Detrended fluctuation analysis of EEG recordings for epileptic seizure detection

In this paper, the detrended fluctuation analysis (DFA) is used to quantify the fractal-like scaling properties of the EEG signals. The power-law exponent of DFA of the EEG time series was used to distinguish subjects with epilepsy from healthy controls. The performance of the proposed method was evaluated using the receiver operating characteristics (ROC) curves. The obtained results show that the DFA technique achieves high detection accuracy rate (98%) on distinguishing the epileptic seizure from the normal healthy EEG.