Emotion Classification from EEG derived features Mental health monitoring is crucial for early intervention and prevention of psychological distress. Leveraging EEG brainwave data, this project aims to develop a real-time emotion prediction system for enhanced mental health support.A commercial MUSE EEG headband is used with a resolution of four (TP9, AF7, AF8, TP10) electrodes. Positive and negative emotional states are invoked using film clips with an obvious valence, and neutral resting data is also recorded with no stimuli involved, all for one minute per session.
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Emotion Classification from EEG derived features
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