Human Emotion Classification Based On the EEG Signals and Music Recommendation

This study examines the interaction between human emotions, electroencephalogram (EEG) data, and music inorder to develop a novel method to emotion identification and tailored music selection. Furthermore, music has a strong influence on emotions. making it a perfect medium for emotional control. The proposed method classifies human emotions using powerful machine learning algorithms that analyze EEG data. EEG data is obtained from subjects while they respond to various emotional stimuli. Feature extraction and selection approaches are used to discover meaningful patterns in EEG data that correspond to distinct emotions. In addition, the study includes a music recommendation system that tailors music playlists depending on observed emotional states.