Motor function assessment using video-based motion capture and machine-learning for children with movement disorders

Research Opportunity
PhD students
Department / Centre
Paediatrics
Location
Royal Children’s Hospital/Murdoch Childrens Research Institute
Primary Supervisor Email Number Webpage
Dr Elyse Passmore elyse.passmore@rch.org.au Personal web page
Co-supervisor Email Number Webpage
Dr Gareth Ball gareth.ball@mcri.edu.au Personal web page

Summary We are seeking an enthusiastic PhD candidate to join our multidisciplinary team of researchers and health professionals working collaboratively across MCRI and the Royal Children's Hospital (RCH) to develop remote motor function assessment options for children with movement disorders using video and machine-learning approaches.

Project Details

We are seeking an enthusiastic PhD candidate to join our multidisciplinary team of researchers and health professionals working collaboratively across MCRI and the Royal Children's Hospital (RCH) to develop remote motor function assessment options for children with movement disorders using video and machine-learning approaches. In conditions affecting development of the neuromuscular system (i.e cerebral palsy, Charcot-Marie-Tooth disease and muscular dystrophies), motor function such as walking or moving from sit-to-stand may be impaired, compounding physical disability.

Movement impairment can significantly impact an individual's ability to perform regular activities and navigate their environment. It is essential to quantitatively assess a child's motor function for earlier diagnosis, monitoring progression and to evaluate efficacy of novel therapies.

A 3D motion capture system is used in hospital-based Motion Analysis Laboratories, the gold standard for assessment of motor function. However, these services are only available in large centres and limited to those with complex movement disorders where surgery is indicated. To increase capacity and accessibility of quantitative motor function assessment we have developed methods for the automatic tracking of limb and joint position in videos using machine-learning. This project will extend the use of this technology to track and analysis movement of children during walking, sit-to-stand and upper limb motion activities. The candidate will develop machine-learning models to identify and predict severity of movement disorders in children.

This project is a collaboration of the Developmental Imaging Group MCRI and the Gait Analysis Laboratory RCH. The project would suit an individual with a science/engineering/computer science/data science or similar background with an interest in applying machine-learning models to clinical datasets.



Faculty Research Themes

Child Health

School Research Themes

Child Health in Medicine



Research Opportunities

PhD students
Students who are interested in joining this project will need to consider their elegibility as well as other requirements before contacting the supervisor of this research

Graduate Research application

Honours application

Key Contact

For further information about this research, please contact a supervisor.

Department / Centre

Paediatrics

Research Node

Royal Children’s Hospital/Murdoch Childrens Research Institute

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