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EMG Hand Burst Activity Detection Study Based on Hard and Soft Thresholding

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 256))

Abstract

Electric signal analysis from live organism is an old area that was documented by Francesco Redi dated from 1666, Walsh 1773, and Galvani 1792 [1]. Contraction of muscular fibers by electric impulses was recorded by Debois-Raymmod 1849 [1]. Electric impulses known as myolectric signal and their recording are named electromyographic signals or EMG [2-8]. The first clinical use of EMG signals was reported in 1966 by Harddyck. It is not until the 1980´s that clinical methods to monitor EMG of several muscles were achieved [1].

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Murguia, M.I.C., Olvera, L.V., Reyes, A.D. (2009). EMG Hand Burst Activity Detection Study Based on Hard and Soft Thresholding. In: Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition. Studies in Computational Intelligence, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04516-5_12

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  • DOI: https://doi.org/10.1007/978-3-642-04516-5_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04515-8

  • Online ISBN: 978-3-642-04516-5

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