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Title: Classification of human hand movements using surface EMG for myoelectric control
Authors: Wei, Jiefei
Meng, Qinggang
Badii, Atta
Issue Date: 2017
Publisher: Springer
Citation: WEI, J. MENG, Q. and BADII, A., 2017. Classification of human hand movements using surface EMG for myoelectric control. IN: Plamen, A. ...et al. (eds.), Advances in Computational Intelligence Systems: Contributions Presented at the 16th UK Workshop on Computational Intelligence, September 7–9, 2016, Lancaster, UK, Cham, Switzerland: Springer, pp. 331-339.
Abstract: © Springer International Publishing AG 2017.Surface electromyogram (sEMG) is a bioelectric signal that can be captured non-invasively by placing electrodes on the human skin. The sEMG is capable of representing the action intent of nearby muscles. The research of myoelectric control using sEMG has been primarily driven by the potential to create humanmachine interfaces which respond to users intentions intuitively. However, it is one of the major gaps between research and commercial applications that there are rarely robust simultaneous control schemes. This paper proposes one classification method and a potential real-time control scheme. Four machine learning classifiers have been tested and compared to find the best configuration for different potential applications, and non-negative matrix factorisation has been used as a pre-processing tool for performance improvement. This control scheme achieves its highest accuracy when it is adapted to a single user at a time. It can identify intact subjects hand movements with above 98% precision and 91% upwards for amputees but takes double the amount of time for decision-making.
Description: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-46562-3_22.
Version: Accepted for publication
DOI: 10.1007/978-3-319-46562-3_22
URI: https://dspace.lboro.ac.uk/2134/24517
Publisher Link: http://dx.doi.org/10.1007/978-3-319-46562-3_22
ISBN: 9783319465616
ISSN: 2194-5357
Appears in Collections:Published Articles (Computer Science)

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