  Evaluation of quality of experience (QoE) based on electroencephalography
(EEG) has received great attention due to its capability of real-time QoE
monitoring of users. However, it still suffers from rather low recognition
accuracy. In this paper, we propose a novel method using deep neural networks
toward improved modeling of EEG and thereby improved recognition accuracy. In
particular, we aim to model spatio-temporal characteristics relevant for QoE
analysis within learning models. The results demonstrate the effectiveness of
the proposed method.
