Smart Wearable Technologies for Real-Time Mental Health Monitoring: A Holistic Approach to Early Detection and Intervention

Mental health disorders, including anxiety, depression, and stress, are increasingly affecting individuals worldwide, creating a significant burden on healthcare systems and society. Early diagnosis and continuous monitoring are critical in managing these conditions effectively. However, traditional methods often fail to provide timely insights due to their reliance on periodic clinical visits and subjective self-reporting. This paper presents a novel smart wearable system designed for real-time mental health monitoring. The proposed system incorporates advanced biosensors capable of measuring physiological parameters such as heart rate variability, electrodermal activity, and skin temperature. These sensors continuously collect data, which is transmitted to a cloud-based analytics platform. Using artificial intelligence algorithms, the platform processes the data to identify stress levels, detect mood variations, and provide actionable insights.The system also features a mobile application that offers users personalized feedback, including relaxation techniques, lifestyle recommendations, and alerts when abnormal patterns are detected. Initial testing on a group of 50 participants demonstrated the system’s high accuracy, achieving 92% in stress level detection and significant user engagement.This research highlights the potential of wearable technology in addressing mental health challenges by enabling early detection, continuous monitoring, and improved accessibility to mental healthcare solutions.. Keywords: AI, biosensors, mental health, monitoring, physiological signals, smart wearables, stress.