MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641109044 A) filed by Sr University on September 11, 2026, for Quantum-Evolutionary Fuzzy Deep Learning System For Adaptive Facial Palsy Severity Assessment And Personalized Rehabilitation.
Inventors include Dr. Revathi Durgam; Dr. Kummari Venkatesh; and Dr. Shaik Abdul Nabi.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: QUANTUM-EVOLUTIONARY FUZZY DEEP LEARNING SYSTEM FOR ADAPTIVE FACIAL PALSY SEVERITY ASSESSMENT AND PERSONALIZED REHABILITATION The present invention discloses a Quantum-Evolutionary Fuzzy Deep Learning System for adaptive facial palsy severity assessment and personalized rehabilitation. The system comprises a Multi-Modal Data Acquisition Module (100) incorporating a 3D depth sensor (101), infrared thermal sensor (102), and sEMG array (103) targeting key facial muscles (103a--103e) of a patient (105). A Quantum-Evolutionary Deep Feature Extraction Engine (200) housed in a Main Computational Host (600) utilizes qubit registers (204), quantum rotation gates (201), and a quantum best memory register (205) to rapidly optimize a Spatial-Temporal Graph Convolutional Network (ST-GCN) (202) and extract feature vectors (206). A Type-2 Neuro-Fuzzy Assessment Engine (300) utilizes interval Type-2 fuzzy logic (301) with footprints of uncertainty (305), rule base (302), and defuzzification (303) to output a continuous Facial Palsy Severity Index (FPSI) (304). A Closed-Loop Controller (400) governs an adaptive NMES driver (401), game engine (402), and synkinesis interlock (403) to deliver personalized, synkinesis-inhibited rehabilitation via an interactive bio-feedback interface (500).
Disclaimer: Curated by HT Syndication.
