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UAS Operator Workload Assessment During Search and Surveillance Tasks Through Simulated Fluctuations in Environmental Visibility
Book chapter   Peer reviewed

UAS Operator Workload Assessment During Search and Surveillance Tasks Through Simulated Fluctuations in Environmental Visibility

Jaime Kerr, Pratusha Reddy, Shahar Kosti and Kurtulus Izzetoglu
Augmented Cognition, pp 394-406
20 Jun 2019

Abstract

Cognitive workload fNIRS Sensor operator Unmanned aircraft systems
Unmanned aircraft system (UAS) sensor operators must maintain performance while tasked with multiple operations and objectives, yet are often subject to boredom and consequences of the prevalence-effect during area scanning and target identification tasks. Adapting training scenarios to accurately reflect real-world scenarios can help prepare sensor operators for their duty. Furthermore, integration of objective measures of cognitive workload and performance, through evaluation of functional near infrared spectroscopy (fNIRS) as a non-invasive measurement tool for monitor of higher-level cognitive functioning, can allow for quantitative assessment of human performance. This study sought to advance previous work regarding the assessment of cognitive and task performance in UAS sensor operators to evaluate expertise development and responsive changes in mental workload.

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7 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Web of Science research areas
Behavioral Sciences
Computer Science, Artificial Intelligence
Computer Science, Cybernetics
Computer Science, Interdisciplinary Applications
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