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Costa, M.V.C., Berger, P.A., Rocha, A.F., de Carvalho, J.L.A. and de Oliveira Nascimento, F.A. (2008) Compression of Electromyographic Signals Using Image Compression Techniques. Proceedings of the 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vancouver, BC, 20-25 August 2008 , 2948-2951.
https://doi.org/10.1109/IEMBS.2008.4649821

has been cited by the following article:

• TITLE: 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)

  AUTHORS: Colince Welba, Aimé Joseph Oyobé Okassa, Pascal Ntsama Eloundou, Pierre Ele

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

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.11 No.3, August 31, 2020

  ABSTRACT: 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.