MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641079383 A) filed by Dr. Preethi Inampudi; Bhujangarao Patcha; Prof. Mini K. Abraham; Rinku Modoor; Dr. Shruthi C; Gokul C; Smita Kallur; Dr. P. Chakradhar; and Dr Prasanna Byahatti on June 27, 2026, for An Intelligent Privacy-Preserving Multimodal Workplace Health Monitoring System And Method For Early Burnout Prediction And Adaptive Intervention.
Inventors include Dr. Preethi Inampudi; Prof. Mini K. Abraham; Rinku Modoor; Dr. Shruthi C; Gokul C; Smita Kallur; Dr. P. Chakradhar; Dr Prasanna Byahatti; and Dr Patcha Bhujanga Rao.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The present invention relates to an AI-based, privacy-preserving multimodal workplace health monitoring system and method. The system comprises a distributed architecture employing edge computing to process behavioral metadata locally on employee-side devices. Multimodal inputs, including keystroke dynamics, linguistic patterns, and physiological indicators, are processed through an edge AI module to extract privacy-masked features. A federated learning framework enables the collaborative training of a global burnout prediction model across multiple edge nodes without the exchange of raw behavioral data. An adaptive intervention engine triggers context-aware, personalized health recommendations based on model outputs, while an explainable AI module provides transparency into prediction factors. The system provides a scalable solution for early burnout detection in high-stress work environments, ensuring data sovereignty, minimizing bandwidth overhead, and facilitating non-intrusive, proactive mental health support for employees across diverse industrial sectors.
Disclaimer: Curated by HT Syndication.
