An EEG-based mental workload estimator trained on working memory task can work well under simulated multi-attribute task

An EEG-based mental workload estimator trained on working memory task can work well under simulated multi-attribute task

Mental workload (MW)-based adaptive system has been found to be an effective approach to enhance the performance of human-machine interaction and to avoid human error caused by overload. However, MW recognized from the spontaneously generated electroencephalogram (EEG) was found to be task-specific....

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Bibliographic Details
Main Authors: Yufeng eKe, Hongzhi eQi, Feng eHe, Shuang eLiu, Xin eZhao, Peng eZhou, Lixin eZhang, Dong eMing
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-09-01
Series:Frontiers in Human Neuroscience
Subjects:
EEG
Feature Selection
Working memory task
Mental Workload
Cross-task
multi-attribute task
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.00703/full

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