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Vestibular autorotation test in primary selection of military student pilots using neural networks
M Klokker1, L Brock-Nannestad, P Mikines
1Department of Otolaryngology, Head & Neck Surgery, Rigshospitalet, Copenhagen, Denmark.
Background:
Selection of student pilots to the Royal Danish Air Force involves a physical examination including a vestibular test. Usually tests for selection proposes are not well documented.
Hypothesis:
The result of the vestibular autorotation test (VAT) is correlated to the ability to learn to fly in a military context.
Methods:
A Multi Layer Perception neural network with three layers configured as a Back Propagation Network was tested using data originating from horizontal VAT of 59 student pilot candidates, given the outcome of the pre-jet basic flight check. In the analysis the leave-one-out method was used.
Results:
Based on horizontal data only the network correctly classified the student pilot candidates as having been passed or rejected within a verification error margin < 0.1.
Conclusion:
The result indicates that VAT performed at the initial physical examination is a powerful tool for the elimination of unfit student pilot candidates when data are analyzed in neural networks.
