Clinical gait analysis in special populations

Clinical gait analysis is a widely recognised method for quantifying dynamic movement problems during walking. Our clinical and research experience with gait analysis in cerebral palsy and more recently osteoarthritis opens up the possibility of PhD studentships in a number of areas building on our clinical collaborations with Alder Hey Children’s Hospital and the National Alkaptonuria Centre.

A specific line of investigation is the effect of manipulated real time visual biofeedback on a patient’s asymmetrical gait. Movement function can be enhanced by using a mirror box which provides a visual representation of the less affected moving limb in place of the more affected limb. In addition to its original use to reduce phantom limb pain in amputees (Ramachandran and Rogers-Ramachandran, 1995), the latest research (Feltham et al., 2010) found evidence that exposure to the mirror box can improve the motor control of children with cerebral palsy.
Our virtual reality based implementation, the Virtual Mirror Box, replicates and excels the functions of a physical mirror. It provides three-dimensional computer-generated imagery driven by motion capture cameras and implements a time delay which enables mirroring of the limbs during walking (Barton et al., 2014).
The studentship involves contributing to the development of an easy-to-use and fully portable virtual mirror box application using our Xsens Awinda motion capture system combined with high quality visualization software. Once operational, the new method will be evaluated in collaboration with Alder Hey Children’s Hospital paving the way to implementation in clinical practice.

Alkaptonuria is an ultra-rare genetic disease which leads to early osteoarthritis. A drug trial is currently under way which makes this rare condition an excellent opportunity to learn more about osteoarthritis on a large scale. The National Alkaptonuria Centre in Liverpool is now the international hub of all registered patients in the world who come to Liverpool regularly for a series of assessments.
One of the tests is clinical gait analysis and so there is room to develop a research question which will lead to a unique research programme embedded in an applied and clinical context. Our track record with artificial neural networks used to evaluate complex gait problems is one of the possible advanced methods which can be applied to quantify deviation from normality (Barton et al., 2012; Barton et al., 2013).