Mr. S Sundeep Kumar, G. Kusuma kumari, M.Shashidhar Reddy, S.Nikhil, T.V.V.S Prasad 02 06 Mental health issues such as anxiety depression and other psychological disturbances have become a significant public health concern globally Identifying individuals at risk of these conditions early on can lead to timely interventions and improved outcomes With the rise of technology and the increasing use of smartphones and wearable devices there is an opportunity to develop an innovative system that can monitor emotional health in realtime helping to detect potential psychological disturbances before they escalate Traditionally mental health assessments relied on selfreporting and periodic checkins with mental health professionals These approaches often had limitations as individuals may not always accurately report their emotional state and there could be significant delays between assessments Additionally access to mental health services was not always readily available leading to potential delays in diagnosis and treatment Therefore the need for an innovative system for monitoring emotional health arises from the desire to overcome the limitations of traditional approaches By leveraging technology such as machine learning natural language processing we can create a continuous and unobtrusive monitoring system Such a system could gather realtime data on an individuals emotional state behavior and physiological responses Early detection of emotional disturbances can lead to timely intervention and support improving the overall mental wellbeing of individuals and reducing the burden on mental health services This innovative monitoring system has the potential to significantly improve mental health outcomes on a broader scale It offers a proactive approach to emotional wellbeing empowering individuals to take control of their mental health and providing an invaluable tool for mental health professionals in identifying and supporting those at risk of psychological disturbances Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026