AI-Driven Mental Health Forecasting and Solutions Using SVM

AI-Driven Mental Health Forecasting and Solutions Using SVM

K.Rajesh kumar, P. Ravindranath venkat, B. Sowmya pavani, S. Durga Manikanta, M. Gopinath Reddy

Artificial Intelligence & Machine Learning
Sasi Institute Of Technology and Engineering
Tadepalligudem, India

ABSTRACT- The identification and evaluation of stress levels through advanced tracking technologies represents an essential research domain which supports wellness improvement and performance enhancement. Deep learning algorithms in this smart system conduct behavioral and physiological indicator analysis alongside Naive Bayes which recognizes emotions through speech and text inputs to detect emotions including anger, sadness, fear, and happiness. Through transfer learning the examination system obtains better capabilities in making measurements across different domains which leads to extra accuracy. Within the system a chatbot running on an artificial neural network (ANN) detects emotional states and provides customized stress support through actionable advice that includes mindfulness training and physical activity and social interaction suggestions and professional resources and recreational activities. This system integrates stress recognition with emotional detection while offering specific guidance which gives users the power to deal in advance with their mental health requirements to maintain balanced well-being.

Keywords-Stress Detection, Mental Health, Machine Learning, Deep Learning, Transfer Learning, Chatbot, Artificial Neural Network (ANN), Stress Management