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The Use of Fuzzy Logic In the Processing Of Myoelectric Signals

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Date
1999
Authors
Taffler, Sean
Kyberd, Peter J.
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Abstract
This paper describes the use of Fuzzy logic for the processing of EMG signals. This can increase the recognition rate and significantly reduce the number of computations required to generate an output. The initial placement of the Fuzzy sets was accomplished with the use of neural network techniques, these are not required for in the final system, only for setting up. The effectiveness of the features extracted from the EMG signals has been assessed using Principal Component Analysis (PCA) The developed system exhibits good generalisabilty but performs better when tuned to the intended user.
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https://hdl.handle.net/10161/4929
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From "MEC 99," Proceedings of the 1999 MyoElectric Controls/Powered Prosthetics Symposium Fredericton, New Brunswick, Canada: August, 1999. Copyright University of New Brunswick.
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  • MEC Symposium Conference Proceedings
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Copyright 2002, 2005 and 2008, The University of New Brunswick.

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License. Creative Commons License

Rights for Collection: MEC Symposium Conference Proceedings


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