Neuro Bio Mood: AI-Driven Emotion Analysis from Biometric Cues

This project is about “Emotion Detection using Human Biometric Inputs through Machine Learning†which aims in human emotion classification or recognition using various human biometric and physiological signals. Combination of deep learning and traditional machine learning techniques to extract feature for emotion classification, which helps to improve overall recognition accuracy. Deep learning models are used to decode facial expressions, voice intonations, and natural language semantics and machine learning algorithms assist with accurate classification of emotional signals. It, therefore, creates a more wholesome understanding of human emotion, making the whole system more adaptable and reliable in nature. Applications could include health care (monitoring emotional response), human-computer interaction (designing systems that respond more appropriately to emotional state), and possibly security (detecting stress or suspicion) VizaEmotion thus serves to posses the foundations of more precise, intelligent, integrating a heuristic and emotional approach to technological solutions.