A Wavelet-Based ECG Compression Algorithm Using Golomb Codes

A new wavelet-based method for the compression of electrocardiogram (ECG) data is presented. The discrete wavelet transform (DWT) is applied to the digitized ECG signal. The DWT coefficients are firstly quantized with a uniform scalar dead zone quantizer. Then, the quantized coefficients are decomposed into two parts for efficient entropy coding: a nonzero coefficient stream and a binary significance symbol stream which indicates the locations of those nonzero coefficients. The Exp-Golomb coding is used to code the lengths of runs of the zero coefficients. The Golomb-Rice coding is used to code the nonzero coefficients. Experiments on several records from the MIT-BIH arrhythmia database show that the proposed coding algorithm outperforms other recently developed ECG signal compression algorithms