Revolution Of Sleep Diagnostics And Personalized Health Care Based On Digital Diagnostics And Therapeutics With Health Data Integration
Funder
National Health and Medical Research Council
Funding Amount
$500,000.00
Summary
Almost 1 billion people suffer from sleep apnoea. Unfortunately, the current diagnostic metric relates poorly to the symptoms and comorbidities of sleep apnoea merely measuring the frequency of breathing cessations. We aim to develop machine learning techniques to better estimate sleep apnoea severity. These techniques are implemented to high-end wearables developed in this project. Finally, we aim to design a digital diagnostic platform and create new standardised guidelines for sleep medicine.