Wrist EMG Pattern Recognition System by Neural Networks and Genetic Algorithms

Y. Matsumura, M. Fukumi, and N. Akamatsu (Japan)


ElectroMyoGram, neural network, Fast Fourier Transform, principal component analysis, genetic algorithm


In this paper, we aim for construction of a high-speed and high-accurate EMG recognition system using Fast Fourier Transform (FFT) for feature extraction, simple PCA (SPCA) for feature compression, and a neural network (NN) for recognition. Furthermore, we reduce the number of units in an input layer of NN using genetic algorithms (GA) for EMG. From results of computer simulation, it is shown that our approach is effective for improvement in recognition accuracy and speed.

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