Detecting passive fatigue with brain-computer interface in drowsy driving and stroke rehabilitation - Foong, Ruyi (2019)
A recent topic of interest for electroencephalography(EEG)-based brain-computer interface (BCI) is mental state monitoring. Mental states such as fatigue, frustration and attention have been shown to affect healthy users’ BCI performance. However, ground truth of mental states is often difficult to ascertain. Instead, surrogate measures such as ratings or reaction times have been used. Additionally, mental state monitoring has yet to be applied in the medical domain. Currently, a handful of studies have reported the mental state of fatigue in motor imagery (MI)-BCI stroke rehabilitation only via subject ratings, but not EEG data. Hence, there is a need to develop algorithms that can detect mental states despite a lack of ground truth. In particular, this thesis focuses on detecting the mental state of passive fatigue induced by monotony in healthy subjects in drowsy driving and in stroke survivors using MI-BCI stroke rehabilitation.