Wavelet Based ECG Signal Coding Using Burrows-Wheeler Transformation, Move-To Front Coder and Arithmetic Coder

In this paper electrocardiogram (ECG) signal is coded using Wavelet based Burrows-Wheeler Transformation, Move-to Front Coder and Arithmetic coder. Discrete Wavelet Transform (DWT) is applied to decompose the ECG signal. Then Burrows-Wheeler Transformation (BWT), Move to front coder (MTF) and Arithmetic coder are used to compress the decomposed ECG signal. Compression Ratio (CR) and Percent Root mean square Difference (PRD) are used as performance measures. ECG signals/records from MIT BIH arrhythmia database are used to evaluate the performance of this coder. This coder is tested with twenty five different records from MIT BIH arrhythmia data base and obtained the average PRD as 0.0306% to 4.3875% for the average CR of 2.528:1 to 33.8206:1. For record 117 the CR of 8.5317:1 is achieved with PRD 1.0836%. This experimental results show that this coder out performs than other coders such as Djohn, EZW, SPIHT, Novel algorithm etc exists in the literature in terms of coding efficiency and in computation.