Browsing University of Waterloo by Subject "myoelectric control"
Now showing items 1-2 of 2
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Applications of Neural Networks in Classifying Trained and Novel Gestures Using Surface Electromyography
(University of Waterloo, 2019-09-09)Current prosthetic control systems explored in the literature that use pattern recognition can perform a limited number of pre-assigned functions, as they must be trained using muscle signals for every movement the user ... -
Spatial Information Enhances Myoelectric Control Performance with Only Two Channels
(Institute of Electrical and Electronics Engineers, 2018-09-10)Automatic gesture recognition (AGR) is investigated as an effortless human-machine interaction method, potentially applied in many industrial sectors. When using surface electromyogram (sEMG) for AGR, i.e. myoelectric ...