ECG signal compression algorithm based on joint-multiresolution analysis (J-MRA)

This paper explores the new algorithm for ECG signal compression based on Joint-multiresolution analysis (J-MRA) using Gaussian pyramid and wavelet analysis. From signal compression prospective, MRA play key role to present signal in few numbers of coefficients with its parental features. The proposed algorithm has been tested on 10 second length of 19 ECG signals from MIT-BIH Arrhythmia database and compared with recent contemporary techniques. The simulation results show that the proposed method achieves high compression ratio at relatively low distortion in comparison with other methods. Analysis contains various simulation results, where the average compression is 86.14% at 4.96% of PRD and correlation founded between original and reconstructed signal is 0.998. It can clearly demonstrate the algorithm efficiency towards to save a great amount of storage space, bandwidth and power consumption especially in data transmission for tele-health care or m-health care systems.

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