Performance reassessment of a real-time seizure-detection algorithm on long ECoG series.

Purpose: Automated seizure detection and blockage requires highly sensitive and specific algorithms. This study reassessed the performance of an algorithm by using a more extensive database than that of a previous study and its suitability for safety/efficacy closed-loop studies to block seizures in humans.

Methods: Up to eight electrocorticography (EcoG) channels from 15 subjects were analyzed off-line.