Key result
The proposed ECG compression method using discrete wavelet transform and run length encoding achieved a PRD between 1.62 and 5.78 and a CR between 8.40 and 12.36, demonstrating high performance.
An efficient ECG signal compression method using discrete wavelet transform and run length encoding achieves high compression performance while preserving signal quality.
May support efficient ECG storage in constrained settings; leaves open prospective clinical validation before adoption.
The storage capacity of the ECG records presents an important issue in the medical practices. These data could contain hours of recording, which needs a large space for storage to save these records. The compression of the ECG signal is widely used to deal with this issue. The problem with this process is the possibility of losing some important features of the ECG signal. This loss could influence negatively the analyzing of the heart condition. In this paper, we shall propose an efficient method of the ECG signal compression using the discrete wavelet transform and the run length encoding. This method is based on the decomposition of the ECG signal, the thresholding stage and the encoding of the final data. This method is tested on some of the MIT-BIH arrhythmia signals from the international database Physionet. This method shows high performances comparing to other methods recently published.
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B’charri et al. (2016) studied Arrhythmia (ECG signals). ECG signal compression using discrete wavelet transform and run length encoding vs. Other compression methods was evaluated on Compression Ratio (CR) and Percentage Root mean Difference (PRD). The proposed ECG compression method using discrete wavelet transform and run length encoding achieved a PRD between 1.62 and 5.78 and a CR between 8.40 and 12.36, demonstrating high performance.
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