Intracranial Electroencephalogram Based Epilepsy Seizure Onset Detection
Published in ICMLC, 2020
In this study, we introduce an intracranial Electroencephalogram (iEEG)-based seizure detection algorithm that leverages high-frequency components in iEEG signals, achieving over 99% accuracy and a 94% F1 score on 1-second windows across three patients. Our analysis of various classifiers, considering both performance and power consumption, identifies gradient boosted decision trees as the most suitable for this task. Paper Url
Recommended citation: Fan, Boyu, et al. “Intracranial Electroencephalogram Based Epilepsy Seizure Onset Detection: Proceedings of the 2020 12th International Conference on Machine Learning and Computing.” ACM Conferences, 1 Feb. 2020, dl.acm.org/doi/10.1145/3383972.3384053#sec-cit.