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Estimation of Cognitive Workload during Simulated Air Traffic Control Using Optical Brain Imaging Sensors
Book chapter   Open access

Estimation of Cognitive Workload during Simulated Air Traffic Control Using Optical Brain Imaging Sensors

Hasan Ayaz, Ben Willems, Scott Bunce, Patricia A Shewokis, Kurtulus Izzetoglu, Sehchang Hah, Atul Deshmukh and Banu Onaral
Foundations of Augmented Cognition. Directing the Future of Adaptive Systems, pp 549-558
2011
DOI: https://doi.org/10.1007/978-3-642-21852-1_63
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https://doi.org/10.1007/978-3-642-21852-1_63View
Published, Version of Record (VoR) Open Maybe Open Access (Publisher Bronze)

Abstract

Air Traffic Control Functional Near Infrared Spectroscopy Cognitive Workload fNIR Optical Brain Imaging
Deployment of portable neuroimaging technologies to operating settings could help assess cognitive states of personnel assigned to perform critical tasks and thus help improve efficiency and safety of human machine systems. Functional Near Infrared Spectroscopy (fNIR) is an emerging noninvasive brain imaging technology that relies on optical techniques to detect brain hemodynamics within the prefrontal cortex in response to sensory, motor, or cognitive activation. Collaborating with the FAA William J. Hughes Technical Center, fNIR has been used to monitor twenty four certified professional controllers as they manage realistic Air Traffic Control (ATC) scenarios under typical and emergent conditions. We have implemented a normalization procedure to estimate cognitive workload levels from fNIR signals during ATC by developing linear regression models that were informed by the respective participants’ prior n-back data. This normalization can account for oxygenation variance due to inter-personal physiological differences. Results indicate that fNIR is sensitive task loads during ATC.

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