AI-Driven Detection of Stress, Anxiety, and Depression: Techniques, Challenges, and Future Perspectives

This research studies new methods used to detect SAD problems based on both mental and physical signals. Because mental health problems affect people worldwide traditional ways to identify these issues and diagnose them do not work for today's demands. This research evaluates AI-powered methods using several input sources including speech, facial expressions and biometric information to better screen patients and expand testing capacity. This discussion covers issues with patient data changes and ethical questions while exploring new methods including transformer processing and shared learning. These results show that AI can change how mental health is diagnosed by helping doctors catch problems sooner and deliver better results to patients.