MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641076527 A) filed by Meenakshi Academy Of Higher Education And Research on June 20, 2026, for A System And Method For Smart Surgical Assistance And Intraoperative Monitoring Using Artificial Intelligence.
Inventors include Dr. Saravanan P. S; Dr. Ravi R; Mohana Thiruchenduran; Vasanthapriya J; Jayabharathi B; and Subhashini K.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: CLAIMS We Claim: 1. A system (100) for smart surgical assistance and intraoperative monitoring, the system comprising: a surgical imaging acquisition module configured to acquire intraoperative imaging data; a multimodal physiological monitoring module configured to acquire physiological measurements associated with a patient; a surgeon motion intelligence module configured to acquire surgical instrument tracking information and surgeon activity data; a digital surgical generation module configured to generate and continuously update a patient-specific digital surgical based on the acquired imaging data, physiological measurements, and surgeon activity data; a tissue stress and trauma prediction module configured to predict tissue injury risks based on tissue interaction characteristics and physiological responses; a surgical complication forecasting module configured to predict one or more potential surgical complications before occurrence; an adaptive surgical strategy simulation module configured to generate and evaluate a plurality of surgical intervention pathways; a physiological-anatomical correlation engine configured to establish correlations among surgeon actions, anatomical conditions, tissue interactions, and physiological responses; and a processor operatively coupled to a memory and configured to generate adaptive intraoperative recommendations based on outputs generated by the digital surgical generation module, the tissue stress and trauma prediction module, the surgical complication forecasting module, the adaptive surgical strategy simulation module, and the physiological-anatomical correlation engine. 2. The system as claimed in claim 1, wherein the digital surgical generation module is configured to continuously update a virtual representation of anatomical structures, physiological conditions, tissue characteristics, organ functions, and procedural status throughout a surgical procedure using real-time intraoperative data. 3. The system as claimed in claim 1, wherein the tissue stress and trauma prediction module is configured to analyze tissue deformation patterns, force distributions, perfusion indicators, and physiological responses to identify potential tissue damage prior to occurrence of actual tissue injury. 4. The system as claimed in claim 1, wherein the adaptive surgical strategy simulation module is configured to generate a plurality of hypothetical intervention scenarios, predict procedural outcomes associated with each intervention scenario, and determine an optimal surgical strategy based on risk analysis and outcome prediction. 5. The system as claimed in claim 1, wherein the system further comprises a surgical knowledge graph engine configured to establish contextual relationships among surgical procedures, anatomical structures, physiological conditions, surgical complications, and intervention strategies to facilitate explainable intraoperative decision support. 6. A method for smart surgical assistance and intraoperative monitoring, the method comprising: acquiring intraoperative imaging data, physiological measurements, surgical instrument tracking information, and procedural metadata; integrating the acquired data to generate a unified intraoperative data framework; generating a patient-specific digital surgical based on the integrated data; continuously updating the digital surgical during a surgical procedure; predicting tissue trauma risks and surgical complications using the digital surgical ; simulating a plurality of surgical intervention pathways; determining an optimal intervention pathway based on predicted outcomes; and generating adaptive intraoperative recommendations for assisting a surgeon. 7. The method as claimed in claim 6, wherein generating the patient-specific digital surgical comprises constructing a dynamic virtual representation of patient anatomy, physiology, tissue characteristics, organ functions, and procedural progress using multimodal intraoperative information. 8. The method as claimed in claim 6, wherein predicting tissue trauma risks comprises analyzing tissue deformation patterns, physiological responses, tissue perfusion characteristics, and instrument interaction parameters to identify potential injury conditions before actual tissue damage occurs. 9. The method as claimed in claim 6, wherein simulating the plurality of surgical intervention pathways comprises generating multiple hypothetical surgical actions, predicting outcome probabilities associated with each surgical action, and selecting a preferred intervention pathway based on risk evaluation criteria. 10. The method as claimed in claim 6, further comprising establishing correlations among surgeon actions, instrument movements, anatomical conditions, tissue interactions, and physiological responses to generate explainable decision-support outputs and risk-prioritized alerts during the surgical procedure.
Disclaimer: Curated by HT Syndication.
