In this paper, an Electrocardiogram (ECG) signal is compressed based on discrete wavelet transform (DWT) and QRS-complex estimation. The ECG signal is preprocessed by normalization and mean removal. Then, an error signal is formed as the difference between the preprocessed ECG signal and the estimated QRS-complex waveform. This error signal is wavelet transformed and the resulting wavelet coefficients are threshold by setting to zero all coefficients that are smaller than certain threshold levels. The threshold levels of all sub bands are calculated based on Energy Packing Efficiency (EPE) such that minimum percentage root mean square difference (PRD) and maximum compression ratio (CR) are obtained. The resulted threshold DWT coefficients are coded using the coding technique. The compression algorithm was implemented and tested upon records selected from the MIT – BIH arrhythmia database simulation results show that the proposed algorithm leads to high CR associated with low distortion level relative to previously reported compression algorithms. The main features of this compression algorithm are the high efficiency and high speed.

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ECG Compression Discrete Wavelet QRS-Complex Estimation