ECG Compression with Thresholding of 2-D Wavelet Transform Coefficients and Run Length Coding

Abstract

In this paper, we present a new ECG compression method using 2-D wavelet transform. 2-D approaches utilize the fact that ECG signals generally show redundancy between adjacent beats and between adjacent samples. This algorithm consists of four steps: converting 1-D ECG signals into 2-D array and preprocessing, applying DWT, thresholding, and RLC. First, the periods of ECG quasiperiodic signals are founded by using detection of QRS complex, then alignment and period sorting is used to convert the ECG signal into a matrix. After this, normalization is using to scale the value of matrix, and make a gray scale image due to 2-D ECG. Three levels of 2-D wavelet transform are applied to the constructed 2-D ECG data array. Energy of each subband in all of levels is calculated. Then the coefficients of each subband are thresholded based on a desired energy packing efficiency, and then significant coefficients are coded with RLC. In here, we use RLC algorithm, because of it's good performance on compression. One of the main advantages of this method is lower calculation complexity in comparison with other methods.