Principal Supervisor: Dr Emma Gowen
Funding available for eligible UK/EU applicants.
Autism is a life-long developmental condition that affects how a person communicates and interacts with people. In addition to these social symptoms, >70% of autistic individuals have altered motor control such as less accurate eye-hand coordination and abnormal gait patterns, causing considerable problems in daily living. Despite this impact, autistic motor control is poorly characterised: current assessment techniques lack sensitivity and do not provide quantitative data on the spatial and temporal nature of movements. This problem prevents advances in understanding the aetiology of motor impairment or whether motor characteristics could be used as a diagnostic biomarker.
Objective: To apply computational and statistical methods to motion tracking data in order to determine the nature of motor impairments in autistic individuals and whether they can be used as a diagnostic biomarker.
Methods: Children and adults with/without autism will perform a number of different actions (e.g. walking, picking up objects), while their movements are tracked by a motion sensor (e.g. Microsoft Kinect). A number of different movement and postural parameters will be extracted and computational and statistical methods (e.g. feature extraction, machine learning) will be applied to discriminate autistic and non- autistic groups.
Impact: This is the first application of computational tools to autistic motor control and we anticipate high impact cross-disciplinary publications. The project has the potential to produce a prototype tool to identify those at risk from having autism as well as detecting and classifying motor impairments. This could lead to earlier and quicker diagnosis of both autism and motor impairments and provide an objective and sensitive method to monitor therapy. Furthermore, the work will compliment current research by the supervisory team that is developing motor based therapies for autism (MIMIT funded) and can also be applied to other conditions such as Parkinson’s Disease which the team researches (ESRC funded).
- Darby J, Li B and Costen N (2014). Tracking Object Poses in the Context of Robust Body Pose Estimates. Computer Vision and Image Understanding, Vol. 127, 57-72
- Gowen E and Hamilton A (2013) Motor abilities in autism: a review using a computational approach. J Autism Dev Disord. 43(2) 323-344
- Wild KS, Poliakoff E, Jerrison A, Gowen E (2012) Goal-Directed and Goal-Less Imitation in Autism Spectrum Disorder. J Autism Dev Disord. 42(8): 1739-49
- Gowen E (2012) Imitation in autism: Why action kinematics matter. Frontiers in Integrative Neuroscience. 6, 117
- Darby J, Li B et al. (2010) Tracking Human Pose with Multiple Activity Models. Pattern Recognition, Vol.43, No.9, p3042-3058
How to Apply
This 4-year full-time studentship forms one of our PhD opportunities within the MRC Doctoral Training Partnership (MRC DTP) scheme. Funding provides full support for tuition fees, annual tax-free stipend at Research Council UK rates (currently £13, 863) and conference/travel allowance. The project is due to commence September 2015 and is open to UK/EU nationals only due to the nature of the funding.
Applicants should hold (or expect to obtain) a minimum upper-second honours degree (or equivalent) in a relevant subject area. A Masters qualification in a similar area would be an advantage.
Please direct applications in the following format to the principal Supervisor:
- Academic CV
- Official academic transcripts
- Contact details for two suitable referees
- A personal statement (750 words maximum) outlining your suitability for the study, what you hope to achieve from the PhD and your research experience to date.
Any enquiries relating to the project and/or suitability should be directed to the Principal Supervisor. The deadline for applications is 26 November 2014.
Further details on the MRC DTP scheme, shortlisting/interview process and additional PhD project opportunities can be found on our website: www.mhs.manchester.ac.uk/mrcdtp