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dc.contributor.advisor Cheatham, John B., Jr.
dc.creatorFernandez, Jaime Julio
dc.date.accessioned 2009-06-04T00:36:48Z
dc.date.available 2009-06-04T00:36:48Z
dc.date.issued 1995
dc.identifier.urihttps://hdl.handle.net/1911/13948
dc.description.abstract This thesis presents a new method of myoelectric signal recognition. Myoelectric signals are electric signals generated by the motion of a person's muscle and can be used as control input for prosthetic hands. It uses genetic programming to create a set of equations capable of recognizing three different myoelectric signals. Three different approaches are presented. The first approach uses genetic programming to create three separate equations. Each equation is capable of recognizing a different pair of the three myoelectric signals. The solution is accomplished by the signal that exactly corresponds to two of the three equations. The second approach creates a single equation capable of distinguishing the three signals. The last approach is a hybrid solution. It uses a simple equation to distinguish 90% of the three signals. It then uses a more complicated equation to distinguish the remaining 10% of the signals.
dc.format.extent 412 p.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectMechanical engineering
Computer science
Biomedical engineering
dc.title Myoelectric signal recognition using genetic programming
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Computer Science
thesis.degree.discipline Engineering
thesis.degree.grantor Rice University
thesis.degree.level Masters
thesis.degree.name Master of Science
dc.identifier.citation Fernandez, Jaime Julio. "Myoelectric signal recognition using genetic programming." (1995) Master’s Thesis, Rice University. https://hdl.handle.net/1911/13948.


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