Neuroergonomics: Research and practice

By Raja Parasuraman. 2003

300 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Radiological and Ultrasound Technology, Social Psychology

View Paper: https://www.semanticscholar.org/paper/0d75d1aceef6279be67045471cbf3344efb55042

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In Biomedical Engineering

In Radiological and Ultrasound Technology

In Social Psychology

Citations in the corpus

Measurement of Trust in Automation: A Narrative Review and Reference Guide (2021, background): “…one of the fastest growing areas of TiA measurement, in part due to the plethora of pre-existing physiological measures that can be drawn from human-human trust measurement and the growing field of neuroergonomics that embraces this methodology (Parasuraman, 2003, 2011; Gramann et al., 2017).”
Imaging Brain Fatigue from Sustained Mental Workload: An ASL Perfusion Study of the Time-On-Task Effect (2009, background): “In particular, the emerging field of neuroergonomics aims to study the neural basis of cognitive and physical work in order to optimize mental functioning (Parasuraman, 2003; Parasuraman and Wilson, 2008).”
Cerebral Hemodynamics and Vigilance Performance (2009, methodology): “The experiments that we have described are part of an emerging effort in human factors developed by Parasuraman and Rizzo known as neuroergonomics, the study of the brain at work (Parasuraman, 2003; Parasuraman & Rizzo, 2007, Parasuraman & Wilson, 2008).”
EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks. (2007, background): “This approach, termed “neuroergonomics,” is an interdisciplinary area of research and practice that integrates understanding of the neural bases of cognition and behavior with the design, development and implementation of technology (21,29,34,35).”
Almost human: Anthropomorphism increases trust resilience in cognitive agents. (2016, background): “Neuroimaging studies may be helpful in determining an underlying threshold and mechanisms for trusting automated agents varying in anthropomorphism (Krach et al., 2008), consistent with a neuroergonomic approach to understanding human performance with automation (Parasuraman, 2003, 2011).”
Optical brain monitoring for operator training and mental workload assessment (2012, unknown): “An accurate and reliable measure of the operator'smentalworkload is a critical component of any such adaptive aiding system (Parasuraman, 2003).”