Bidirectional-Pass Algorithm for Interictal Event Detection

Epilepsy is one of the most invalidating neurological conditions, affecting 1\(\%\) of the global population. The main diagnostic tool for epilepsy is electroencephalography (EEG), used to detect local field potentials and discern pathological brain patterns, i.e., ictal activity (the EEG correlate of a clinical seizure) and interictal activity (the pathological brain pattern occurring between seizures). Interictal activity may provide insights into seizure generation mechanisms and may contain information relevant to the identification of the seizure onset zone. Further, interictal activity may be relevant for seizure prediction algorithms. This paper presents a algorithm for accurate detection of interictal events using a combination of mathematical methods.