This thesis covers work conducted to develop robust sensing systems which quantify the behaviour of sporting equipment in its real environment. The data collected provides understanding of how the athlete and the equipment are performing. It has allowed further analysis into specific competitive sports, improving training methods, providing equipment performance analysis and advanced equipment selection techniques. The work has focused on snowboarding and curling, both sports are conducted in a cold, harsh environment. Literature and research into previous work on these sports is presented. This thesis presents a study of the mechanical behaviour of snowboards and show how this can be used to enhance training techniques. Procedures for quantifying physical characteristics of a snowboard are examined. A custom built laboratory rig is used to test snowboards under controlled, repeatable conditions. Results from static and dynamic on-slope tests are presented, with reference to technical literature. The design and iteration of sensing arrangements for on-slope analysis capable are shown. Dynamic testing was performed using custom wireless and hard-wired acquisition systems. The data from static and dynamic testing are correlated with snowboarder performance and its application to current training techniques is discussed. Systems developed for snowboards were transferred to curling to develop an instrumental curling brush (<i>sweep ergometer</i>). The ergometer measured the forces and accelerations involved in sweeping. The results gathered are analysed to present statistical analysis, velocities and distances swept providing users with an individual sweeper profile. The data is the first of its kind in the world of curling, allowing repeatable accurate data for sweeping at Olympic standard. These results have led to improved training and selection techniques adopted by the British Curling team.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:642194 |
| Date | January 2006 |
| Creators | Buckingham, Mark-Paul |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/13257 |
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