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Since Electro Encephalo Graphic (EEG) signal is considered chaotic, Nonlinear Dynamics and Deterministic Chaos theory may supply effective descriptors of the dynamics and underlying chaos in the brain. The EEG signals are highly subjective and the information about the various states may appear at random in the time scale. Therefore, EEG signal parameters, extracted and analyzed using computers, are highly useful. This study was undertaken to evaluate the linear and nonlinear parameters such as Approximate Entropy (ApEn), Correlation Dimension (D2), Pearson Autocorrelation, Bi-correlation, Hurst exponent and phase space plots from the EEG signals under different cognitive states.

A Case Study Analysis of EEG Signals under Conditions of Cognition