Analysis of Extracted Forearm sEMG Signal Using LDA, QDA, K-NN Classification Algorithms
نویسندگان
چکیده
منابع مشابه
Analysis of Extracted Forearm sEMG Signal Using LDA, QDA, K-NN Classification Algorithms
A surface electromyographic (sEMG) signal includes important information on muscular activity and was recently widely used as an input signal in a myoelectric control system. In this manuscript, eight hand motions were classified using different extracted features from sEMG signals. The results of the experiment show that the combination of sample entropy (SampEnt), root mean square (RMS), myop...
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ژورنال
عنوان ژورنال: The Open Automation and Control Systems Journal
سال: 2014
ISSN: 1874-4443
DOI: 10.2174/1874444301406010108