Assessment of Ocular and Physiological Metrics to Discriminate Flight Phases in Real Light Aircraft

Sébastien Scannella · Vsevolod Peysakhovich · Florian Ehrig · Evelyne Lepron · Frédéric Dehais

49 citations0/0 files storedHuman Factors The Journal of the Human Factors and Ergonomics Society

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Human-Automation Interaction and Safety Sleep and Work-Related Fatigue Gaze Tracking and Assistive Technology

Abstract

OBJECTIVE: The purpose of the present study was to find psychophysiological proxies that are straightforward to use and could be implemented in actual flight conditions to accurately discriminate pilots' workload levels. BACKGROUND: Piloting an aircraft is a complex activity where cognitive limitations may jeopardize flight safety. There is a need to implement solutions to monitor pilots' workload level to improve flight safety. There has been recent interest in combining psychophysiological measurements. Most of these studies were conducted in flight simulators at the group level, limiting the interpretation of the results. METHODS: We conducted an experiment with 11 pilots performing two standard traffic patterns in a light aircraft. Five metrics were derived from their ocular and cardiac activities and were evaluated through three flight phases: takeoff, downwind, and landing. RESULTS: Statistical analyses showed that the saccadic rate was the most efficient metric to distinguish between the three flight phases. In addition, a classifier trained on the ocular data collected from the first run predicted the flight phase within a second run with an accuracy of 75%. No gain in the classifier accuracy has been found by combining cardiac and ocular metrics. CONCLUSIONS: Ocular-based metrics may be more suitable than cardiac ones to provide relevant information on pilots' flying activity in operational settings. APPLICATIONS: Electrocardiographic and eye-tracking devices could be implemented in future cockpits as additional flight data for accident analysis, an objective pilot's state evaluation for training, and proxies for human-machine interactions to improve flight safety.

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1988Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research 2012Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness 2002An Analysis of Mental Workload in Pilots During Flight Using Multiple Psychophysiological Measures 2013Using near infrared spectroscopy and heart rate variability to detect mental overload 1998A comparison of heart rate, eye activity, EEG and subjective measures of pilot mental workload during flight.1992Assessing pilot workload. Why measure heart rate, HRV and respiration?2009Attentional Tunneling and Task Management in Synthetic Vision Displays 2013Failure to Detect Critical Auditory Alerts in the Cockpit

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