Low-cost assistive device for hand gesture recognition using sEMG (Erratum)

2016 
Publisher's Note : This paper, originally published on 7/11/16, was replaced with a corrected/revised version on 10/17/18. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. 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.
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