Fractal Analysis of Movement Variability in Spinal Curvature Communities

Lau Man Lung (2016)

Human posture and movement sensing have become crucial practices in health monitoring, especially with the introduction of various types of wearable technology in the recent five years. Utilising computational techniques, this research explores human movement dynamics by using a fractal and multifractal approach. The study obtains knowledge from the movement data extracted from non-invasive optical motion capture techniques and analyses the representation of physiological signals on spinal curvature movement. Design criteria have been derived for the wearable sensing devices in monitoring applications. This thesis develops a framework that investigates the small and large local scale fluctuations within physiological signals' temporal dimension along the spine. The findings contribute to the understanding of human movement and demonstrate the implication of the technical results on wearable technology design. In general, this research provides insights into how computational techniques can be used to develop wearable design applications, with considerations of both technology and interaction design aspects.