MUMBAI, India, Sept. 7 -- Intellectual Property India has published a patent application (202641104736 A) filed by Dr. Sharmila B.; Dr. Gobinda Kr. Sarkar; Dr. Priyadarshini Mishra; Dr. Karthikeyan Selvaganapathy; Dr. Roshini Rajappan; Dr. Shantanu Gupta Ot; Dr. Sai Padmaja Ch; Dr. Sai Jaya Prakash Ch; Dr. Neha Pandey; and Dr. Rupam Sarkar on August 31, 2026, for Ai-Enabled Assessment And Rehabilitation System For Post-Stroke Dysphagia.
Inventors include Dr. Sharmila B.; Dr. Gobinda Kr. Sarkar; Dr. Priyadarshini Mishra; Dr. Karthikeyan Selvaganapathy; Dr. Roshini Rajappan; Dr. Shantanu Gupta Ot; Dr. Sai Padmaja Ch; Dr. Sai Jaya Prakash Ch; Dr. Neha Pandey; and Dr. Rupam Sarkar.
The application for the patent was published on September 04, 2026, under issue no. 36/2026.
Abstract: ABSTRACT AI-ENABLED ASSESSMENT AND REHABILITATION SYSTEM FOR POST-STROKE DYSPHAGIA The present invention relates to an AI-enabled system (100) for assessment and rehabilitation of post-stroke dysphagia. The system comprises a patient assessment interface (102), swallowing-data acquisition module (104), data processing module (110), AI-assisted analysis engine (112), patient profiling module (114), personalized rehabilitation module (116), rehabilitation monitoring module (118) and comparison module (120). Patient-specific swallowing-related information is acquired and computationally processed. The AI-assisted analysis engine determines one or more swallowing-performance characteristics from the processed information, based upon which a patient-specific dysphagia profile (136) and personalized rehabilitation configuration (138) are established. Information obtained during subsequent rehabilitation sessions is compared with historical patient-specific information to determine changes in monitored parameters and generate longitudinal rehabilitation-monitoring information. A therapist interface (122) provides the generated information for professional review. The system thereby integrates dysphagia assessment, AI-assisted analysis, personalized rehabilitation and longitudinal monitoring within a unified computational architecture.
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