Compression Approach of EMG Signal Using 2D Discrete Wavelet and Cosine Transforms

The use of telemedicine is of paramount importance, and often involves the compression of biomedical signals. These signals are sensitive to many statistical parameters and high levels of compression, we propose in this work a new approach to compression of EMG signals. The Discrete Wavelet Transform (DWT) and SPIHT (Set Partitioning In Hierarchical Trees) coding proven, we propose to adapt this transform by associating the Discrete Cosine Transform (DCT). The idea is to transform the EMG signal in 2D by a technique so as to increase the correlation between pixels. The image thus formed is then segmented into blocks of pixels of size M x N, where each block will undergo the Discrete Wavelet Transform or Discrete Cosine based on criteria that take into account some statistical parameters of order 1 or 2. The operation is repeated on all blocks of the image. The coefficients thus obtained are coded by the SPIHT coding. The results obtained allow reaching a good compromise between the PRD, the compression ratio and quality of reconstruction of the EMG signal.