OBJECTIVE: The authors describe research and applications in prominent areas of neuroergonomics. BACKGROUND: Because human factors/ergonomics examines behavior and mind at work, it should include the study of brain mechanisms underlying human performance. METHODS: Neuroergonomic studies are reviewed in four areas: workload and vigilance, adaptive automation, neuroengineering, and molecular genetics and individual differences. RESULTS: Neuroimaging studies have helped identify the components of mental workload, workload assessment in complex tasks, and resource depletion in vigilance. Furthermore, real-time neurocognitive assessment of workload can trigger adaptive automation. Neural measures can also drive brain-computer interfaces to provide disabled users new communication channels. Finally, variants of particular genes can be associated with individual differences in specific cognitive functions. CONCLUSIONS: Neuroergonomics shows that considering what makes work possible - the human brain - can enrich understanding of the use of technology by humans and can inform technological design. APPLICATION: Applications of neuroergonomics include the assessment of operator workload and vigilance, implementation of real-time adaptive automation, neuroengineering for people with disabilities, and design of selection and training methods.
OBJECTIVE: The authors describe research and applications in prominent areas of neuroergonomics. BACKGROUND: Because human factors/ergonomics examines behavior and mind at work, it should include the study of brain mechanisms underlying human performance. METHODS: Neuroergonomic studies are reviewed in four areas: workload and vigilance, adaptive automation, neuroengineering, and molecular genetics and individual differences. RESULTS: Neuroimaging studies have helped identify the components of mental workload, workload assessment in complex tasks, and resource depletion in vigilance. Furthermore, real-time neurocognitive assessment of workload can trigger adaptive automation. Neural measures can also drive brain-computer interfaces to provide disabled users new communication channels. Finally, variants of particular genes can be associated with individual differences in specific cognitive functions. CONCLUSIONS: Neuroergonomics shows that considering what makes work possible - the human brain - can enrich understanding of the use of technology by humans and can inform technological design. APPLICATION: Applications of neuroergonomics include the assessment of operator workload and vigilance, implementation of real-time adaptive automation, neuroengineering for people with disabilities, and design of selection and training methods.
Authors: Vincent P Clark; Brian A Coffman; Andy R Mayer; Michael P Weisend; Terran D R Lane; Vince D Calhoun; Elaine M Raybourn; Christopher M Garcia; Eric M Wassermann Journal: Neuroimage Date: 2010-11-19 Impact factor: 6.556
Authors: Kuan-Hua Chen; Michelle L Rusch; Jeffrey D Dawson; Matthew Rizzo; Steven W Anderson Journal: Soc Cogn Affect Neurosci Date: 2015-03-29 Impact factor: 3.436
Authors: Julian Lim; Richard Ebstein; Chun-Yu Tse; Mikhail Monakhov; Poh San Lai; David F Dinges; Kenneth Kwok Journal: PLoS One Date: 2012-03-16 Impact factor: 3.240