MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202621044165 A) filed by Deshmukh Vishwesh; Talathi Nupur Suhas; Tagare Pruthviraj Pandharinath; Kulkarni Swarnima Abhay; and Swami Kedar Chidanand on April 07, 2026, for Integrated Multi-Modal Ai-Based Health Monitoring And Predictive Cardiac Risk Assessment System Using Hybrid Sensor And Deep Learning Framework.
Inventors include Deshmukh Vishwesh; Talathi Nupur Suhas; Tagare Pruthviraj Pandharinath; Kulkarni Swarnima Abhay; and Swami Kedar Chidanand.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: The present invention relates to a hardware-integrated system and method for personalized cardiovascular risk prediction using adaptive baseline modeling and multi- parameter sensor fusion. The system continuously acquires physiological data including heart rate, blood oxygen saturation (SpO2), temperature, and electrocardiogram (ECG) signals through one or more sensors. A personalized physiological baseline is generated for each user and dynamically updated using real-time and historical data. The invention employs a composite deviation scoring mechanism to evaluate variations between real-time signals and corresponding baselines, incorporating temporal trends and interdependencies among multiple parameters. A sensor reliability weighting mechanism assigns dynamic importance to each signal based on quality and consistency. Further, the system includes context-aware baseline segmentation and a hybrid analysis module combining machine learning and deep learning techniques. A fusion module generates a unified cardiovascular risk prediction along with a confidence score. The system enables early detection of potential risks prior to exceeding predefined thresholds, thereby improving accuracy and reliability in health monitoring
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