Leveraging deep learning for robust EEG analysis in mental health monitoring

Mental health monitoring utilizing EEG analysis has garnered notable interest due to the non-invasive characteristics and rich temporal information encoded in EEG signals, which are indicative of cognitive and emotional conditions. Conventional methods for EEG-based mental health evaluation often de...

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Veröffentlicht in:	Frontiers in neuroinformatics Jg. 18; S. 1494970
Hauptverfasser:	Liu, Zixiang, Zhao, Juan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Research Foundation 03.01.2025 Frontiers Media S.A
Schlagworte:	Adaptability Algorithms application of EEG Brain research Datasets Deep learning EEG Electroencephalography Graph representations Information processing Machine learning Mental disorders Mental health mental health monitoring neural electrical signals Neural networks Support vector machines transformer transformer mental health monitoring EEG application of EEG neural electrical signals
ISSN:	1662-5196, 1662-5196
Online-Zugang:	Volltext
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