In-ear EEG properties using echo state network to assess sleep quality and cognitive performance

Abstract

Sleep strongly affects physical and mental health as well as numerous aspects of cognitive performance, such as attention and memory. Moreover, a decrement of attention can lower work performance and cause critical mistakes. Therefore, it is important to measure sleep quality and wakefulness while taking into account attention states. In this thesis, in-ear EEG was used to measure brain status during sleep and cognitive tasks and to classify sleep stages and attention states. In addition, the association between sleep quality and cognitive performance was examined. This study can be used for 24/7 EEG monitoring with earphone-shaped EEG devices, which are more comfortable than conventional headset-type EEG devices.