In this paper, we aim for construction of high-speed and high-accurate system using Fast Fourier Transform (FFT) for feature extraction, Simple-PCA (SPCA) for feature compression, and a neural network (NN) for recognition. In particular, we present a novel method based on Multiple PCA to improve recognition accuracy for EMG. From results of computer simulation, it is shown that our approach is effective for improvement in recognition accuracy and speed. © Springer-Verlag 2004.
CITATION STYLE
Matsumura, Y., Fukumi, M., Akamatsu, N., & Takeda, F. (2004). Wrist EMG Pattern Recognition System by Neural Networks and Multiple Principal Component Analysis. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3213, 891–897. https://doi.org/10.1007/978-3-540-30132-5_120
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