Pattern Recognition of Momentary Mental Workload Based on Multi-Channel Electrophysiological Data and Ensemble Convolutional Neural Networks

In this paper, we deal with the Mental Workload (MWL) classification problem based on the measured physiological data. First we discussed the optimal depth (i.e., the number of hidden layers) and parameter optimization algorithms for the Convolutional Neural Networks (CNN). The base CNNs designed we...

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Detalles Bibliográficos
Autores principales: Zhang, Jianhua, Li, Sunan, Wang, Rubin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5447754/
https://www.ncbi.nlm.nih.gov/pubmed/28611583
http://dx.doi.org/10.3389/fnins.2017.00310

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5447754/
https://www.ncbi.nlm.nih.gov/pubmed/28611583
http://dx.doi.org/10.3389/fnins.2017.00310

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