A Novel Unsupervised Autoencoder-Based HFOs Detector in Intracranial EEG Signals

High frequency oscillations (HFOs) have demonstrated their potency acting as an effective biomarker in epilepsy. However, most of the existing HFOs detectors are based on manual feature extraction and supervised learning, which incur laborious feature selection and time-consuming labeling process. I...

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Veröffentlicht in:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) S. 1426 - 1430
Hauptverfasser:	Li, Weilai, Zhong, Lanfeng, Xiang, Weixi, Kang, Tongzhou, Lai, Dakun
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 23.05.2022
Schlagworte:	Continuous wavelet transforms convolutional variational autoencoder Detectors Hafnium oxide High frequency oscillation Sensitivity Signal processing algorithms Supervised learning Time-frequency analysis unsupervised detector
ISSN:	2379-190X
Online-Zugang:	Volltext
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