Research Aims and Objectives
The main objective of the SESAME project is to conduct high-quality scientific research to produce deployable systems that have a positive and measurable impact on the training of elite athletes. This project is application-led and multidisciplinary and has the following aims:
- To understand coaching requirements by working with coaches throughout the lifetime of the project.
- To support both athletes' and coaches' training and education through:
- capturing fine-grained data about athletes' actions and performance using wireless sensors, extensible middleware and networking platforms;
- processing these data to extract information that is meaningful to coaches, using a newly developed biomechanical model to guide this;
- identifying deviations between captured data and an idealised model of movement, supporting real-time corrective feedback;
- storing the data and information in a long-term data store and performing trend analyses;
- visualising this information in a form that is meaningful to athlete and coach.
- To explore the feasibility of correcting actions and building 'muscle memory' (the proprioceptive sense) through the use of real-time non-invasive wireless signalling.
- To compare and evaluate different athletes' actions and performance, identifying advantages and disadvantages and informing customised feedback for individuals.
- To place the UK firmly at the forefront of sporting technology.
The R&D process within the SESAME project is driven by a set of critical technical objectives. Consequently, the project activities have been structured as a set of interlinked milestones; these will be tackled by interdisciplinary interinstitutional teams, led by scientists and engineers with world-leading expertise.
In addition to domain-specific contributions, we expect to make research advances in:
- sensor system design for monitoring human activities;
- biomechanical modelling and its symbiosis with the modelling of human activity in sensor-enabled applications;
- filtering and fusion to support quality of service/reliability requirements with high-volume sensor data capture;
- engineering of interactive sensor-driven applications;
- integration of sensor monitoring data and derived guidance information within electronic health records;
- autoconfiguration for sensor systems;
Topic revision: r1 - 20 Jul 2006 - 17:27:44 - RobertHarle