LUMEN-Mind: An AI-Powered Social Platform for Mental Wellbeing Assessment and Depression Intervention via Multimodal Linguistic and Behavioural Analysis

Abstract

Depression continues to impact millions around the globe, yet existing tools often fail to reach and respect every community. In response, this study presents LUMEN-Mind, a cutting-edge artificial-intelligence system that gauges mental health and provides custom anti-depression support by examining everyday words and actions found online. Working with anonymised posts and usage habits in four leading languages, the platform relies on a two-part neural network that meshes state-of-the-art language models with careful tracking of how users interact over time. Thanks to a layered attention approach, LUMEN-Mind spots high-risk individuals with impressive precision, an ability proven on a benchmark of more than one million records gathered from diverse users. Once a person is flagged, the intervention engine dynamically tunes its suggestions through reinforcement learning, yielding deeper engagement and test score drops that align with clinical standards. Broad stress-testing further shows that the platform is fair, easy to explain, and carefully adopts all relevant global privacy rules. By uniting solid detection, on-the-fly guidance, and ethical, scalable design in one multilingual package, LUMEN-Mind raises the bar for the future of digital mental health careholds promising implications for applications in human-computer interaction, assistive technologies, and intelligent surveillance systems.