Performance Physiology and Data Analytics in Motorsport
Theme: Personalised Performance and Team Performance
Student type: PhD – Submit an Expression of Interest
Host University: UNSW
Sports research objectives/questions: Fusing sensors on both the athlete and the (motor racing) vehicle to monitor and optimise overall performance, including:
- On track performance
- Career development performance
Wave forecasting at Olympic venues: complex system modelling
Themes: AI for holistic athlete performance and wellbeing / Personalised Performance and Team Performance
Student: Jonathan Sebban
Host University: UNSW
Sports research objectives/questions:
- Through the collection of reliable metocean data and mathematical modelling techniques, can we improve forecasting of surf conditions at Olympic venues (Tahiti, Brisbane)?
- Is the aforementioned method then able to calculate the number of wave-riding opportunities a surfer may have in a competitive heat using a short-range forecast of 30-60 minutes?
Prediction of relative hormonal environment for all common menstrual cycle ‘types’ (natural and pharmaceutically modified)
Themes: AI for holistic athlete performance and wellbeing / Personalised performance
Student type: Honours – Submit an Expression of Interest
Host Universities: QUT & UNSW
Sports research objectives/questions:
- Develop an open source predictive model for individual daily female hormonal profile based on known variants, including both endogenous (natural cycle) and exogenous (medicated cycle) cycle types.
- Develop an AI model to understand the relationship between the predicted hormonal environment and daily tracking variables: physical/psychological/emotional.
Novel 360 degree viewing widget of menstrual cycle (hormone profile vs wellbeing/recovery/performance variables)
Themes: AI for holistic athlete performance and wellbeing / Personalised performance
Student type: Honours – Submit an Expression of Interest
Host Universities: QUT & UNSW
Sports research objectives/questions: How can the cyclical nature of women’s training and wellbeing data be better visualised to enhance ongoing understanding and learning?
- Normalise female cycle data for the representation of repeated patterns.
- Develop an open source novel 360 degree visualisation tool with easy to use viewing windows for past, present and future for optimal user experience and learning of personal traits which may be hormonally influenced in response to the individual’s hormonal profile.
- By improving the visualisation of predictive modelling (what is likely to occur in the next viewing window) is it possible to both enhance the user experience and informed decision making regarding, recovery, performance and menstrual cycle management.
The use of photobiomodulation (PBM light therapy) to improve athletic performance and reduce injury
Themes: Data driven technological innovations / Personalised Performance and Team Performance
Student type: Masters – Submit an Expression of Interest
Host University: UNSW
Sports research objectives/questions: How significantly does Photobiomodulation (PBM light therapy) assist in athletic recovery, athletic performance and treatment of musculoskeletal injury? Research objectives are to validate affordable photobiomodulation therapies to:
- precondition joints/muscles to prevent injury
- precondition major muscle groups to extend athletic endurance
- reduce DOMS by accelerating cellular recovery post-exertion
- treat athletic musculoskeletal injuries