Finding Psychological Instability Using Machine Learning

Psychological instability is a growing concern in today's fast-paced world, impacting individuals' mental wellbeing and productivity. This project presents a Python-based web application designed to detect psychological instability through user input and provide actionable feedback. The system features three primary modules: a general information page, HR-style mental health questions, and scenario-based questions. Responses are analyzed using natural language processing and predictive machine learning model to determine whether the user may require professional intervention or treatment. To enhance accessibility, the application includes a voice input option, allowing users to answer questions without typing. The feedback, which includes recommendations or alerts, is securely sent to the user's registered mobile number. The solution operates in real-time, ensuring a seamless user experience and timely responses. Additionally, the system's modular architecture supports future enhancements, such as dynamic questionnaires and multilingual support. This project demonstrates the integration of technology and mental health awareness, offering an innovative approach to early detection and support for psychological well-being.