Abstract
In order to control the movement of a cybernetic actuator the EMG signal is generally
used as a source of command. This signal has to be processed in order to extract relevant
features, which are then classified. Many schemes exist today in both feature extraction
and classification, each one claiming to reduce the error rate and there has been
some approaches in order to assess the input-output characteristics of prostheses.
This paper vvill introduce a new concept in developing a unique platform using virtual
reality (VR) tools for evaluating both the different schemes of EMG signal processing
and cybernetic control. The design follows a modular approach allowing for the change
of each module (analog signal conditiorming, data acquisition, signal processing,
actuator control, VR aspects) accordingly to the specific needs of an application.
The foreseen applications of this work are performance evaluation of EMG signal processing
algorithms for prosthesis control in real conditions, performance evaluation of the
motor control schemes by executing real tasks, selection of the optimum scheme for
a particular application (spatial, medical surgery, underwater, etc...) and training
of amputees or future users of the system in real conditions where "real conditions"
means the VR simulated environment.
Citation
From "MEC 95," Proceedings of the 1995 MyoElectric Controls/Powered Prosthetics Symposium
Fredericton, New Brunswick, Canada: August, 1995. Copyright University of New Brunswick.
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