Abstract

Patients with absence epilepsy fail to report almost 90% of their seizures. The clinical gold standard to assess absence seizures is video-electroencephalography (vEEG) recorded in the hospital, an expensive and obtrusive procedure which requires also extended reviewing time. Wearable sensors, which allow the recording of electroencephalography (EEG), accelerometer and gyroscope have been used to monitor epileptic patients in their home environment for the first time. We developed a pipeline for accurate and robust absence seizure detection while reducing the review time of the long recordings. Our results show that multimodal analysis of absence seizures can improve the robustness to false alarms, while retaining a high sensitivity in seizure detection.

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