ECG Data Compression using Wavelet Transform

ECG data compression has been one of the active research areas in biomedical engineering. In this paper a compression method for electrocardiogram (ECG) signals using wavelet transform is proposed. Wavelet transform compact the energy of signal in fewer samples and has a good localization property in time and frequency domain. The MIT-BIH ECG signals are decomposed using discrete wavelet transform (DWT).The DWT provide powerful capability to remove frequency components at specific time in the data. The thresholding of the resulted DWT coefficients are done in a manner such that a predefined goal percent root mean square difference (GPRD) is achieved. The compression is achieved by the quantization technique, run-length encoding, Huffman and binary encoding methods. The proposed method, for fixed GPRD shows better performance with high compression ratios and good quality reconstructed signals. Keywords—Compression, discrete wavelet transform Electrocardiogram (ECG), PRD, quantization, thresholding.