Classification Of EMG Signal Based On Time Domain And Frequency Domain Features

Too, Jing Wei and Abdullah, Abdul Rahim and Tengku Zawawi, Tengku Nor Shuhada and Mohd Saad, Norhashimah and Musa, Haslinda (2017) Classification Of EMG Signal Based On Time Domain And Frequency Domain Features. International Journal Of Human And Technology Interaction (IJHaTI), 1 (1). pp. 25-30. ISSN 2590-3551

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Electromyography (EMG) is widely used in controlling the signal in manipulating the robot assisted rehabilitation. In order to manipulate a more accurate robot assisted, the feature extraction and selection were equally important. This study evaluated the performance of time domain (TD) and frequency domain (FD) features in discriminating EMG signal. To investigate the features performance, the linear discriminate analysis (LDA) was introduced. The present study showed that the FD features achieved the highest accuracy of 91.34% in LDA. The results were verified by LDA classifier and FD features showed best classification performance in EMG signal classification application.

Item Type: Article
Uncontrolled Keywords: Electromyography (EMG), time domain (TD), frequency domain (FD) and linear discriminant analysis (LDA)
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Electrical Engineering
Depositing User: Mohd Hannif Jamaludin
Date Deposited: 20 Mar 2019 08:23
Last Modified: 23 Aug 2021 02:11
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