TY - GEN
T1 - Estimation of cognitive workload during simulated air traffic control using optical brain imaging sensors
AU - Ayaz, Hasan
AU - Willems, Ben
AU - Bunce, Scott
AU - Shewokis, Patricia A.
AU - Izzetoglu, Kurtulus
AU - Hah, Sehchang
AU - Deshmukh, Atul
AU - Onaral, Banu
N1 - Funding Information:
Acknowledgments. This work was supported by the U.S. Federal Aviation Administration through BAE Systems Technology Solutions Services Inc. under Primary Contract, DTFA01-00-C-00068 and Subcontract Number, 31-5029862.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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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U2 - 10.1007/978-3-642-21852-1_63
DO - 10.1007/978-3-642-21852-1_63
M3 - Conference contribution
AN - SCOPUS:79960311694
SN - 9783642218514
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 549
EP - 558
BT - Foundations of Augmented Cognition
T2 - 6th International Conference on Foundations of Augmented Cognition, FAC 2011, Held as Part of HCI International 2011
Y2 - 9 July 2011 through 14 July 2011
ER -