MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641049266 A) filed by Sona College Of Technology, Salem, Tamil Nadu, on April 17, for 'integrated quantum-classical system for real-time biomechanical tongue motion analysis.'
Inventor(s) include Pournima S; and Sindhudaranya B.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "The present invention is a novel hybrid quantum-classical deep learning framework designed to address these limitations by integrating quantum neural networks (QNNs) with conventional deep learning architectures. By leveraging quantum feature mapping, variational quantum circuits, and hybrid optimization strategies, the proposed model effectively reduces the dimensionality of tongue motion data while preserving essential biomechanical and neurophysiological characteristics. The quantum enhanced feature representation enables the system to learn complex motion patterns more efficiently, leading to improved classification accuracy and enhanced robustness against noise and data variability. Experimental evaluations are conducted on a benchmark dataset of tongue motion signals, comparing the hybrid quantum-classical approach with traditional deep learning methods. The results demonstrate superior classification accuracy, faster convergence rates, and enhanced computational efficiency in the quantum-assisted model. Moreover, the hybrid approach exhibits greater resilience to overfitting, making it a promising solution for real world biomedical signal processing applications."
Disclaimer: Curated by HT Syndication.
