University level education is in constant evolution, making use of technological advancements in order to provide high quality pedagogical instruction to students. An important aspect of modern education is the contribution of Information Technologies,as different technological resources can be implemented to provide education under a variety of teaching modalities.
Reliable fatigue assessment is desired in many different fields and environments. An efficient fatigue evaluation tool is promising in reducing fatal errors and economic loss in industrial settings. This dataset contains electroencephalographic (EEG) signals obtainedfrom an 8-channel OpenBCI headset, as well as biometric measurements obtained from the Empatica E4 wristband. Signals obtained from the E4 include: Photopletismography (PPG), heart rate, inter-beat interval (IBI), skin temperature and Electrodermic Activity(EDA).