Development of Intelligent Tools for Self-Monitoring and Self-Management of Pre-Diabetes

School of Engineering and Technology
Dr Mary Tom
Professor Andrew Taylor-Robinson


An estimated 1.7 million Australians (including undiagnosed Type 2) have diabetes, of which 85-90% are Type 2. Pre-diabetes is a condition diagnosed by testing HgBA1c. Studies have found that there are higher chances for people diagnosed with pre-diabetes to develop diabetes. However, it is also found that lifestyle modifications by changes in diet and exercise can delay or prevent the progression into diabetes. The existing challenge is to enable people to adhere to an improved lifestyle long-term. This study aims to investigate the development of an intelligent tool, to apply fuzzy evolutionary computation for diet optimisation, and create a scheduled diet aligned with activities. This will involve a selection of participants diagnosed with pre-diabetes, analysis of their current diet and exercise, and initial testing of the software application using a randomised control trial. The trial will evaluate the tool's effectiveness in enabling self-monitoring and self-management.

Information and Computing Sciences| Medical and Health Sciences
Artificial Intelligence, Fuzzy Evolutionary Computation, Diet Optimisation


This project is associated with the International Engaged Research Scholarship, which offers a 20% reduction in tuition fees for eligible international students.
Fees Scholarship

Other special notes

Funding is also provided by CQUniversity to support research higher degree student project costs, and to support national and international conference presentations. This includes:

For doctoral candidates:

  • up to $6,000 in Candidate Support Funds
  • up to $4,500 for Conference Travel Support

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