Abstract
Brain serves as the body's processing of knowledge and management centre. The central nervous system directly produces ElectroEncephaloGram (EEG) physiological signals, which are strongly associated with human emotions. In the upcoming years, there will be an increase in interest for identifying emotion using brain waves by EEG (ElectroEncephaloGraphy) signals. It takes efficient and effective signal processing and feature extraction techniques for detection of emotions from human biological brain signals. Current approaches gather valuable information from a fixed number of ElectroEncephaloGraphy (EEG) channels utilizing variety of methodologies. This work analyses the different difficulties and problems associated with EEG signals for emotion identification and provides a comprehensive summary of several contemporary approaches. Pre-processing, feature extraction, and categorization are the first steps in the process of recognizing emotions from EEG signals. The main goal of this survey is to sought and enhance brain signal-based emotion detection ability by comparing all novel and adaptive channel selection technique that recognize the distinct changes in brain activities that varies between individuals and emotional states.
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