Intellectual Property India Publishes Patent Application for Constructive Emotional Regulation Engine For Reducing Student Exam Anxiety And Enhancing Focus.

MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641085878 A) filed by Dr. V. Nithyananthan; Prof. Dr. Malvika Kandpal; Dr. Anand Kumar; Dr Ritu Sinha; Mrs. Rakhi Chauhan; Nikita Srivastava; Dr. Priyanka Upadhyay; and Dr. Rekha Dhyani on July 13, 2026, for Constructive Emotional Regulation Engine For Reducing Student Exam Anxiety And Enhancing Focus..

Inventors include Dr. V. Nithyananthan; Prof. Dr. Malvika Kandpal; Dr. Anand Kumar; Dr Ritu Sinha; Mrs. Rakhi Chauhan; Nikita Srivastava; Dr. Priyanka Upadhyay; and Dr. Rekha Dhyani.

The application for the patent was published on July 17, 2026, under issue no. 29/2026.

Abstract: The present invention relates to a computer-implemented constructive emotional regulation engine for reducing student examination anxiety and enhancing cognitive focus. The invention comprises one or more processors, one or more memory units, a communication interface, a context acquisition module, an emotional parameter processing module, an anxiety quantification engine, a cognitive focus assessment engine, an adaptive regulation engine, an intervention recommendation module, a feedback learning module, and one or more data repositories. The context acquisition module collects contextual, behavioural, interaction-based, environmental, and physiological information associated with an examination preparation session. The emotional parameter processing module generates standardized emotional feature representations, which are processed by the anxiety quantification engine and the cognitive focus assessment engine to determine an examination anxiety index and a cognitive focus score. Based on the computed parameters and historical behavioural profiles, the adaptive regulation engine selects an optimized emotional regulation strategy and generates personalized interventions through the intervention recommendation module. The feedback learning module evaluates post- intervention behavioural responses and continuously updates behavioural profiles to refine subsequent intervention selection. The integrated computational architecture provides context-aware adaptive emotional regulation, improves intervention personalization, enhances sustained cognitive focus, reduces repetitive recommendations, and enables deployment across mobile, desktop, cloud, and institutional computing environments.

Disclaimer: Curated by HT Syndication.