<p>Skeletal muscles produce detectable electrical currents and voltages when they contract from any cause. The electrical potentials or electromyographic (EMG) signal is recorded from the muscle using suitable electrodes. The research presented in this thesis is concerned with the analysis and processing of electromyographic signals with a view to their use as a source of control for environmental control or other rehabilitation devices. An application of myo-electric control of a simple communication device for a cerebral palsied patient is presented. A model of the myo-electric source which can be used to stimulate EMG signals in real-time is proposed. The model algorithm has been tested for two different electrode systems and the results compared with real signals recorded using these electrode systems. A number of statistical parameters of the surface recorded EMG signal have been examined to determine which parameter is most suitable for myo-electric control. Finally, a pattern recognition algorithm is proposed which attempts to extract the motor unit recruitment and discharge frequency information present in the surface recorded EMG signal. The statistical parameters and the algorithm have been tested for six normal subjects, under isometric conditions.</p> / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/14151 |
| Date | 07 1900 |
| Creators | de, Bruin Huibregt |
| Contributors | Torre, Della E., Electrical Engineering |
| Source Sets | McMaster University |
| Detected Language | English |
| Type | thesis |
Page generated in 0.0147 seconds