Print Email Facebook Twitter Validating models of sensory conflict and perception for motion sickness prediction Title Validating models of sensory conflict and perception for motion sickness prediction Author Irmak, T. (TU Delft Intelligent Vehicles) Pool, D.M. (TU Delft Control & Simulation) de Winkel, K.N. (TU Delft Intelligent Vehicles) Happee, R. (TU Delft Intelligent Vehicles) Date 2023 Abstract The human motion perception system has long been linked to motion sickness through state estimation conflict terms. However, to date, the extent to which available perception models are able to predict motion sickness, or which of the employed perceptual mechanisms are of most relevance to sickness prediction, has not been studied. In this study, the subjective vertical model, the multi-sensory observer model and the probabilistic particle filter model were all validated for their ability to predict motion perception and sickness, across a large set of motion paradigms of varying complexity from literature. It was found that even though the models provided a good match for the perception paradigms studied, they could not be made to capture the full range of motion sickness observations. The resolution of the gravito-inertial ambiguity has been identified to require further attention, as key model parameters selected to match perception data did not optimally match motion sickness data. Two additional mechanisms that may enable better future predictive models of sickness have, however, been identified. Firstly, active estimation of the magnitude of gravity appears to be instrumental for predicting motion sickness induced by vertical accelerations. Secondly, the model analysis showed that the influence of the semicircular canals on the somatogravic effect may explain the differences in the dynamics observed for motion sickness induced by vertical and horizontal plane accelerations. Subject Motion sicknessPerceptual modellingSensory conflictSensory integrationState estimation To reference this document use: http://resolver.tudelft.nl/uuid:ac1e1e53-0b18-47ca-8aa7-56efcc6398f2 DOI https://doi.org/10.1007/s00422-023-00959-8 ISSN 0340-1200 Source Biological Cybernetics: communication and control in organisms and automata, 117 (3), 185-209 Part of collection Institutional Repository Document type journal article Rights © 2023 T. Irmak, D.M. Pool, K.N. de Winkel, R. Happee Files PDF s00422_023_00959_8.pdf 1.38 MB Close viewer /islandora/object/uuid:ac1e1e53-0b18-47ca-8aa7-56efcc6398f2/datastream/OBJ/view