Estimation of cognitive workload during simulated air traffic control using optical brain imaging sensors

Abstract

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. © 2011 Springer-Verlag.