Machine Learning Of Sports Movement Data Patterns For Injury Prevention In Cricket
Estrel Convention Center, Berlin, Germany
16:50 - 17:10
This presentation will elaborate the use of wearable sensors and supervised machine learning to capture or predict early risk indicators in cricket batting. It also discusses the importance of designing an application-specific criterion for filtration of machine learning models for sports injury prevention.
Mr. Pubudu Dias is a PhD research student in his final year of studies at Sports Technology Institute of Loughborough University, where his current research focuses on the use of inertial data and supervised machine learning to prevent injuries in cricket. He holds a bachelor's degree in textile process engineering. He also gathered 7+ years of industry experience as an innovation engineer by working for one of the leading textiles and apparel manufacturers, where he worked with global brands to develop innovative solutions.
Loughborough University is one of the top ten universities in the UK with a reputation for excellence in teaching and research, strong links with business and industry and unraveled sporting achievement. Loughborough University Sports Technology Institute is a £15M facility housing the Sports Technology Research Group, one of the world's leading research groups of its kind and the largest in the UK. The Group has established an international reputation for its work with global brands including adidas, Callaway Golf, Canterbury of New Zealand, Dunlop, Head, New Balance, Nike, Reebok, Slazenger, Spalding, Speedo and Umbro on the design, simulation, testing and manufacture of sporting goods.
Around 50 academics, research associates, technicians and PhD students carry out wide-ranging research including athletic footwear, technical apparel, protective equipment, balls, bats, clubs, rackets and fitness equipment. The track record of design-led innovation and accelerating novel concepts from initial stages through to commercialisation is unparalleled.