Changes in feature generation provided incremental discrimination power to differentiate between hyperkinetic, tonic, and tonic-clonic seizures. Motion features from the catch22 feature collection extracted from video were explored to transform the patients' videos into numerical time series for clustering and visualization. Only seizures with unequivocal hyperkinetic, tonic, and tonic-clonic semiology were included. 10 subjects with 130 seizures were included in the training dataset, and 17 different subjects with 98 seizures formed the testing dataset. 3D near-infrared video was recorded by the Nelli® seizure monitoring system. This study evaluated the accuracy of motion signals extracted from video monitoring data to differentiate epileptic motor seizures in subjects with drug-resistant epilepsy. You just subscribed to receive the final version of the article
