Motor function assessment using video-based motion capture and machine-learning for children with movement disorders
- Research Opportunity
- PhD students
- Department / Centre
- Royal Children’s Hospital/Murdoch Childrens Research Institute
|Dr Elyse Passmorefirstname.lastname@example.org||Personal web page|
|Dr Gareth Ballemail@example.com||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.
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
School Research Themes
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
For further information about this research, please contact a supervisor.
Department / Centre
Research NodeRoyal Children’s Hospital/Murdoch Childrens Research Institute
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