Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603616
Title: Development of a computer-assisted system for the analysis of canine locomotion following spinal cord injury
Author: Hamilton, L.
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2011
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Abstract:
This project aimed to develop an objective, quantitative system for assessing canine locomotion that would enable sensitive detection of changes following thoracolumbar spinal cord injury (SCI), with the eventual aim of using this to analyse the effects of an autologous olfactory ensheathing cell (OEC) transplant. Using a motion capture camera system, data analysis methods were developed which enabled objective assessment of the dog’s pelvic limb motion. Measures were developed which were independent of potential variables as size, breed and concurrent orthopaedic conditions. Locomotion was assessed immediately after incomplete SCI, and, where possible, during recovery from such an injury. Some features of locomotion were found to improve measurably and rapidly, whereas other features did not. A cohort of dogs with chronic and near-complete SCI received an autologous OEC transplant. In several animals, subtle changes in gait were detected both in the short and the long term after transplant, however no changes could be definitively attributed to the transplant. Initial information regarding the timescale and features of gait changes over time following chronic SCI was gathered. This project shows that it is possible to objectively quantify locomotor coordination in any dog, regardless of a lack of knowledge of its gait prior to injury; and that these methods are sufficiently sensitive to detect changes that may not be observed visually. Therefore, these methods may prove valuable in the analysis of the outcome of therapeutic interventions following SCI.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.603616  DOI: Not available
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