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Characterising motor impairments in autism using computational techniques

Project Description

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: 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.

The student will join a vibrant research team in the cross-faculty Body, Eye and Movement (BEAM) lab ( There are regular opportunities to become involved in other activities such as teaching and public engagement events and the student will benefit from the interdisciplinary research network [email protected] (, chaired by Emma Gowen.

Funding Notes

This project has a Band 1 fee. Details of our different fee bands can be found on our website (View Website). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (View Website).

Informal enquiries may be made directly to the primary supervisor.


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

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