Study to Validate Novel Seizure-Detection Algorithm

Seizures are paroxysmal, abnormal behaviors which usually are associated with altered awareness and amnesia. The frequency of seizures is not easily documented. The individual who suffers from seizures may be unaware that a seizure is occurring. Many seizures, including generalized major motor seizures, have stereotyped, vigorous motor activity associated with the events. Currently, accurate seizure detection relies on EEG and video which are limited by time, size and mobility. Seizure detection can also use biomarkers such as movement patterns described by gyroscopes. These devices can monitor patterns of movement which correspond to the activity during seizures and kept in a log of seizures without patient input. The log can be used to notify patients or caregivers of seizures. This study is to determine the accuracy of a system using a commercial, wearable device linked to a computer algorithm based in the cloud which stores the movement pattern and notifies the patient and others of a generalized major motor seizure. The accuracy will be determined by a comparison of the system detections to simultaneously recorded video electroencephalogram, considered the "gold standard" of seizure detection.