Electromyography Signal Acquisition and Analysis System for Finger Movement Classification
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 6
Abstract
Electromyography (EMG) is very important to capture muscle activity. Although many jobs establish data acquisition system, however, it is also essential to demonstrate that these data are reliable. In this sense, one proposes a design and implementation of a data acquisition system with the Myoware device and the ATmega329P microcontroller. One also proved its reliability by classifying the movement of the fingers of the hand, with the help of the algorithm k-Nearest Neighbors (KNN) and the application of Classification Learner code of Matlab. The results show a success rate of 99.1%.
Authors and Affiliations
Alvarado-Díaz, Witman, Meneses-Claudio Brian, Roman-Gonzalez Avid
Keywords
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- EP ID EP596830
- DOI 10.14569/IJACSA.2019.0100653
- Views 78
- Downloads 0
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