MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202621022925 A) filed by Rajarambapu Institute Of Technology, Walwa, Maharashtra, on Feb. 26, for 'real-time adaptive multimodal emg-based pain quantification system with personalized learning.'
Inventor(s) include Jayashree Sudhir Awati; Mahesh S. Kumbhar; and Shreyas S. Awati.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "Real-Time Adaptive Multimodal EMG-Based Pain Quantification System with Personalized Learning This invention describes a real-time adaptive multimodal electromyography-based pain quantification system configured to provide objective clinical decision support. The system acquires electromyographic signals representative of nociceptive muscular activity and synchronously integrates supplementary physiological parameters for enhanced reliability. Acquired signals undergo rectification, digital filtering, and statistical feature extraction, followed by generalized linear regression-based feature selection to isolate significant predictors of pain intensity. A Support Vector Machine classifier categorizes pain into eight discrete levels and generates a corresponding probabilistic confidence score. The system incorporates personalized baseline calibration to normalize inter-patient variability and employs a dynamic feedback-driven recalibration mechanism to adapt classification parameters over time. All computational processes are executed within an embedded edge-computing architecture to enable low-latency, bedside and intraoperative deployment without reliance on remote infrastructure. The invention provides a standardized, adaptive, and confidence-weighted physiological pain index suitable for surgical, emergency, and chronic care environments."
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