MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202611065230 A) filed by Geeta University on May 20, 2026, for A Cognitive Load-Adaptive Recommender System Using Pupillometry And Neuromorphic Filtering.
Inventors include Mr. Anurag Vashist; Dr. Kapil Saini; Dr. Poonam; Dr. Rekha Narang; and Mr. Pankaj Bajaj.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: A COGNITIVE LOAD-ADAPTIVE RECOMMENDER SYSTEM USING PUPILLOMETRY AND NEUROMORPHIC FILTERING Abstract of the Invention The present invention discloses a Cognitive Load-Adaptive Recommender System that dynamically optimizes recommendation outputs based on real-time user cognitive workload. The system captures physiological signals including pupil dilation, blink rate, and gaze behavior using a webcam or eye-tracking device. These signals are processed by a machine learning model to compute a Cognitive Load Index (CLI). A real-time processing architecture enables continuous monitoring and adaptation of recommendations. A neuromorphic filtering engine applies biologically inspired decision pruning to regulate recommendation quantity and complexity based on cognitive load. An adaptive interface modifies presentation in real time, while a feedback loop refines future recommendations using post-interaction behavioral signals. The invention reduces cognitive overload, improves decision-making efficiency, and enhances user satisfaction in digital recommendation environments such as e-commerce platforms.
Disclaimer: Curated by HT Syndication.
