Another strand of the ISEH's research tries to assess the benefits to elite sport of our work. It looks at novel ways in which our understanding of musculoskeletal conditions can be translated to professional sport. One such example is our collaboration with the department of computer science at UCL, to look at how data is collected, stored and analysed in this environment.
Recent advances in technology have increased the number of wearable and portable sensors capable of measuring various attributes in real time. Motion can be analysed qualitatively and quantitatively, with health-related data can being collected either on the field or in a clinical/sport setting, using minimally invasive techniques.
The increase in the quantity and quality of data poses the challenge of developing scientific approaches to transform the data into meaningful information that can affect practice in sports and also improve human performance and health. Such scientific advances have the potential to improve our approach to how we exercise, eat and maintain our health, leading to a better quality of life for the public and enhanced performance in sports.
To develop this concept we created SHARP (Sports and Health Analytics Research Partnership).
SHARP promotes a data driven approach towards sport, using data science to better characterize talent, identify performance drivers and understand the influence of physical training on personal wellbeing.
Employing machine learning techniques and ubiquitous computing, we aim to discover effective or disruptive patterns in any aspect of an elite athlete's training and to investigate ways in which these findings can be used to educate the wider population on how to approach physical activities to maximize health benefits and minimize risks.
Skills and Expertise:
• Machine learning
• Sports medicine and science
• Psychology and psychometric for sports
• Software development
• Databases for sports (SQL and NoSQL)