An Efficient Analysis of EEG Signals to Perform Emotion Analysis

The analysis of human emotional features is a significant hurdle to surmount on the path to understanding the human mind. Human emotions are convoluted thus making its analysis even more daunting. In this paper, a meticulous and thorough analysis of EEG Brainwave Dataset: Feeling Emotions is performed in order to classify three basic sentiments experienced by people. A Machine Learning (ML) based framework is proposed to execute a multi-class classification process to identify positive, neutral and negative emotional experiences in people. The dataset is analysed in two distinct ways. The first method employs chi-square algorithm to select 500 of the best features from each sample in the dataset which are then employed in classifying multiple emotions utilizing several machine learning…