Context-sensitive cognitive rehabilitation aims to address the specific deficits of patients by taking into account the unique strengths and weaknesses of each brain-injured individual. However, this approach requires customized assessments and trainings that are difficult to validate, time-consuming or simply unavailable for daily clinical use. Given the currently struggling economy and an increasing number of patients with brain injuries, a feasible and efficient solution for this individualized rehabilitation concept is needed.
This dissertation addresses the development and evaluation of a VE-based training and assessment for context-sensitive cognitive rehabilitation. The proposed application is designed to closely resemble real-world places that are relevant to each individual neurological patient. Despite such an ecologically valid approach to rehabilitation, the application also integrates traditional process-specific tasks that offer potential for standardization and collection of normative data across patient populations.
Three cognitive tasks (navigation, orientation, spatial memory) have been identified for use in individualized VEs. In three experimental trials the feasibility and validity of the technological implementation and theoretical foundation of these tasks has been assessed. In a fourth trial one of the tasks has been used for the rehabilitation of a brain-injured patient. Based on the results of these studies a workflow for the rapid development of VEs has been established which allows a VR developer to provide clinicians with individualized cognitive tasks. In addition, promising results for the clinical use and validation of the proposed system form the basis for future randomized controlled clinical trials.
In conclusion, this dissertation elaborates how context-sensitive and process-specific rehabilitation approaches each offer a unique perspective on cognitive rehabilitation and how combining both through the means of VR technology may offer new opportunities to further this clinical discipline.
| Identifer | oai:union.ndltd.org:canterbury.ac.nz/oai:ir.canterbury.ac.nz:10092/6870 |
| Date | January 2012 |
| Creators | Koenig, Sebastian |
| Publisher | University of Canterbury. Human Interface Technology Lab New Zealand |
| Source Sets | University of Canterbury |
| Language | English |
| Detected Language | English |
| Type | Electronic thesis or dissertation, Text |
| Rights | Copyright Sebastian Koenig, http://library.canterbury.ac.nz/thesis/etheses_copyright.shtml |
| Relation | NZCU |
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