The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2017
Session ID : 2P1-M11
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Estimation of Finger Motions Focusing on Time Series Features of EMG
Tetsu ONOYuki UENOYoshiki MATSUO
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Abstract

Methods to estimate continuous finger motion from EMG considering its time series features are examined. Although EMG in continuous motion seems to include dynamic properties, conventional methods utilizes EMG feartures only statically. In this presentation, to utilize the dynamic properties, an artificial neural network with time delays and one with a recursive structure are examined. The validity of the both metods are confirmed by experiment. As a result, the higher accuracy is obtained for unknown data sets comparing to a conventional method.

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© 2017 The Japan Society of Mechanical Engineers
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