Abstract:
Mindfulness meditation has been recommended as a helpful practice for improving one's overall well-being, with influence that is likely to be reflected in the electrical activity in the brain. In this thesis, we address objectives related to mental state estimation using EEG signal processing with experimental data sets that include virtual reality based experiences. EEG signals are very sensitive to noise and often require rigorous preprocessing steps. The thesis first objective aims at understanding the effect of preprocessing on EEG-based mental state estimation in a virtual reality setting with biofeedback using data from a subject study conducted at the American University of Beirut. The thesis second objective aims at analyzing the variations of the spectral bands in the brain during relaxation and concentration exercises using a publicly available dataset. Our results demonstrate a significance in the mental state variations across sessions and subjects, with focus on the spatial distribution across different electrodes with on inter-subject variability under various experimental conditions.
