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Classification Method of Hand Gestures Based on Support Vector Machine
Computer Engineering and Applications Journal
This paper presents the EMG signal classification based on PCA and SVM method. The data is acquired from the 5 subjects and each subject perform 7 hand gestures includes the tripod, power, precision closed, finger point, mouse, hand open, and hand close. Each gesture is repeated 10 times (5 data as training data and the 5 remaining data as testing data). Each of training and testing data are processed using 16 features extraction in time–domain and reduced using principal component analysisdoi:10.18495/comengapp.v7i3.269 fatcat:w5vp5xjdxrgfnl3wjvlvipcyny