Human Factors The Journal of the Human Factors and Ergonomics Society · 2008 · 217 citations · 41 references
Life SciencesMolecular GeneticsNeuroscienceCognitive NeuroscienceErgonomicsNeurogeneticsCognitive ErgonomicsCognitive LoadCognitive WorkloadErgonomic AssessmentFunctional NeuroimagingPhysical ErgonomicsAdaptive AutomationErgonomic WorkloadMental Workload AssessmentOperator Cognitive WorkloadOperator WorkloadPhysical WorkloadWorkloadWorkload Assessment
Human factors/ergonomics examines behavior and mind at work, so it should include the study of brain mechanisms underlying human performance. The authors aim to describe neuroergonomics research and its applications, such as workload assessment, adaptive automation, neuroengineering for disabilities, and training design. The review covers neuroergonomic studies across workload and vigilance, adaptive automation, neuroengineering, and molecular genetics. Neuroimaging reveals mental workload components and vigilance resource depletion, enabling real‑time adaptive automation and brain‑computer interfaces, while gene variants correlate with cognitive differences, demonstrating that neuroergonomics enhances technology design by integrating brain mechanisms.
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.
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