ABSTRACT
Electroencephalogram (EEG) is an electrophysiological recording of the brain potentials whose analysis has been crucial in the study of various neurological conditions. However, due to the non-stationarity and noisy nature of EEG, it is extremely difficult to extract meaningful information. In this chapter, we introduce a standard pipeline consisting of an amalgamation of advanced signal processing and machine learning techniques that can be used to analyze EEG signals irrespective of the organism it was collected from. The working of the proposed standard EEG analysis pipeline is demonstrated in the detection of traumatic brain injury (TBI) in mouse and human sleep EEG.
