EEG and behavioural correlates of fatigue indicated by real-time monitoring of saccadic eye movements

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As a society, we are becoming increasingly sleep-deprived. Consequently, sleep restriction is having a greater impact on our day-to-day lives. One potentially life-threatening outcome is increased driver fatigue, often resulting in serious motor vehicle accidents. The main objective of the proposed research is the development of a non-invasive, ubiquitous and unobtrusive in-vehicle system to detect driver fatigue before a motor vehicle accident occurs. Our proposed system uses near infra-red (NIR) camera technology, in combination with our novel algorithm to detect somnolence, to be used to alert the driver while driving. While seemingly similar technology currently exists on the market, they rely on the duration of eyelid closures or other facial features to detect sleepiness. The major limitation of this technology is that it may detect sleepiness too late, which is crucial in order to successfully prevent motor vehicle accidents. Thus, we aim to study the relationship between saccadic eye movements and driver sleepiness, to refine our method to detect sleepiness and alert drivers before impairment and lapses in judgement occur. Here, we will study eye movements and their relationship to behavioural vigilance, brain arousal and sleep micro-states using EEG and investigate how this relates to sleep-pressure. The proposed research will help to scientifically validate this technology, foster training opportunities, mobilize knowledge to the community, and help to transfer knowledge about the dangers of drowsy driving. Ultimately, this development will result in the commercialization of an "early warning system" to prevent sleepiness-related accidents in the transport-trucking industry, public transit and in individual passenger vehicles. We expect that this research initiative will open up further avenues for research about the fitness to drive due to various causes, such as alcohol or drug use, distraction and even cognitive impairment due to dementia.