Nonlinear dynamics and chaos theory have been used in neurophysiology with the aim to understand the complex brain activity from electroencephalographic (EEG) signals. Although linear methods have been the most used in EEG analysis, nonlinear approaches have been increased their presence because they reveal aspects that cannot be measured from linear approaches. However, published works in this scientific field is still very low. This work describes the fundamentals of EEG signals and its basic concepts related with nonlinear dynamics and chaotic measures of complexity and stability. After that, a short review of the most common EEG-based applications is given in medical and non-medical contexts.
Rodr?guez-Berm?dez, Germ?n and J. Garc?a-Laencina, Pedro
"Analysis of EEG Signals using Nonlinear Dynamics and Chaos: A review,"
Applied Mathematics & Information Sciences: Vol. 09:
5, Article 12.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol09/iss5/12