Epileptic Seizure Detection by Cascading Isolation Forest-based Anomaly Screening and EasyEnsemble

The electroencephalogram (EEG), for measuring the electrophysiological activity of the brain, has been widely applied in automatic detection of epilepsy seizures. Various EEG-based seizure detection algorithms have already yielded high sensitivity, but training those algorithms requires a large amou...

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Veröffentlicht in:	IEEE transactions on neural systems and rehabilitation engineering Jg. 30; S. 1
Hauptverfasser:	Guo, Yao, Jiang, Xinyu, Tao, Linkai, Meng, Long, Dai, Chenyun, Long, Xi, Wan, Feng, Zhang, Yuan, Van Dijk, Johannes, Aarts, Ronald M., Chen, Wei, Chen, Chen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	aEEG Algorithms Anomalies Anomaly detection Band-pass filters Child Convulsions & seizures EEG Electroencephalography Epilepsy Epilepsy - diagnosis Feature extraction Forestry Forests Humans Hybrid systems Labeling Labelling Learning Low-pass filters Machine learning Modules Screening Segmentation Segments Seizure detection system Seizures Seizures - diagnosis Sensitivity Signal Processing, Computer-Assisted supervised learning unsupervised learning Workload Workloads
ISSN:	1534-4320, 1558-0210, 1558-0210
Online-Zugang:	Volltext
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