Wrist motion pattern recognition system by EMG signals

  • Authors:

  • Yuji Matsumura;Minoru Fukumi;Norio Akamatsu

  • Affiliations:

  • Faculty of Engineering, The University of Tokushima, Tokushima, Japan;Faculty of Engineering, The University of Tokushima, Tokushima, Japan;Faculty of Engineering, The University of Tokushima, Tokushima, Japan

  • Venue:
  • KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
  • Year:
  • 2005

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Abstract

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 Canonical Discriminant Analysis (CDA) to improve recognition accuracy for EMG. From results of computer simulation, it is shown that our approach is effective for improvement in recognition accuracy.