Detection of Epileptic Seizures Using Video Data

Abstract

Monitoring of epileptic patients is usually done by video/EEG-monitoring which is considered as the golden standard. Due to some disadvantages of this method, this method is not feasible to use in long term home monitoring. Video monitoring provides a solution to this problem as it can monitor the patient in a non-contacting way. An algorithm is developed to detect movement epochs in nocturnal datasets for pediatric epileptic patients. The performance was measured using a threefold crossvaildation, which resulted in a sensitivity of 1 and a positive predictive value above 0.85.