Wavelet based vector quantization with tree code vectors for EMG Signal compression

bstract -This paper discusses a wavelet-based Vector Quantization technique for the
compression of Electromyogram (EMG) signals. Wavelet coefficients, obtained from EMG
signal samples, are arranged to form a set of vectors called Tree Vectors (TVs), where each vector has a hierarchical tree structure. Vector quantization is then applied to these tree vectors for encoding, which uses a pre-calculated codebook. The encoded vector is a set of indexes of the codebook vectors. The codebook is updated dynamically using distortion constrained codebook replenishment method. Finally the signal is decoded using a copy of the same codebook available with encoder. Tests were performed on EMG records obtained from PGI Chandigarh. A good quality of reconstructed signal and sufficient compression is achieved. An average CR of 20.64:1 at PRD of 6.12% is obtained by this technique.