“Facial expression affective state recognition for air traffic control automation concept exploration” by Reisman and El Kaliouby

Current methods for evaluating workload and usability of air traffic control automation concepts are often heavily reliant on subjective data. Typically subjects (often off-duty air traffic controllers) assess new tools or technologies in controlled experimental sessions, and then report on their memories of the session experience in some structured format, such as interviews, surveys, or scalar responses to standardized questions. These subjective reports may be affected by post-session memory distortions, and concurrent validation of is often difficult.

1. Reisman, R., and Brown, D, (2006) Design of Augmented Reality Tools for Air Traffic Control Towers, 6th AIAA Aviation Technology, Integration and Operations Conference (ATIO), Wichita, Kansas (September, 2006)
2. El Kaliouby, R., and Robinson, P., (2005) Real-time Inference of Complex Mental States from Facial Expressions and Head Gestures, in Real-Time Vision for Human-Computer Interaction, ed. Kisacanin, B., et al, pp. 181–200 (Springer-Verlag, 2005)