Detection and Classification of EEG Waves

The Electroencephalograph (EEG) signal is widely used to analyze neural activity within the human brain for detection of any abnormalities. Since the EEG signal is dynamic by nature and changes constantly a highly sensitive yet robust system is required to monitor the activities.

In this work, EEG waves are analyzed and then classified using first the Discrete Wavelet Transform DWT, used for time-frequency analysis, followed by Fast Fourier Transform (FFT) that captures the rhythmic changes in EEG data. The process uses DWT for classifying EEG wave’s frequencies, where as FFT is implemented to visualize these waves.