MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641109696 A) filed by J. J College Of Engineering And Technology on September 12, 2026, for Artificial Intelligence-Enabled Digital Twin Framework For Predictive Monitoring And Personalized Treatment Of Chronic Heart Failure.
Inventors include Dr. K. Saravana Kumar; S Lakshmi Narasimhan; Dr I Shahanaz Begum; Dr S Murugesan; and Jaison Vimalraj T.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: The present invention relates to an Artificial Intelligence (AI)-enabled Digital Twin framework for predictive monitoring and personalized treatment support of patients suffering from chronic heart failure. The system creates a continuously updated virtual representation of a patient's cardiovascular condition using physiological, clinical, lifestyle, medication, and historical health data acquired from wearable sensors, medical devices, electronic health records, laboratory investigations, and patient inputs. An Internet of Medical Things (IoMT) data acquisition layer collects parameters including heart rate, blood pressure, oxygen saturation, respiratory rate, body weight, activity level, electrocardiographic characteristics, and other clinically relevant parameters. An AI analytics engine performs multimodal data fusion, anomaly detection, time-series analysis, risk prediction, and patient-specific response modelling. The Digital Twin dynamically represents the patient's physiological state and simulates potential disease trajectories and responses to different therapeutic scenarios. A predictive risk engine identifies early indications of deterioration and generates personalized treatment-support recommendations based on patient-specific characteristics, medication history, physiological response, and predicted risk. An explainable AI module provides interpretable reasons for generated predictions and recommendations. The framework further provides clinician alerts, patient monitoring dashboards, and continuous feedback-based updating of the Digital Twin, thereby enabling proactive, personalized, and data-driven chronic heart failure management.
Disclaimer: Curated by HT Syndication.
