PERFORMANCE ANALYSIS OF NONLINEAR TRANSFORMATIONAL ECG COMPRESSION METHOD

Abstract

This paper presents and analyzes nonlinear transform-based method electrocardiogram (ECG) compression. The procedure used is similar to that used in linear transform-based method. The ECG signal is first transformed using (i) linear transform: discrete cosine transforms (DCT), Laplacian pyramid (LP), wavelet transform (WT) and it is transformed using (ii) nonlinear transform: essentially nonoscillatory cell average (ENOCA). The transformed coefficients (TC) are thresholded using the bisection algorithm in order to match the predefined user-specified percentage root mean square difference (PRD) within the tolerance. Then, the binary lookup table is made to store the position map for zero and nonzero coefficients (NZCs). The NZCs are quantized by Max–Lloyd quantizer followed by arithmetic coding. Lookup table is encoded by Huffman coding. The results are presented on different ECG signals of varying characteristics. The results show that nonlinear transform (ENOCA) gives better performance at high PRD where as at low PRD, DCT performs better.