Most of EEG information in clinical practice has been obtained from EEG waveform analysis by visual inspection. As digital EEG recording becomes popular in many hospital, computational analysis of EEG has been a new method for the analysis of clinical EEG. Among many computational tools for the manipulation of recorded EEG time series, linear methods such as frequency analysis, power spectral analysis, and other statistical analysis were applied at first. However, after the realization of the non-linear nature of biological signals, some researchers started to apply non-linear dynamics for the analysis of digital EEG data. Basic concept of non-linearity and chaos theory were reviewed in this article. And approach to chaotic system through several non-linear chaos parameters such as correlation dimension and largest Lyapunov exponent were followed; basic principles of chaos parameters, clinical application examples of the chaos parameters.
