Abstract
Electromyogram (EMG) is a kind of biological signal that is generated because of excitement of muscle according to the motor instruction from a brain. We have been experimentally developing the real-time hand motion recognition system by using 4 channels forearm SEMG signals. In our system, in order to classify measured SEMG SVM (Support Vector Machine) that has higher discriminability is used. Usually SVM is used as a non-linear classifier. However, In the conventional system that we developed, we used a canonical discriminant analysis (CDA) method. CDA method is based on linear discriminant function, and it has shown good experimental results. So, we think linear SVM also has good separate performance. Than before, these discussions are not enough. Therefore, we developed real-time hand motion recognition system that uses linear SVM or non-linear SVM as a discriminant function, and we have compared the discriminant ability between linear SVM, non-linear SVM. In this report, we will describe about the results of this experiment.
