Groundbreaking research now under way in the UK could help our leading athletics coaches deliver outstanding results in the years ahead.
The SESAME (Sensing for Sport and Managed Exercise) project is developing innovative video and body sensor technologies designed to aid the training of both novice and elite athletes. The aim is to combine these technologies into a unique, integrated computer system that substantially increases the quantity and variety of data available to coaches during training sessions.
The project, which is being funded by the Engineering and Physical Sciences Research Council (EPSRC), will be described at this year's BA Festival of Science in York. SESAME has the potential to significantly improve future UK medal prospects in events such as sprinting, long jump and pole vault, for example.
"Many sports depend on correct technique to optimise athlete performance and reduce injury risk," says Dr Robert Harle of the University of Cambridge, who will deliver the presentation on 13th September. "So there's significant value in developing technologies which can assist the coaching process by providing near-instantaneous feedback on an athlete's technique during a training session itself."
The naked eye has long been the tool of choice for athletics coaches, perhaps supplemented by a single fixed video camera producing pictures of limited value. These video limitations arise because the coach has to use the camera either to provide useful close-up pictures of a running athlete but which only cover one or two strides, or to generate longer-range shots which show more strides but make it harder to see the athlete's technique in the necessary detail.
SESAME is therefore developing a leading-edge data recording and analysis system that will greatly increase the amount of useful information available to a coach. The system will produce simultaneous shots from multiple video cameras located in different positions that can autonomously track a moving athlete and then transmit pictures to the coach for near-instant, slow motion replay. This will require significant technical innovation as no video system currently available can cost-effectively deal with this amount and variety of data.
In addition, the project is developing on-body sensors that will use small, low-power electronics which exploit recent advances in wireless communications to collect data about arm angle, knee lift, body lean etc. This data will be transmitted straight to the coach and synchronised to the video streams to permit extensive data mining and analysis. Identifying the optimum means of presenting this synchronised information to the coach is a key SESAME objective.
Crucially, this new system will enable the coach to give an athlete, during the short time when they are walking back to their mark, immediate feedback and advice on improving their technique -- with no interruption to training schedules. For example, they could highlight the need for a sprinter to increase or decrease their stride length or knee lift in order to achieve maximum running speed, or for a jumper not to look down during take-off.
Achieving all the project's goals will require wide-ranging multidisciplinary expertise, from computer science and engineering to biomechanics and medical science. A consortium has been assembled to deliver the cutting-edge capabilities needed. The partners are University College London, the Royal Veterinary College, the University of Wales Institute, Cardiff as well as the University of Cambridge. Technology developed by the project is beginning to be trialled, with a view to availability within around 3 years.
"Our aim is to use technology to help coaches, not replace them," Robert Harle comments. "A key aspect of SESAME is to listen to coaches and understand their needs. Their input could help ensure that we develop technology tools which make a real impact on achievement by UK athletes in the future."
The above story is based on materials provided by Engineering and Physical Sciences Research Council. Note: Materials may be edited for content and length.
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