ESPRIT (Elite Sport Performance Research in Training)
One of the biggest challenges facing sports technology today is to understand precisely how elite athletes achieve their feats. This requires pervasive sensing, both on-body and off-body, from biomechanical to physiological, to extract continuous, unperturbed information under normal training and competition environments to recreate the winning action.
To address the needs of real-time, continuous monitoring in elite sports, as well as general healthcare applications, the ESPRIT programme (www.esprit-sport.org) supported by EPSRC (Engineering and Physical Sciences Research Council) and UK Sport, led by the Hamlyn Centre, addresses some of the key challenges related to miniaturised wearable sensors with ultra-low power, high portability, robustness, and intelligence.
The vision of ESPRIT is to position the UK at the forefront of pervasive sensing in elite sports and promote its wider application in public life-long health, wellbeing and healthcare. The project programme represents a unique synergy of leading UK research in body sensor networks (BSN), biosensor design, sports performance monitoring and equipment design.
This is to translate the ESPRIT research results from sports to healthcare and wellbeing applications. To ensure a wider uptake of the ESPRIT technolo
(G) Generalised body sensor networks
The main objective of the G-theme is to develop platform technologies for monitoring the athlete pervasively in the field during training or competitions. For this theme, there are two underlying strands of research. One is to extend and generalised the BSN platform to incorporate both wearable and ambient sensing to facilitate human dynamometric modelling, onto which we can then superimpose physiological and psychological responses. The second strand of the research is to push the current frontier of BSN to achieve ultra-low power design through the concurrent progress of ultra-low power mixed signal ASIC, power MEMS, and mapping on-node processing to mixed signal ASIC architecture.
(O) Optimised sensor design and embodiment
The aim of the O-theme is to develop innovative technologies to provide individualised, quantitative, multi-parameter assessment to modulate dynamic training regimens, with technical objectives of non-intrusive, continuous/rapid response monitoring. Minimally invasive monitoring sensors have been designed for on body measurement and deskilled in vitro assay in the case of complex targets.
(L) Learning, data modelling and performance optimisation
The L-theme focuses on the understanding of the interplay of biomechanics, exercise physiology, biochemistry and psychology. Through gathering athletes’ information in the field with pervasive technologies, it aims to establish correlations between athletic performance, biomechanical, physiological, and biochemical processes during training and competitions. This enables the development of optimised training strategies where training programmes can be designed and adjusted objectively based on the physiological or psychological responses.
(D) Device and technology innovation
The D-theme focuses on translating the new understanding of the elite athlete in themes G, O, L to guiding principles of performance optimisation through smart devices and innovative sports technologies. The D-theme aims to address the challenges in autonomic sensing, real-time feedback and adaption, enhanced reality and visualisation, individualised optimisation, customisation and technology migration and percolation. Through working closely with athletes and coaches under the ESPRIT programme, the D-theme has developed many smart technologies for sport training, such as cycling ergometers and swimming start platforms.
This is to translate the ESPRIT research results from sports to healthcare and wellbeing applications. To ensure a wider uptake of the ESPRIT technology, significant focus has also been placed on developing open platforms and ultimately standards that can facilitate seamless integration of ESPRIT hardware platforms with existing sensing platforms being used or developed in healthcare.