1. Please give a summary of your research.
Sleep apnoea is a sleep related breathing disorder that involves a decrease or complete halt of airflow. It is a serious and prevalent health issue affecting quality of life associated with a high rate of mortality and morbidity. Unfortunately, 80 to 90% of the sufferers remain undiagnosed and untreated. If it remains untreated, the consequences are immense such as cardiac disorders, heart failure and physiological, psychological and financial sever costs. It is estimated that anywhere up to 15% of the population have sleep apnoea and many suffer from daytime sleepiness and fatigue which may be a symptom of disturbed sleep pattern.
Thus, it is vigorously needed to be treated. The standard treatment is CPAP (continuous positive airway pressure) which basically operates like an inverse vacuum cleaner and pumps the air into the airway to keep it open. There are other treatment options such as surgery, medication and oral appliances.
Since starting my PhD in 2014, my goal was to enhance the diagnosis and treatment for sleep disorders and increase the public awareness toward the importance of sleep disorders and their consequences on mental, cognitive and physiological health and quality of life.
At the Sleep Research Group in Charles Perkins Centre, the University of Sydney, we believe that as people are different, so are the cause, symptoms, anatomies, genetics, and clinical parameters. Thus, we need to match every individual with the best therapy and management program. The aim of our research is to personalise the therapy for sleep apnoea and provide every individual with the best treatment option. Thus, we reduce the cost and improve the treatment outcome.
2. Please include any additional details you would like to share
It will be a multidisciplinary program drawing on inputs from biomedical engineering and medicine (particularly respiratory, heart and sleep medicine).
To personalise the therapy and achieve the goals of this project
1. Our medical team conduct clinical trials of sleep monitoring in the North Shore hospital. They Collect long term data on patient’s diagnosis, clinical parameters, anatomical and physiological parameters as well as the type of treatment and the success of the treatment.
2. Then, the biomedical engineering team of our sleep research group analyse the information and look for clusters in the data i.e sub-groups of patients who did well on a treatment.
3. We will then try and predict these sub-groups using the information obtain at the time of diagnosis.
4. Finally, we design a mathematical and computerised model using modern machine learning methods such as deep learning to help match new patient with the best therapy option.
5. This will lead to a reduction in cost and an improvement the treatment outcome.
We are also collecting data from other countries around the globe (Australia, United States, Europe, and Asia) from different populations with various parameters and ethnicity. This will help to extend the analysis and improve the outcome and final system.