A New Seizure Prediction Method Based on Return Map

Epilepsy is one of the most common neurological disorders and affects closely 50 million people worldwide. Theunpredictability of seizures onset is a main agony for all patients who has epilepsy. In this article, a new seizureprediction method based on chaos theory and nonlinear dynamics are used to make a return map based on zerocrossing to find the Preictal stage before Ictal stage in electroencephalographic (EEG) signal in order to seizureonset prediction. Our index is calculated for sliding windows and compared with adaptive threshold. Lastly our average prediction time is about 20±5 minutes with 86.6 % in sensitivity and 0.067 in FPR.

کلیدواژه ها:

seizure prediction ، return map ، zero crossing ، chaotic signal processing ، EEG