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02.09.2022 15:18

Project explores early detection of motion sickness in prospective German Armed Forces pilots

Christina Haberland Wissenschaftskommunikation
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE

    Pilot training is a complex and cost-intensive task for the German Armed Forces. It is therefore an important goal to reduce costs and delays whenever possible. Especially during training, some pilot candidates suffer from symptoms of motion induced illness also known as motion sickness or kinetosis. Affected candidates then usually have to interrupt training in order to undergo desensitization training, causing significant costs and delays. To prevent such cases in the future, the German Armed Forces have launched the project "KiRis" led by Fraunhofer FKIE and in collaboration with the German Aerospace Center (DLR) and the Universität der Bundeswehr München.

    The goal of the “Early Detection of Kinetosis Risk” (KiRis) project is to develop an AI and simulator-based method for the early detection of the motion sickness tendency of pilot candidates.

    Nausea, disorientation, and visual impairments – the symptoms of motion sickness that occur in unfamiliar movement situations not only cause those affected to feel queasy but can also lead to mistakes with serious consequences and accidents in safety-critical situations. "However, assessing whether someone is susceptible to motion sickness is difficult," explains FKIE scientist and KiRis project manager Mara Kaufeld. "In the case of German Armed Forces pilot candidates, this usually becomes apparent during their initial flight training in the USA. If a candidate develops severe motion sickness symptoms during this phase, he or she has to temporarily interrupt the training cycle to undergo desensitization training. One of the very limited, high-quality training slots thus remains vacant, resulting in significant delays in training.”

    According to data from the U.S. Air Force and the German Air Force (Luftwaffe), between 10 to 20 percent of pilot candidates show symptoms of motion sickness during flight training. But how can we determine if a training candidate is susceptible to motion sickness? Are there general psychophysiological signs that can be used to gauge risk? These are the questions the research team is investigating in the KiRis project.

    Developing a reliable model for the prediction of motion sickness

    "For the project, we are fortunate to have access to the simulator and the impressive motion cueing system of our partner, the German Aerospace Center (DLR)," says motion sickness expert, Mara Kaufeld. In the future, pilot candidates will complete specially developed test scenarios in this simulator. The physiological reactions they show will be documented, analyzed, combined with previous motion sickness experiences, and finally correlated with the occurrence of motion sickness in actual flight training. The aim is to apply machine learning methods to identify risk factors and use them to develop a model for predicting motion sickness susceptibility as reliably as possible.

    The study, awarded by the German Armed Forces (Planungsamt der Bundeswehr), is scheduled for a period of three years. FKIE is responsible for the overall coordination, the scientific presentation of motion sickness, the selection of suitable physiological parameters for its prediction, and the conceptual design, preparation and monitoring of the tests. The results of these tests will then be scientifically analyzed and evaluated.

    The main contribution of the Institute of Flight Systems (IFS) of the Universität der Bundeswehr München is the creation of realistic scenarios and missions as well as the implementation of special eye-tracking technologies as part of the sensor technology used in the study. It is also responsible for carrying out the actual measurement campaigns and evaluating measurements of eye movement.

    The entire test infrastructure is provided by DLR's Institute of System Dynamics and Control (SR). Primarily, this relates to the simulator environment including the flight dynamics models and the cockpit module. DLR is also responsible for developing the motion algorithms and real-time visualizations tailored to the test scenarios.

    On the German Armed Forces side, the German Air Force Command (Kdo Lw) and the Air Force Center for Aerospace Medicine (ZentrLuRMedLw) are supporting the project. ZentrLuRMedLw project manager, Colonel Dr. Oliver Erley (medial corps): "For the German Armed Forces, the focus of this project is on providing optimal support to the next generation of pilots. With the help of the project, a unique competence is to be built up and established in the long term for the German Armed Forces to ensure the highest level of air safety now and in the future."


    Wissenschaftliche Ansprechpartner:

    Mara Kaufeld
    Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE
    Department "Human Systems Engineering"
    Research Group "Human Factors Analysis"
    Phone: +49 228 502 12 419
    Mail: mara.kaufeld@fkie.fraunhofer.de


    Weitere Informationen:

    https://www.fkie.fraunhofer.de/en/press-releases.html


    Bilder

    The goal of the research project "KiRis" is to develop an AI and simulator-based method for the early detection of the motion sickness tendency of German Armed Forces pilot candidates. In the picture: Fraunhofer FKIE, DLR and UniBw München project team.
    The goal of the research project "KiRis" is to develop an AI and simulator-based method for the earl ...

    Fraunhofer FKIE


    Merkmale dieser Pressemitteilung:
    Journalisten, Wissenschaftler
    Informationstechnik, Medizin, Verkehr / Transport
    überregional
    Forschungsprojekte, Kooperationen
    Englisch


     

    The goal of the research project "KiRis" is to develop an AI and simulator-based method for the early detection of the motion sickness tendency of German Armed Forces pilot candidates. In the picture: Fraunhofer FKIE, DLR and UniBw München project team.


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