Classification of hand motions using linear discriminant analysis and support vector machine

In this study, we aimed to recognize six hand motions using surface electromyogram (sEMG) signals recorded from eight muscles of the right hand. Twenty-five healthy subjects participated in this experiment. Data were segmented using windows of 250-ms length with a 150-ms overlapping. In this paper,...

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Veröffentlicht in:	2017 Chinese Automation Congress (CAC) S. 2353 - 2356
Hauptverfasser:	Haibin Zeng, Ke Li, Xincheng Tian, Na Wei, Rui Song, Lelai Zhou
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.10.2017
Schlagworte:	classification discriminant analysis Electromyography Feature extraction Field-flow fractionation hand motions linear discriminant analysis multiple regression analysis Muscles support vector machine Support vector machines surface electromyogram Thumb
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