Title
Electromyography signal acquisition and analysis system for finger movement classification
Date Issued
01 January 2019
Access level
open access
Resource Type
journal article
Publisher(s)
Science and Information Organization
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%.
Start page
411
End page
416
Volume
10
Issue
6
Language
English
OCDE Knowledge area
Biotecnología relacionada con la salud
Scopus EID
2-s2.0-85070509301
Source
International Journal of Advanced Computer Science and Applications
ISSN of the container
2158107X
Sponsor(s)
This work was supported by Public Health Service grants from the National Institutes of Health (AI059130 to O.B.P. and AI042189 to D.J.B.).
Sources of information: Directorio de Producción Científica Scopus