Mathematical Modeling and Data Analysis of Electroencephalographic Signals: A Review

-Electroencephalography is the simple method of recording and measuring electrical activity of brain. This brain signal is amplified and resulting in electroencephalogram (EEG). EEG is non-invasive tool used in monitoring brain activities and diagnosis of many neurological disorder. The main challenge of EEG is the small signal amplitude and its sensitivity to noise because of which it demands advanced and accurate data analysis. Other challenges such as artifacts, synchronizations and temporal variability of signal also have strong impact on to real time EEG measurement and analysis. The EEG analysis plays very important role in feature extraction of EEG signal for detecting and predicting various brain diseases. The main objective of this paper is to study mathematical model and the methods of data analysis of EEG signal. Keywords--Electroencephalogram (EEG), artifacts, Functional MRI (fMRI)