Non-invasive automated assessment of tonic attention (vigilance) of commercial airline pilots during simulated flights

With the goal of increasing the safety of civilian air flight, the detection of a decrease in pilot attention is becoming an important need in civilian aeronautics. Multiple models used for the detection of hypovigilant states have been developed over the years in experimental conditions, but barriers still exist limiting current use. First, some of these models require the execution of behavioral tasks that can disrupt pilot workflow. .Second, other models relying on the use of physiological monitoring devices are still too cumbersome. The main objective of this project is to review all of the scientific publications about hypovigilance detection models so that future functional models can integrate the best evidence available. Although the main domain of application is aeronautics, other domains would also benefit from such technologies such as ground transportation and medical care.

Faculty Supervisor:

Patrick Archambault

Student:

Maxime Huot-Lavoie

Partner:

Thales solutions numériques Inc

Discipline:

Medicine

Sector:

Aerospace and defense

University:

Université Laval