Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/14462
Title: | EMG Controlled Hand Prosthesis: EMG Classification System |
Authors: | Chrapka, Philip |
Keywords: | Electromyographic control;support vector machines;neural networks;cus- tom hardware design;Biomedical;Electrical and Computer Engineering;Biomedical |
Publication Date: | 23-Apr-2010 |
Abstract: | <p>Since the 1970s, electromyographic control of a prosthetic device has been attempted in a number of different ways. It was only until recently, that the classification of electromyo- graphic signals was possible through the use of neural networks. With the advent of more advanced techniques like support vector machines this type of control is becoming more re- alistic. This would initiate a great step in the development of prosthetic devices. It would become possible for more advanced control of these devices with a more natural interface. This project focuses on the development of an electromyographic classification system on an embedded platform for the specific use of controlling a prosthetic device.</p> |
URI: | http://hdl.handle.net/11375/14462 |
Identifier: | ee4bi6/59 1034 1796598 |
Appears in Collections: | EE 4BI6 Electrical Engineering Biomedical Capstones |
Files in This Item:
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fulltext.pdf | 757.6 kB | Adobe PDF | View/Open |
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