Time-Frequency Analysis of EEG Data to Distinguish Different Mental States By Using Global Wavelet Spectrum
1Department of Mathematics, NED University of Engineering and Technology, Karachi, PAKISTAN
2Department of Computer and Information Systems Engineering, NED University of Engineering and Technology, Karachi, PAKISTAN
3Department of Textile Engineering, NED University of Engineering and Technology, Karachi, PAKISTAN
2Department of Computer and Information Systems Engineering, NED University of Engineering and Technology, Karachi, PAKISTAN
3Department of Textile Engineering, NED University of Engineering and Technology, Karachi, PAKISTAN
Sigma J Eng Nat Sci 2019; 10(): 355-362
Abstract
The electroencephalography (EEG) is a way to study the individual’s electrical activity of the brain. It is non-invasive technique to analyze brain signals which help to identify that either signals are showing normal or abnormal activity of the brain i.e. Different emotional states and mental diseases. The signals of EEG are non-stationary means the frequency of signals changes over time. To study these non-stationary signals, wavelet transform is used to classify EEG segment for seven different subjects. In the proposed work, three dimensional global wavelet spectrum (GWS) are applied on seven EEG datasets to compare the results of different mental states of a person.
Keywords: EEG, global wavelet spectrum.
