By a News Reporter-Staff News Editor at Biotech Week -- Current study results on Algorithms have been published. According to news reporting originating in Brasilia, Brazil, by NewsRx journalists, research stated, "Surface electromyographic (S-EMG) signal processing has been emerging in the past few years due to its non-invasive assessment of muscle function and structure and because of the fast growing rate of digital technology which brings about new solutions and applications. Factors such as sampling rate, quantization word length, number of channels and experiment duration can lead to a potentially large volume of data."
The news reporters obtained a quote from the research from the University of Brasilia, "Efficient transmission and/or storage of S-EMG signals are actually a research issue. That is the aim of this work. This paper presents an algorithm for the data compression of surface electromyographic (S-EMG) signals recorded during isometric contractions protocol and during dynamic experimental protocols such as the cycling activity. The proposed algorithm is based on discrete wavelet transform to proceed spectral decomposition and de-correlation, on a dynamic bit allocation procedure to code the wavelets transformed coefficients, and on an entropy coding to minimize the remaining redundancy and to pack all data. The bit allocation scheme is based on mathematical decreasing spectral shape models, which indicates a shorter digital word length to code high frequency wavelets transformed coefficients. Four bit allocation spectral shape methods were implemented and compared: decreasing exponential spectral shape, decreasing linear spectral shape, decreasing square-root spectral shape and rotated hyperbolic tangent spectral shape. The proposed method is demonstrated and evaluated for an isometric protocol and for a dynamic protocol using a real S-EMG signal data bank. Objective performance evaluations metrics are presented. In addition, comparisons with other encoders proposed in scientific literature are shown. The decreasing bit allocation shape applied to the quantized wavelet coefficients combined with arithmetic coding results is an efficient procedure."
According to the news reporters, the research concluded: "The performance comparisons of the proposed S-EMG data compression algorithm with the established techniques found in scientific literature have shown promising results."
For more information on this research see: S-EMG signal compression based on domain transformation and spectral shape dynamic bit allocation. Biomedical Engineering Online, 2014;13(1):22. (BioMed Central - www.biomedcentral.com/; Biomedical Engineering Online - www.biomedical-engineering-online.com)
Our news correspondents report that additional information may be obtained by contacting M.H. Trabuco, Group of Digital Signal Processing, Dept. of Electrical Engineering, University of Brasilia, Brasilia, DF, Brazil. Additional authors for this research include M.V. Costa and F.A Nascimento (see also Algorithms).
Keywords for this news article include: Brazil, Brasilia, Algorithms, South America, Information Technology, Information and Data Compression.
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