Modeling embodiment during the rubber hand illusion

A dynamical model validated by a time-varied experiment

Master Thesis (2022)
Author(s)

A.J. Knijnenburg (TU Delft - Mechanical Engineering)

Contributor(s)

A. Zgonnikov – Mentor (TU Delft - Human-Robot Interaction)

Phillip Beckerle – Mentor (Friedrich-Alexander-Universität Erlangen-Nürnberg)

G. Smit – Graduation committee member (TU Delft - Medical Instruments & Bio-Inspired Technology)

M. Wisse – Graduation committee member (TU Delft - Robot Dynamics)

Faculty
Mechanical Engineering
Copyright
© 2022 Brenda Knijnenburg
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Brenda Knijnenburg
Graduation Date
31-10-2022
Awarding Institution
Delft University of Technology
Programme
['Biomedical Engineering']
Faculty
Mechanical Engineering
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Abstract

A common method to investigate multisensory integration is using multisensory illusions. The rubber hand illusion is one of the best-known multisensory illusion used in clinical applications. By stroking a visible rubber hand and the participant’s occluded hand, the illusion arises that the rubber hand belongs to the participant. Possible applications based on this illusion are for neurorehabilitation or developing robotic devices. These applications are still in a very initial state, and this thesis aims to take these possible applications a step further. The thesis provides the results of a rubber hand illusion experiment over time and a dynamic model related to the embodiment of the rubber hand. The dynamical model can visualize the proprioceptive drift that arises from the illusion and predict the time it takes to experience it. The results of the experiment and other empirical findings from the literature form the basis of the model. The experiment measured these factors and the feeling of ownership and agency over time. The results from this experiment have much variance but are in line with the literature. The dynamical model fails to visualize the body ownership and agency results. Adding extensions and improvements could make this dynamic model more complete and applicable in many research fields.

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