Help Privacy Policy Disclaimer
  Advanced SearchBrowse





A Cybernetic Approach to Self-Motion Perception


Soyka,  F
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available

Soyka, F. (2013). A Cybernetic Approach to Self-Motion Perception. Berlin, Germany: Logos Verlag.

Cite as: https://hdl.handle.net/21.11116/0000-0001-3C05-7
Self-motion describes the motion of our body through the environment and is an essential part of our everyday life. The aim of this thesis is to improve our understanding of how humans perceive self-motion, mainly focusing on the role of the vestibular system. Following a cybernetic approach, this is achieved by systematically gathering psychophysical data and then describing it based on mathematical models of the vestibular sensors. Three studies were performed investigating perceptual thresholds for translational and rotational motions and reaction times to self-motion stimuli. Based on these studies, a model is introduced which is able to describe thresholds for arbitrary motion stimuli varying in duration and acceleration profile shape. This constitutes a significant addition to the existing literature since previous models only took into account the effect of stimulus duration, neglecting the actual time course of the acceleration profile. In the first and second study model parameters were identified based on measurements of direction discrimination thresholds for translational and rotational motions. These models were used in the third study to successfully predict differences in reaction times between varying motion stimuli proving the validity of the modeling approach. This work can allow for optimizing motion simulator control algorithms based on self-motion perception models and developing perception based diagnostics for patients suffering from vestibular disorders.