Neural networks and neurophysiological signals

• Main Author: Sarda, Srikant, 1977-
• Other Authors: Steve Burns.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2005
• Subjects: Electrical Engineering and Computer Science
• Online Access: http://hdl.handle.net/1721.1/9806

Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999. === Includes bibliographical references (p. 45). === The purpose of this thesis project is to develop, implement, and validate a neural network which will classify compound muscle action potentials (CMAPs). The two classes of signals are "via­ble" and "non-viable." This classification system will be used as part of a quality assurance mech­anism on the NC-stat nerve conduction monitoring system. The results show that standard backpropagation neural networks provide exceptional classification results on novel waveforms. Also, principal components analysis is a powerful preprocessing technique which allows for a sig­nificant reduction in processing efficiency, while maintaining performance standards. This system is implementable as a real-time quality control process for the NC-stat. === by Srikant Sarda. === S.B.and M.Eng.