Video-based Visualization of Knee Movement in Cycling for Quantitative and Qualitative Monitoring

Abstract

In this work, we consider a video-based visualization framework for qualitative and quantitative monitoring of knee movement in cycling to promote subjective and objective analyses. Cycling has become a ubiquitous physical activity worldwide for recreation, commuting, or sport. It is a low-impact non-weight bearing activity due to body weight being carried by a bicycle. However, this does not guarantee an exercise experience free from injuries. Besides falls, the repetitive nature of cycling and monotonous loading of joints are consistently associated with overuse injuries. Among all, knee overuse remains an ill-defined injury type with anecdotal treatment approaches. Although biomedical research consider numerous factors as originators, state of the art motion capture approaches mainly consider lab-like indoor environments and quantitative data visualizations. Therefore, we define a two-part video-based framework for indoor-outdoor tracking and visualization of knee joint movement in cycling. In this paper, we briefly introduce the outline of our framework and explain the visualization component with reference to visual information-seeking mantra. We describe the preliminary studies we conducted and demonstrate it is potential to enhance athlete monitoring through simple practices. Furthermore, we formulate several future research directions which may provide suitable means to scholars for better understanding knee overuse injuries in cycling. We also consider our approach promising for enabling subjective and objective knee joint monitoring in cycling.