The global mental health crisis continues to escalate, with millions of individuals unable to access timely and effective therapeutic support due to barriers such as cost, availability, and social stigma. To address this growing concern, our project introduces an AI-enabled robotic therapist designed to provide scalable, accessible, and personalized mental health care. By integrating advanced natural language processing (NLP), emotion recognition, and machine learning techniques, the AI system can engage users in real-time therapeutic conversations, analyse emotional cues, and deliver tailored interventions based on established therapeutic frameworks such as Cognitive Behavioural Therapy (CBT) and Mindfulness-Based Cognitive Therapy (MBCT).The system is capable of learning from user interactions, continuously adapting to individual mental health needs. Our research involved a sample size of 150 participants from diverse age groups, each undergoing a 12-week evaluation period to measure the AI’s effectiveness in reducing symptoms of anxiety, depression, and stress. The results demonstrate significant improvements in participants' mental wellness, underscoring the potential of AI-powered systems to play a crucial role in the future of mental health care.
Machine Learning, Emotion Detection, Natural Language Processing(NLP)
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