Exploitation of Differential Pulse Code Modulation for Compression of EMG Signals by a Combination of DWT and DCT

Abstract Storage and transmission of medical information are for more than a decade a subject of great importance, particularly because of exponential growth experienced by telemedicine. This paper presents a compression method of EMG signals, based on encoder Differential Pulse Code Modulation (DPCM) as pre-processing. The method consists to process a signal by the DPCM coder and transform signal into 2D; arrange this signal by correlation sorting function and cut them into blocks of pixels. Finally, we apply Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). The coefficients thus obtained are coded by the SPIHT coding. The results obtained on real signals are measured by the compression ratio (CR), signal to noise ratio (SNR) and percentage root mean square difference (PRD) and quality of reconstruction EMG signal. This method offers encouraging results in terms of Compression Ratio (CR) and PRD. Keywords Compression, EMG, DCT, DPCM, SPIHT, DWT 1. Introduction Images, as the electrophysiological signals contain redundant information. of compression is to The aimminimize or eliminate such redundancy. The compression of electrophysiological signals is the subject of manystudies that focus onimprovement of compression algorithms and the development of new techniques and compression formats. Predictive coding also called Differential Pulse Code Modulation (DPCM) is a simple method for reduction of redundancy [1, 2]. The hiddentheory of predictive coding is to predict the sample values of a signal based on already existing values, and coding the prediction error. That is why we proposed to significantly reduce signal distortion by the predictive coding in order to obtain a low value of the percentage root mean square difference in compression. Compression electrophysiological signals in 2D began with the electrocardiogram (ECG) signals, before extending to others as EMG. In this review, just a few works will be mentioned to show the exponential growth of this technique. Lee and Buckley in 1996 [3, 4], and Uyar Ider 2001 [5] proposed compression methods of electrocardiogram (ECG)

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