The purpose of this research is to construct an intelligent upper limb prosthesis control system that uses electromyogram (EMG) signals. The signal processing of EMG signals is performed using a linear multiple regression model that can learn parameters in a short time. Using this model, joint angles are predicted, and the motion pattern discrimination is conducted. Discriminated motions were grip, open, and chuck of a hand. Predicted joint angles were multi-finger angles corresponding to these three motions. In several experiments we proved the usefulness of processing EMG signals with a linear multiple regression model. © 2006 IEEE.
CITATION STYLE
Kitamura, T., Tsujiuchi, N., & Koizumi, T. (2006). Hand motion estimation by EMG signals using linear multiple regression models. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (pp. 1339–1342). https://doi.org/10.1109/IEMBS.2006.259329
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