Gait analysis – i.e. the analysis of how a human subject walks or runs forms part of a continuing research topic within the Smart Environments Research Group. Gait data can be gathered via accelerometers and can be used as a diagnostic of patient health. Recent research suggests that using data analysis techniques from an area of applied mathematics known as nonlinear analysis may help to reveal subtle features of gait which are not found by other methods. In this research project the PhD student will gather new gait data, and investigate existing data, using techniques from nonlinear analysis to find new ways to classify patient medial conditions and help with more accurate diagnosis.
First Supervisor: Zheng, H Dr
Second Supervisor: McCartney, M Dr
Collaboration: This project does not involve collaboration with another establishment