Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.572416
Title: Optimising visuo-locomotor interactions in a motion-capture virtual reality rehabilitation system
Author: Gilbert, Mathew Alan
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2013
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Abstract:
This thesis presents the research-driven design and development of Stromohab: A motion-capture virtual-reality locomotion simulator for the research and rehabilitation of gait disorders following stroke. Software and hardware components are designed, developed and tested to facilitate and motivate patients in rehabilitative interactive avatar-based locomotor tasks. The system is then used to investigate systematically on healthy volunteers the known problem of distance underestimation in virtual environments by testing and analysing all combinations of cross-planar translation of leg movement to avatar actuated movement in a virtual environment. Specific performance deficits in the sagittal plane are confirmed and compared to those from coronal and transverse motion. Potential improvements of adding in isolation monocular cues for perspective, illumination, or size, and binocular cues from 3D stereo anaglyphs, are investigated, leading to a proposed movement model and scaling solution that both explains and resolves the observed deficit empirically in a practical locomotor task. Overall, the findings demonstrate the importance for the design and application of virtual environment interfaces of quantifying the underlying mechanisms in order to ensure accurate and controlled reproduction of a user’s movement. These would be of particular significance in medical rehabilitation for neurological patients, for whom consideration of cognitive load and the potential for improper re-adaptation when returning to real world environments can be critical. It is envisaged that this study will be useful to technologists, clinicians and other professionals who apply the rapidly developing, increasingly accessible and beneficial motion capture and virtual reality technologies to medicine and related applications.
Supervisor: Pelah, Adar Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.572416  DOI: Not available
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