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Proceedings Paper

Low-cost assistive device for hand gesture recognition using sEMG
Author(s): Ondrej Kainz; Dávid Cymbalák; Slavomír Kardoš; Peter Fecil'ak; František Jakab
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Paper Abstract

In this paper a low-cost solution for surface EMG (sEMG) signal retrieval is presented. The principal goal is to enable reading the temporal parameters of muscles activity by a computer device, with its further processing. Paper integrates design and deployment of surface electrodes and amplifier following the prior researches. Bearing in mind the goal of creating low-cost solution, the Arduino micro-controller was utilized for analog-to-digital conversion and communication. The software part of the system employs support vector machine (SVM) to classify the EMG signal, as acquired from sensors. Accuracy of the proposed solution achieves over 90 percent for six hand movements. Proposed solution is to be tested as an assistive device for several cases, involving people with motor disabilities and amputees.

Paper Details

Date Published: 11 July 2016
PDF: 7 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100111B (11 July 2016); doi: 10.1117/12.2243167
Show Author Affiliations
Ondrej Kainz, Technical Univ. of Košice (Slovakia)
Dávid Cymbalák, Technical Univ. of Košice (Slovakia)
Slavomír Kardoš, Technical Univ. of Košice (Slovakia)
Peter Fecil'ak, Technical Univ. of Košice (Slovakia)
František Jakab, Technical Univ. of Košice (Slovakia)


Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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