Abstract
Objective
Managing the progress of drug-resistant epilepsy patients implanted with the responsive neurostimulation (RNS) system requires the manual evaluation of hundreds of hours of intracranial recordings. The generation of these large amounts of data and the scarcity of experts’ time for evaluation, necessitates the development of automatic tools to detect intracranial electroencephalographic seizure patterns (iESPs) with expert-level accuracy. We developed an intelligent system for identifying the presence and onset time of iESPs in intracranial EEG (iEEG) recordings from the RNS device.
Methods
An ...
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