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
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