Fatigue Monitoring

Fatigue monitoring research aims to objectively assess and mitigate the detrimental effects of mental and physical fatigue across various sectors, from transportation to healthcare. Current efforts focus on developing robust and reliable systems using diverse data sources, including electroencephalography (EEG) signals, vocal characteristics analyzed via neural embeddings, and even facial recognition in driving contexts. These systems often employ machine learning techniques, such as multi-task learning models and support vector machines, to improve accuracy and efficiency. The ultimate goal is to improve safety, productivity, and overall well-being by providing timely detection and intervention strategies for fatigue-related risks.