EEG-Based Emotion Recognition and Its Interface with Augmented Reality

Automatic detection of emotions determines the mental state of a person and makes him better understandable. The paper proposes a reliable system for emotion detection using brain signals and interfacing the data with the virtual world which gives a secured view of the information. The most notable feature of this work is the creation of a readily accessible and easy-to-use App with augmented reality and uploading the information to the App enhances portability and facilitates the user to perceive the virtual information added to the real world. Happiness and sadness are detected practically and the DEAP dataset is used for other emotions. A depressed individual can get out of his sad mental state with the aid of this system. Angry, excited, pleasant and sad emotions are classified with the aid of Support Vector Machine and respective soothing videos for each emotion are played in the virtual world.