Estimating distribution shifts for predicting cross-subject generalization in electroencephalography-based mental workload assessment

Assessment of mental workload in real-world conditions is key to ensuring the performance of workers executing tasks that demand sustained attention. Previous literature has employed electroencephalography (EEG) to this end despite having observed that EEG correlates of mental workload vary across s...

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Detalles Bibliográficos
Autores principales: Albuquerque, Isabela, Monteiro, João, Rosanne, Olivier, Falk, Tiago H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9576998/
https://www.ncbi.nlm.nih.gov/pubmed/36267659
http://dx.doi.org/10.3389/frai.2022.992732

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9576998/
https://www.ncbi.nlm.nih.gov/pubmed/36267659
http://dx.doi.org/10.3389/frai.2022.992732

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