Research and Implementation of Online Learning System Based on Electroencephalogram Emotion Computing

The lack of emotion is the bottleneck to improve the efficiency of online learning. In this paper, an online learning system based on EEG emotion computing is developed by using Python and PHP mixed programming method. The original EEG data are collected by Emotive EPOC, PSD is extracted as EEG features, and SVM classifier is used to classify emotional states. The system can analyze the emotional state of online learners in real time and accurately. It has the characteristics of humanized interface and modular algorithm. It can enhance the emotional interaction in online learning environment, and has reference significance for the development of educational application based on BCI.