by Bansal, Pansy

Abstract (Summary)
Evoked potentials are defined as potentials that are caused by the electrical activity in the central nervous system after a stimulation .In analysis of evoked potentials the main problem is to extract waveform from the measurements that also contain on-going background electroencephalogram (EEG). The most conventional tool for the analysis of evoked potentials has been the averaging of the measurements over an ensemble of trials. This is the optimal way to improve the signal-to-noise ratio when the evoked potential is a deterministic signal in independent and additive background noise of zero mean. However it is evident that the evoked potential can vary with repetitions of the stimuli. There are two aims of this thesis .The first is to develop a new simulation method for evoked potentials with slow variations among different trials. The second aim is to develop a new method to extract the variations occurring in a number of time-aligned trials. These variations are then added to the mean of the measurements to reconstruct the single trial evoked potentials. The extraction method has been evaluated using both simulated data and real measurements with satisfactory results.
Bibliographical Information:

Advisor:Mingui Sun; Marwan A. Simaan; Ching-Chung Li; Robert Sclabassi

School:University of Pittsburgh

School Location:USA - Pennsylvania

Source Type:Master's Thesis

Keywords:electrical engineering


Date of Publication:06/09/2004

© 2009 All Rights Reserved.