摘要
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 <span style="font-family:Verdana;">digitized s-EMG signal. A Discrete Cosine Transforms (DCT) is applied to the MDWPT coefficients (only on detail coefficients). The MDWPT+ DCT coeffici</span><span style="font-family:Verdana;">ents are quantized with a Uniform Scalar Dead-Zone Quantizer (USD</span><span style="font-family:Verdana;">ZQ)</span><span style="font-family:Verdana;">. An arithmetic coder is employed for the entropy coding of symbol streams. The</span><span style="font-family:Verdana;"> proposed approach was tested on more than 35 act</span><span style="font-family:Verdana;">uals S-EMG signals divided into three categories. The proposed approach was evaluated by the foll</span><span style="font-family:Verdana;">owing parameters: Compression Factor (CF), Signal to Noise Ratio (SN</span><span style="font-family:Verdana;">R), </span><span style="font-family:Verdana;">Percent Root mean square Difference (PRD), Mean Frequency Distortion (MFD) </span><span style="font-family:Verdana;">and the Mean Square Error (MSE). Simulation results show that the proposed coding algorithm outperforms some recently developed s-EMG compression algorithms.</span>
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 <span style="font-family:Verdana;">digitized s-EMG signal. A Discrete Cosine Transforms (DCT) is applied to the MDWPT coefficients (only on detail coefficients). The MDWPT+ DCT coeffici</span><span style="font-family:Verdana;">ents are quantized with a Uniform Scalar Dead-Zone Quantizer (USD</span><span style="font-family:Verdana;">ZQ)</span><span style="font-family:Verdana;">. An arithmetic coder is employed for the entropy coding of symbol streams. The</span><span style="font-family:Verdana;"> proposed approach was tested on more than 35 act</span><span style="font-family:Verdana;">uals S-EMG signals divided into three categories. The proposed approach was evaluated by the foll</span><span style="font-family:Verdana;">owing parameters: Compression Factor (CF), Signal to Noise Ratio (SN</span><span style="font-family:Verdana;">R), </span><span style="font-family:Verdana;">Percent Root mean square Difference (PRD), Mean Frequency Distortion (MFD) </span><span style="font-family:Verdana;">and the Mean Square Error (MSE). Simulation results show that the proposed coding algorithm outperforms some recently developed s-EMG compression algorithms.</span>
作者
Colince Welba
Aimé Joseph Oyobé Okassa
Pascal Ntsama Eloundou
Pierre Ele
Colince Welba;Aimé Joseph Oyobé Okassa;Pascal Ntsama Eloundou;Pierre Ele(Department of Fundamental Science, Faculty of Mines and Petroleum Industries, University of Maroua, Maroua, Cameroon;School of Engineering of Masuku, Franceville, Gabon;Physics Department, Faculty of Sciences, University of Ngaoundere, Ngaoundere, Cameroon;Electrical Engineering and Telecommunications Department, National Advanced School of Engineering,University of Yaounde 1, Ya-oundé, Cameroon)
