In order to develop a comprehensive test scenario to detect the risk of early motion induced kinetosis, in aviation more commonly known as airsickness (AS), we conducted a detailed survey on the experiences of jet-aircraft student pilots, flight instructors, and flight physicians to discover AS-related flight maneuvers and other non-motion-induced triggers. Subsequently, we use these findings to design test scenarios that simulate the relevant stimuli in a controlled laboratory setting. Additionally, we propose how gaze tracking can be used to get further information about the pilot’s behaviour. For instance, it gives information about head-down times related to secondary tasks and the use of landmarks for orientation in space. Finally, we suggest machine-learning algorithms that combine those parameters with psycho-physiological measures to estimate the AS risk.     «

In order to develop a comprehensive test scenario to detect the risk of early motion induced kinetosis, in aviation more commonly known as airsickness (AS), we conducted a detailed survey on the experiences of jet-aircraft student pilots, flight instructors, and flight physicians to discover AS-related flight maneuvers and other non-motion-induced triggers. Subsequently, we use these findings to design test scenarios that simulate the relevant stimuli in a controlled laboratory setting. Addition...     »