Author(s)

Colince Welba^1*, Aimé Joseph Oyobé Okassa², Pascal Ntsama Eloundou³, Pierre Ele⁴

¹Department of Fundamental Science, Faculty of Mines and Petroleum Industries, University of Maroua, Maroua, Cameroon.
²School of Engineering of Masuku, Franceville, Gabon.
³Physics Department, Faculty of Sciences, University of Ngaoundere, Ngaoundere, Cameroon.
⁴Electrical Engineering and Telecommunications Department, National Advanced School of Engineering,University of Yaounde 1, Ya-oundé, Cameroon.

A new Modified Discrete Wavelets Packets Transform (MDWPT) based method for the compression of Surface EMG signal (s-EMG) data is presented. A Modified Discrete Wavelets Packets Transform (MDWPT) is applied to the digitized s-EMG signal. A Discrete Cosine Transforms (DCT) is applied to the MDWPT coefficients (only on detail coefficients). The MDWPT+ DCT coefficients are quantized with a Uniform Scalar Dead-Zone Quantizer (USDZQ). An arithmetic coder is employed for the entropy coding of symbol streams. The proposed approach was tested on more than 35 actuals S-EMG signals divided into three categories. The proposed approach was evaluated by the following parameters: Compression Factor (CF), Signal to Noise Ratio (SNR), Percent Root mean square Difference (PRD), Mean Frequency Distortion (MFD) and the Mean Square Error (MSE). Simulation results show that the proposed coding algorithm outperforms some recently developed s-EMG compression algorithms.

S-EMG, Compression, MDWPT, DCT, Arithmetic Coding, Uniform Scalar Dead-Zone Quantizer (USDZQ)

Welba, C. , Okassa, A. , Eloundou, P. and Ele, P. (2020) Contribution to S-EMG Signal Compression in 1D by the Combination of the Modified Discrete Wavelet Packet Transform (MDWPT) and the Discrete Cosine Transform (DCT). Journal of Signal and Information Processing, 11, 35-57. doi: 10.4236/jsip.2020.113003.