s approximation coefficient and detailed coefficients. The results indicate that the threshold sets of 99% for EPEAC and 80-90% equally for EPEDC1, EPEDC2 and EPEDC3 contribute to less than 1% PRD values and the satisfactorily high CR levels of 4.6-11. Moreover, this research descriptively compared the ECG signal numbers 100 (regular), 117 and 228 (irregular) with regard to the signal compression performances. Keyword: compression, ECG, mapping technique, discrete wavelet transform

Dynamic Mapping Algorithmic Scheme for Compression of Regular and Irregular ECG Signals