Helicopters are inherently unstable. This means that a pilot needs to provide inputs constantly to stay in control of the aircraft. A seemingly basic task such as hovering in place requires a pilot to coordinate inputs to multiple controls devices, which affect the lift generated by the main rotor, the direction of this lift, and the thrust generated by the tail-rotor. These devices all affect each other, such that input to one device also requires inputs to the others. In short: helicopter control is a demanding task.
To control the aircraft, pilots rely on readings from the helicopter’s instruments as well as on their sense of motion. The central nervous system generates a sense of motion primarily on the basis of visual and inertial cues. When these cues are less reliable, so is the sense of motion. Consequently, one might hypothesize that a pilot’s workload is affected by the richness of the visual environment: flying through fog is more demanding than flying in fair weather.
In this project, we want to investigate whether we can measure a pilot’s workload using Near-Infrared Spectroscopy (NIRS). Participants will be recruited to fly a ‘helicopter’ in the Max Planck CyberMotion Simulator (pictured). They will need to hover in different visual conditions while their neural activity is recorded.
If you are intrigued by this project, comfortable working with participants and performing data analyses, and would like to do research on this topic at the Max Planck Institute for Biological Cybernetics, contact:
Dr. Ksander de Winkel
Max Planck Institute for Biological Cybernetics
Dept. Human Perception, Cognition and Action.
Phone: +49 7071 601 -641, Fax: -616