Complexity of EEG-signal in Time Domain - Possible Biomedical Application
Włodzimierz Klonowski · AIP conference proceedings · 2002
Human brain is a highly complex nonlinear system. So it is not surprising that in analysis of EEG‐signal, which represents overall activity of the brain, the methods of Nonlinear Dynamics (or Chaos Theory as it is commonly called) can be used. Even if the signal is not chaotic these methods are a motivating tool to explore changes in brain activity due to different functional activation states, e.g. different sleep stages, or to applied therapy, e.g. exposure to chemical agents (drugs) and physical factors (light, magnetic field). The methods supplied by Nonlinear Dynamics reveal signal characteristics that are not revealed by linear methods like FFT. Better understanding of principles that govern dynamics and complexity of EEG‐signal can help to find ‘the signatures’ of different physiological and pathological states of human brain, quantitative characteristics that may find applications in medical diagnostics.