Hybrid Wrist EMG Recognition System by MDA and PCA
Yuji MATSUMURA, Yasue MITSUKURA, Minoru FUKUMI
In this paper, we propose a recognition system of wrist operation by focusing on ElectroMyoGram (EMG) that is the living body signal generated with movement of a subject. In previous research, we only performed pattern recognition by Neural Network (NN) and Fast Fourier Transform (FFT). In contrast, in proposal research, we try to improve recognition accuracy and reduce learning-time of system by combining Multi Discriminant Analysis (MDA) and gradual Principal Component Analysis (PCA) based on the PCA result of EMG data. From results of computer simulation, it is shown that our approach is effective for improvement in recognition accuracy and speed.