St. Petersburg Polytechnical University Journal. Computer Science. Telecommunication and Control Sys, 2018 Volume 11, Issue 4,Pages 151–161(Mi ntitu226)
Intellectual Systems and Technologies
Evaluation of students’ mental performance level based on eeg signal analysis
Abstract:
The article presents the results of studies on using non-invasive brain-computer interfaces (BCI) for analyzing the degree of mental fatigue of students. It is proposed to use electroencephalographic (EEG) signals, allowing to determine the potentials caused by events. A set of algorithms for preprocessing EEG signals and recognizing the evoked potential of P300 arising 300 ms after a visual stimulus is described in detail. The main focus is on the P300 wave recognition experiment from information captured by a Muse headset. Preliminary results on the accuracy of P300 wave recognition in different people using various types of classifiers are given. A methodology has been developed for using P300 to assess the students’ mental fatigue. A number of experiments have been carried out confirming the possibility of such assessment using the developed methodology.
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