Summary
The paper presents a concept of bio-prosthesis control via recognition of user intent on the basis of miopotentials acquired of his body. We assume, that in the control process each prosthesis operation consists of specific sequence of elementary actions. The contextual (sequential) recognition is considered in which the rough sets approach is applied to the construction of classifying algorithm. Experimental investigations of the proposed algorithm for real data are performed and results are discussed.
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Kurzynski, M., Zolnierek, A., Wolczowski, A. (2009). Control of Bio-prosthetic Hand via Sequential Recognition of EMG Signals Using Rough Sets Theory. In: Kurzynski, M., Wozniak, M. (eds) Computer Recognition Systems 3. Advances in Intelligent and Soft Computing, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93905-4_54
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DOI: https://doi.org/10.1007/978-3-540-93905-4_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-93904-7
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