Modelling visuomotor coordination in People with Parkinson’s Disease
Parkinson’s is a progressive neurological condition that mainly affects people of 50 and over. One person in every 500 has Parkinson’s, which equates to about 127,000 people in the UK. There’s currently no cure, and the range of symptoms and how quickly they progress are different for everyone. The main symptoms of Parkinson’s are tremor, rigidity and slowness of movement. Despite optimal medication therapy, many people with Parkinson’s (PwP) still experience gait impairments. Gait impairments (e.g., freezing of gait) are associated with falls and fear of falling, and reduced quality of life.
This studentship aims to further our understanding of the degenerative nature of the disease by taking a dynamical systems approach to modelling the coordination of locomotion (gait) from an individual perspective. While many studies have examined discrete gait measures (e.g. step length) it is likely that several gait malfunctions will interact and incur a simultaneous deterioration of stepping. A dynamical systems approach is particularly useful in predicting when and if this deterioration may cross a critical threshold; for example, triggering a freeze or a stumble.
Additionally, efficient locomotion is underpinned by a well-coordinated process that involves visual, vestibular, proprioceptive and sensorimotor feedback. It has been argued that visual information dominates such a process and that visual input is important for employing avoidance strategies, for proactive regulation to ensure stability in dynamic environments, to adjust for different surfaces in the travel path, and to plan the routes for destinations that are not visible from the start. In sum, visuospatial information makes possible preventative regulation of gait patterns that ensure effective and safe locomotion.
The first stage of this project will be to develop a model based on gait data we have already collected from 12 people with Parkinson’s. The second stage would be to collect additional data that would also consider the role of gaze in supporting accurate stepping, in order that the original model’s predictions could be refined and improved. To enhance the model’s predictions of stepping deterioration in everyday life, gaze and gait data (kinematics) will be collected from people with Parkinson’s as they walk and negotiate simulated domestic environments, to represent more closely, the movement tasks encountered in their everyday life.
Professor Mark Wilson, Sports and Health Science (University of Exeter)
Professor Krasimira Tsaneva-Atanasova, Mathematics (University of Exeter)
Dr Victoria Stiles, Sports and Health Science (University of Exeter)
Location: University of Exeter, St Luke’s Campus, Exeter
About the award:
This project is one of a number which are funded within the Carlota Palmer PhD programme. This four-year programme, run under the auspices of the Centre for Biomedical Modelling and Analysis, will commence in September 2016. The studentships will provide funding for a stipend (currently £16,165 per annum), research costs and UK/EU tuition fees for four years. Further details can be found here: http://www.exeter.ac.uk/bma/phd/
Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. Applicants with a Lower Second Class degree will be considered if they also have Master’s degree or have significant relevant non-academic experience. If English is not your first language you will need to have achieved at least 6.5 in IELTS (and no less than 6.0 in any section) by the start of the project (alternative tests may be acceptable, see http://www.exeter.ac.uk/postgraduate/apply/english/).