Mental Workload Classification Method Based on EEG Cross-Session Subspace Alignment

Mental Workload Classification Method Based on EEG Cross-Session Subspace Alignment

Electroencephalogram (EEG) signals are sensitive to the level of Mental Workload (MW). However, the random non-stationarity of EEG signals will lead to low accuracy and a poor generalization ability for cross-session MW classification. To solve this problem of the different marginal distribution of...

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Bibliographic Details
Main Authors: Hongquan Qu, Mengyu Zhang, Liping Pang
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Mathematics
Subjects:
Mental Workload
EEG
domain adaptation
KL divergence
subspace alignment
Online Access:https://www.mdpi.com/2227-7390/10/11/1875

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https://www.mdpi.com/2227-7390/10/11/1875

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