MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115302 A) filed by Mohan Chinnasamy; Dr. A. Muthu Manickam; Mr. Ramesh D; Ms. D. Nathangashree; Ms. K. Janani; Dr. S. Chandru; Mr. K. S. Senthil Kumar; Dr. V. Kavitha; and Mrs. B. Sree Devi on September 25, 2026, for Machine Learning-Based Real-Time Mental Health Monitoring And Alert System Using Ecg Signal Analysis.
Inventors include Mohan Chinnasamy; Dr. A. Muthu Manickam; Mr. Ramesh D; Ms. D. Nathangashree; Ms. K. Janani; Dr. S. Chandru; Mr. K. S. Senthil Kumar; Dr. V. Kavitha; and Mrs. B. Sree Devi.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: The need for intelligent and continuous health monitoring systems has increased dramatically due to the rise in stress-related ailments and cardiovascular diseases. In this research, we offer an Internet of Things (IoT)-based stress monitoring and prediction system that uses machine learning and physiological sensors for real-time healthcare applications. In this sense, the suggested system continuously gathers physiological signals using HR and GSR sensors interfaced with an ESP8266 microprocessor. The IoT cloud receives the gathered data together with other context characteristics like age groups and seasonal elements for storage, visualisation, and remote monitoring. The gathered data is used for feature extraction and machine learning model training. Stress levels are categorised as Low, Medium, and High using machine-learning ensemble approaches such as Random Forest and XGBoost. The created framework has obtained high prediction confidence, ranging from 91.5% to 99.1%, according to experimental data. As a result, it guarantees precise and trustworthy assessment of stress levels under various environmental circumstances. A mobile application and timely alerts created for healthcare apps can be used to monitor this system in real time.
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