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Optical Brain Imaging to Enhance UAV Operator Training, Evaluation, and Interface Development
Journal article   Peer reviewed

Optical Brain Imaging to Enhance UAV Operator Training, Evaluation, and Interface Development

Justin Menda, James Hing, Hasan Ayaz, Patricia Shewokis, Kurtulus Izzetoglu, Banu Onaral and Paul Oh
Journal of intelligent & robotic systems, v 61(1), pp 423-443
Jan 2011

Abstract

Engineering UAV Training Control , Robotics, Mechatronics Artificial Intelligence (incl. Robotics) UAV pilot interface Mechanical Engineering UAV safety fNIR Electrical Engineering Optical brain imaging
As the use of unmanned aerial vehicles expands to near earth applications and force multiplying scenarios, current methods of operating UAVs and evaluating pilot performance need to expand as well. Many human factors studies on UAV operations rely on self reporting surveys to assess the situational awareness and cognitive workload of an operator during a particular task, which can make objective evaluations difficult. Functional Near-Infrared Spectroscopy (fNIR) is an emerging optical brain imaging technology that monitors brain activity in response to sensory, motor, or cognitive activation. fNIR systems developed during the last decade allow for a rapid, non-invasive method of measuring the brain activity of a subject while conducting tasks in realistic environments. This paper investigates deployment of fNIR for monitoring UAV operator’s cognitive workload and situational awareness during simulated missions. The experimental setup and procedures are presented with some early results supporting the use of fNIR for enhancing UAV operator training, evaluation and interface development.

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Web of Science research areas
Computer Science, Artificial Intelligence
Robotics
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