Abstract
This paper tries to recognize EMG signals by using neural networks. The electrodes under the dry state are attached to wrists and then EMG is measured. These EMG signals are classified into seven categories, such as neutral, up and down, right and left, wrist to inside, wrist to outside by using a neural network. The NN learns FFT spectra to classify them. Moreover, we structuralized NN for improvement of the network. It is shown that our approach is effective to classify the EMG signals by means of computer simulations.
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References
Hashimoto, K., Endo, T.: How to Inspect to Vital Function. Japan publishing service (1983) (in Japanese)
Cooley, J.W., Turkey, J.W.: An Algorithm for Machine Calculation of Complex Fourier Series, vol. 19, pp. 297–301 (1965)
Hearts, J., Krogh, A., Palmer, R.G.: Introduction to The Theory of Neural Computation. In: The Advanced Book Program, Addison-Wesley Publishing Company, 350 Bridge Park0way (1991)
Vaughan Jr., H.G., Costa, L.D., Gilden, L., Schimmel, H.: Identification of Sensory And Motor Components of Cerebral Activity in Simple Reaction Time Tasks. In: Proc. 73rd, Conf. Amer. Psychol. Ass., vol. 1, pp. 179–180 (1965)
De Luca, C.J.: Physiology and Mathematics of Myoelectric signals. IEEE Trans, Biomed. Eng. 26, 313–325 (1979)
Kohonen, T.: Self-Organization and Associative Memory. Springer, Heidelberg (1984)
Kohonen, T.: Self-Organizing Maps. Springer, Heidelberg (1995)
Matsumura, Y., Fukumi, M., Akamatsu, N.: Recognition of EMG Signal Patterns by Neural Network. In: ICONIP 2002 Workshop Proceeding (2002)
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Matsumura, Y., Mitsukura, Y., Fukumi, M., Akamatsu, N., Takeda, F. (2003). Recognition of EMG Signal Patterns by Neural Networks. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_85
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DOI: https://doi.org/10.1007/978-3-540-45224-9_85
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40803-1
Online ISBN: 978-3-540-45224-9
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