Abstract
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.
Highlights
The Electrocardiogram signal (ECG), as shown in Fig. 1, represents the electrical activity of the hearts
The compression process of these records 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 paper proposes an efficient method of the ECG signal compression using the discrete wavelet transform and the run length encoding
Summary
The Electrocardiogram signal (ECG), as shown in Fig. 1, represents the electrical activity of the hearts. The compression process of these records 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. The algorithms based on the discrete wavelet transform (DWT) [16,17] offer an important solution for the ECG compression These algorithms provide a better localization of the different features consisting the ECG signal. This paper proposes an efficient method of the ECG signal compression using the discrete wavelet transform and the run length encoding. This paper is organized as follows, after the introduction; the section presents the different steps of the proposed method from the decomposing of the ECG signal to the encoding of data. The Symlet 7 (sym7) is the chosen function for this method; this function shows the best results comparing to others in the proposed method
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