Wavelet based ECG Compression with Large Zero Zone Quantizer

Abstract

A new threshold based Wavelet ECG data compression method is proposed. The proposed method uses linear phase Biorthogonal 9/7 discrete Wavelet transform. Wavelet coefficients are selected based on energy packing efficiency of each subband. Significant wavelet coefficients are quantized with uniform scalar zero zone quantizer (USZZQ). Significance map is created to store the indices of the significant coefficients and this map is encoded efficiently with less number of bits by applying Huffman coding on the differences between the indices. ECG records from the MIT-BIH arrhythmia and compression test database are selected as test data. For the record 117, the proposed method achieves a compression ratio of 17.641:1 with lower percentage root mean square difference (PRD) compared to other threshold based methods. An average compression ratio of 20.8231:1 with an average PRD of 7.1641% is achieved for 19 records. The performance is better compared to the SPIHT and ASEC method for some selected records