An Analysis of Mental Workload in Pilots During Flight Using Multiple Psychophysiological Measures

By Glenn F. Wilson. 2002

527 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology, Social Psychology

View Paper: https://www.semanticscholar.org/paper/04f70fb9d2e4679d3bf982616d5f7df78df154b9

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In Experimental and Cognitive Psychology

In Social Psychology

Citations in the corpus

Modeling and Predicting Mental Workload in En Route Air Traffic Control: Critical Review and Broader Implications (2007, background): “Research efforts in complex work systems such as piloting (e.g., Wilson, 2002), unmanned aerial vehicle control (e.g., Dixon, Wickens, & Chang, 2005), anesthesiology (e.g., Leedal & Smith, 2005), railway signaling (e.g., Pickup et al., 2005), and automobile driving (e.g., Recarte & Nunes, 2003)…”
A Review of the Mental Workload Literature (2007, background): “Wilson (2004) notes that pupil diameter generally increases with higher cognitive processing levels and it is sensitive to rapid changes in workload, however, when overload occurs, pupil diameter can become unresponsive to changes or even reverse its response.”
Removal of ocular artifacts from electro-encephalogram by adaptive filtering (2004, methodology): “For example, researchers in our laboratory are developing methods for accessing a pilot's functional state during flight, so that adaptive aid can be provided in the case of mental overload (WILSON, 2002; HANKINS and WILSON, 1998).”
EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks. (2007, background): “A variety of linear and nonlinear classifier models have been employed including linear, quadratic, and logistic discriminant function analysis (DFA), artificial neural networks (ANN), and support vector machines (13,15,20,41,54,57).”
A Random Glance at the Flight Deck: Pilots' Scanning Strategies and the Real-Time Assessment of Mental Workload (2007, methodology): “Departure and landing are also known to produce the greatest number of changes in psychophysiological data because of the increased level of cognitive demand placed on pilots during these important maneuvers (Wilson, 2002).”
What multimodal data can tell us about the students’ regulation of their learning process? (2019, background): “For example, cardiovascular data can reveal arousal, and heart rate and heart rate variation indices have been found to be measures of experienced cognitive load (e.g., Cranford, Tiettmeyer, Chuprinko, Jordan, & Grove, 2014; Haapalainen, Kim, Forlizzi, & Dey, 2010; Wilson, 2002).”
Measuring mental workload using physiological measures: A systematic review. (2019, background): “Differences in HR have been observed during different phases of actual flight, with highest HR during take off (Hankins and Wilson 1998; Hart and Hauser 1987; Wilson 2002) and simulated flight during ILS approach and landing (Lahtinen et al., 2007).”
Performance Enhancement in an Uninhabited Air Vehicle Task Using Psychophysiologically Determined Adaptive Aiding (2007, methodology): “For example, using data collected from general aviation pilots, Wilson (2002a) reported that eye blink rate decreased when pilots flew using only the aircraft instruments, heart rate increased during takeoffs and landings, and electroencephalographic (EEG) activity was affected by navigation tasks.”
Detecting stress during real-world driving tasks using physiological sensors (2005, methodology): “The EMG was placed on the trapezius (shoulder), which has been used as an indicator of emotional stress [16].”