Mental workload and task engagement evaluation based on changes in electroencephalogram

被引：8
作者：
Rabbi, Ahmed Fazle [1 ]
Zony, Abongwa [1 ]
de Leon, Pablo [2 ]
Fazel-Rezai, Reza [1 ]
机构：
[1] Biomedical Signal Processing Laboratory, Department of Electrical Engineering, University of North Dakota, Grand Forks, ND 58202, United States
[2] Department of Space Studies, University of North Dakota, Grand Forks, ND 58202, United States
来源：
Biomedical Engineering Letters | 2012年 / 2卷 / 03期
关键词：
Manned space flight;
D O I：
10.1007/s13534-012-0065-8
中图分类号：
学科分类号：
摘要：
Purpose: In this study, electroencephalogram (EEG) signals were used to assess subject's mental workload and task engagement level during a set of neurocognitive tasks in an experimental space suit. Methods: EEG signals were collected using a wireless EEG system during two experimental conditions - when subjects did/did not wear space suit. Brain state changes based on EEG changes were quantified and compared with the direct responses of the subjects for different tasks. In addition, a statistical test of significance on the computed EEG index for the two experimental conditions was performed. Results: It was found that the spacesuit experiment introduced a greater mental workload where subject's stress levels were higher than control experiment. Results indicated significant differences in task engagement between the spacesuit and control experiments for most of the tasks. Conclusions: The findings could be useful in monitoring astronaut's or human subject's cognitive performance in assuring safety as well as improving the performance. © 2012 Korean Society of Medical and Biological Engineering and Springer.
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收藏
页码：139 / 146
页数：7
相关论文
共 44 条
[1]  
Molloy R.(1993)Performance consequences of automation induced “complacency” Int J Aviats Psychol. 3 1-23
[2]  
Singh I.L.(1995)Biocybernetic system evaluates indices of operator engagement in atuomated task J Biol Psychol. 40 187-195
[3]  
Parasuram R.(2003)Effects of a psychophysiological system for adaptive automation on performance, workload, and the event-related potential P300 component Hum Factors. 45 601-613
[4]  
Pope A.T.(1993)Lapses in alertness: Coherence of fluctuations in performances and EEG spectrum Electroen Clin Neuro. 86 23-35
[5]  
Bogart E.H.(1995)Changes in alertness are principal component in variance in the EEG spectrum Neuroreport. 7 213-216
[6]  
Bartolome D.S.(1996)Tonic, phasic, and transient EEG correlates of auditory awareness in drowsiness Cognitive Brain Res. 4 15-25
[7]  
Prinzel L.J.(2004)Real-time analysis of EEG indices of alertness, cognition, and memory with a wireless headset Int J Hum-Comput Int. 17 151-170
[8]  
Freeman F.G.(2007)EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks Aviat Space Envir Md. 78 B231-B244
[9]  
Scerbo M.W.(1997)Estimating alertness from EEG power spectrum IEEE T Bio-med Eng. 44 60-69
[10]  
Mikulka P.J.(2005)Estimating driving performance based on EEG spectrum analysis EURASIP J Appl Signal Process. 19 3165-3174
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