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Objectives
High counts of averaged interictal epileptiform discharges (IEDs) are key components of accurate interictal electric source imaging (ESI) in patients with focal epilepsy. Automated detections may be time‐efficient, but they need to identify the correct IED types. Thus we compared semiautomated and automated detection of IED types in long‐term video‐EEG (electroencephalography) monitoring...
The Wearables for Epilepsy And Research (WEAR) International Study Group identified a set of methodology standards to guide research on wearable devices for seizure detection. We formed an international consortium of experts from clinical research, engineering, computer science, and data analytics at the beginning of 2020. The study protocols and practical experience acquired during the development...
Noninvasive wearable devices have great potential to aid the management of epilepsy, but these devices must have robust signal quality, and patients must be willing to wear them for long periods of time. Automated machine learning classification of wearable biosensor signals requires quantitative measures of signal quality to automatically reject poor‐quality or corrupt data segments. In this study,...
Objective
Movement‐based wearable sensors are used for detection of convulsive seizures. The identification of the absence of motion following a seizure, known as post‐ictal immobility (PI), may represent a potential additional application of wearables. PI has been associated with potentially life‐threatening complications and with sudden unexpected death in epilepsy (SUDEP). We aimed to assess whether...
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