Investigation of suitable Gaussian estimate to extract brain source signals of disabled subjects

Analyzing brain signals plays vital role in diagnosis and treatment of brain disorders. Brain signals obtained from electrodes of Electroencephalogram (EEG) are linear mixture of evoked potentials (EVP) of some number of neurons. Original signals have to be separated from linear mixture of source signals. Earlier work on disabled EEG signals considered analyzing electrode/sensor signals rather than on EVPs. This paper investigates the decision of applying suitable Gaussian function in extracting source signals from sensor signals. The EEG was recorded at 2048 Hz sampling rate from 32 electrodes placed at the standard positions of the 10-20 international system. The system was tested with five disabled subjects. Results were obtained for all the subjects. Results shown in this paper were of a subject which has relatively more disability than other subjects. This subject has least movement than other subjects. The decision was taken based on visual inspection of extracted source signals through different Gaussian estimates followed by confirmation through frequency analysis.