Abstract
Electromyographic (EMG) signal is an established technique for the control of a prosthetic hand. In its simplest form, the signals allow for opening a hand and subsequent closing to grasp an object. An EMG control system consists of two main components: feature extraction and classification. Using the information from different speeds of contraction, this paper describes the classification stage of the signal in determining the final grip postures of the hand. Fuzzy logic (FL) system is used in classifying the final information and the results demonstrate the ability of the system to discriminate the output successfully.
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© 2011 Springer-Verlag Berlin Heidelberg
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Ahmad, S.A., Ishak, A.J., Ali, S.H. (2011). Speed Based Surface EMG Classification Using Fuzzy Logic for Prosthetic Hand Control. In: Osman, N.A.A., Abas, W.A.B.W., Wahab, A.K.A., Ting, HN. (eds) 5th Kuala Lumpur International Conference on Biomedical Engineering 2011. IFMBE Proceedings, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21729-6_33
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DOI: https://doi.org/10.1007/978-3-642-21729-6_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21728-9
Online ISBN: 978-3-642-21729-6
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