Sleep neuroscience refers to the effect of sleep on the brain and nervous system in the body. Rapid scientific and technical advances have enabled reliable and affordable measurement of sleep neurophysiology. Individual variability in performance and impacts of sleep loss will reflect biological variability in sleep and circadian control systems along with a range of other lifestyle and genetic factors. A range of physiological measures based in neuroscience are needed to understand many of these mechanisms, including why some people cope with sleep loss and sleep disorders that predict poor health outcomes better than others.
Our research aims to discover and validate new neural, behavioural and biological biomarkers to help predict how an individual will respond to sleep loss or sleep disorders. We can then use these biomarkers to develop clinically deployable tools to identify people at high risk of poor cognitive and mental health outcomes and risk of alertness failure and sleep-related performance impairment on the road and at work.
These tools could provide early screening of people at higher risk of poor cognitive and mental health outcomes and prevent potentially fatal work or motor vehicle accidents caused by sleep loss or disorder.
One of the new methods being used includes tri-concentric ring electrodes (TCRE) for recording brain electrical activity from more localised areas of the brain and with much less muscle artefact than traditional electrode systems.
We are also developing new signal processing methods are also being applied to develop novel biomarkers that are more sensitive to sleep disruption compared to traditional sleep scoring methods.
Research focuses on development and validation of biomarkers to identify people’s vulnerability to sleep loss and sleep disorders. The goal of this research is to deploy biomarker screening tools to help clinicians identify people at higher risk of alertness failure and performance impairment for fitness to drive and operational environments to ultimately reduce sleepiness related accidents. This research increasingly utilises novel wearable and nearable technology to help profile people’s sleep in the home environment and how they respond to insufficient sleep or sleep disorders from a cognitive function and operational performance perspective.
Research expertise in wearables, machine learning, and Biomedical signal processing. Currently developing novel algorithms and methods for upper airway collapsibility, sleep disordered breathing, sleep apnoea, and cardiorespiratory applications. Key research activities include automated upper airway collapsibility and EMG reflex analysis for analysing sleep breathing disorder data, a novel method to extract vital sleep parameters from sleep reports and the development of "Groundtruth GUI," an open-source MATLAB tool for artifact identification/removal from various physiological signals.
Professor Danny Eckert, Director FHMRI Sleep Health, Matthew Flinders Professor
Dr Bastien Lechat,
Research Fellow
Mandy O’Grady,
Research Assistant
Kelsey Bickley,
Research Assistant
Jesse Parker,
PhD Candidate
Claire Dunbar,
PhD Candidate
We have long-term international and Australian sleep health partnerships across universities, South Australian Local Health Network and with industry groups. Please contact us to discuss opportunities.
Sturt Rd, Bedford Park
South Australia 5042
South Australia | Northern Territory
Global | Online
CRICOS Provider: 00114A TEQSA Provider ID: PRV12097 TEQSA category: Australian University
Flinders University uses cookies to ensure website functionality, personalisation and a variety of purposes as set out in its website privacy statement. This statement explains cookies and their use by Flinders.
If you consent to the use of our cookies then please click the button below:
If you do not consent to the use of all our cookies then please click the button below. Clicking this button will result in all cookies being rejected except for those that are required for essential functionality on our website.