Sports Body Sensor Networks (Sports-BSN)
Lead Research Organisation:
Imperial College London
Department Name: Computing
Abstract
With the rapid advances in sports technologies, athletes and sports coaches are constantly searching for improved performance assessment methods. Whilst athletic performances continue to improve, accurate training prescription and feedback is important to the consistency of the training outcome and maintaining the performance margin. To maximise the potential of UK athletes at future Olympics, Olympic Winter Games, and Paralympics, there is a pressing need to exploit the latest technical advances in sensing, materials, aerodynamics, biomechanics, and performance equipment design. In supporting the quest for gold in the London Olympics and Paralympics in 2012, UK Sports and EPSRC have identified a range of engineering and physical sciences disciplines that through the interaction with the sports community can generate innovative training solutions and sports equipment designs for gaining competitive advantage of the UK athletes. Such a synergy brings the opportunity not just to ensure success at the Games themselves, but to provide a sporting legacy that will underpin the long-term health and success of sport in this country. The purpose of this proposal is to investigate the use of miniaturised wireless Body Sensor Networks (BSN) for providing real-time feedback and in situ analysis of the biomechanical indices of the athletes during training. It is a feasibility project aimed at addressing the technical requirement of Sports-BSN hardware design, miniaturisation, packaging, as well as real-time data processing, sensor fusion, and data visualisation issues. The project brings together an interdisciplinary team from the Department of Computing at Imperial College London, UK Sport and nominated technical expertise working within the elite sport network (Dr Aki Salo, UK Athletics Speed specialist currently based at University of Bath).
People |
ORCID iD |
Guang-Zhong Yang (Principal Investigator) |
Publications
Ali R
(2012)
Detection and analysis of transitional activity in manifold space.
in IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society
Andreu-Perez J
(2015)
From Wearable Sensors to Smart Implants--Toward Pervasive and Personalized Healthcare.
in IEEE transactions on bio-medical engineering
Atallah L
(2014)
Gait asymmetry detection in older adults using a light ear-worn sensor.
in Physiological measurement
Atallah L
(2012)
Validation of an ear-worn sensor for gait monitoring using a force-plate instrumented treadmill.
in Gait & posture
Atallah L
(2011)
Sensor positioning for activity recognition using wearable accelerometers.
in IEEE transactions on biomedical circuits and systems
Atallah L
(2009)
The use of pervasive sensing for behaviour profiling - a survey
in Pervasive and Mobile Computing
ATALLAH L
(2011)
Energy Expenditure Prediction Using a Miniaturized Ear-Worn Sensor
in Medicine & Science in Sports & Exercise
Atallah L
(2009)
Real-time activity classification using ambient and wearable sensors.
in IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society
Atallah L
(2009)
Detecting Walking Gait Impairment with an Ear-worn Sensor
Description | The purpose of this project is to assess the applicability of the latest development of Body Sensor Networks (BSN) for real-time interactive analysis of the biomechanical factors in sport training and develop a prototype system that can be used for training potential UK medallists towards 2010 and 2012 Olympics. It is a feasibility project aimed at addressing the technical requirement of Sports-BSN hardware design, miniaturisation, packaging, as well as real-time data processing, sensor fusion, and data visualisation issues. The project has allowed to define and investigate detailed biomechanical sensing requirement and field deployment constraints for Sports-BSN in elite athlete training; design, miniaturisation and integration of the Sports-BSN sensor hardware platform with comprehensive reliability testing and packaging evaluation; development of data analysis, modelling, feature abstraction and visualisation software environment used for real-time feedback and long-term trend analysis. |
Exploitation Route | The project has resulted in a large programme grant on Elite Sport Performance Research in Training (ESPRIT, http://ubimon.doc.ic.ac.uk/esprit), which contributed to the training of UK athletes for the 2012 Olympic Games. This is a collaborative venture between the Department of Computing at Imperial College London and UK Sport, as well as UK Sport nominated technical expertise working within the elite sport network. |
Sectors | Digital/Communication/Information Technologies (including Software) Electronics |
URL | http://www.imperial.ac.uk/hamlyn |
Description | This project has allowed feasibility research of using BSN for sports and wellbeing, the end result has allowed the creation of a large consortium (ESPRIT) for elite sport training and performance analysis. The research results have been exploited by Imperial's spin-off company Sensixa. |
First Year Of Impact | 2009 |
Sector | Digital/Communication/Information Technologies (including Software),Leisure Activities, including Sports, Recreation and Tourism |
Impact Types | Cultural Societal |
Description | UK Sport |
Organisation | UK Sport |
Country | United Kingdom |
Sector | Public |
Start Year | 2007 |