MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202621064975 A) filed by Mrs. Nita Jayesh Mahale; Dr. Tushar Ram Sangole; Dr. Santosh Borde; and Dr. Prashant Kumbharkar on May 22, 2026, for Ai-Based Real-Time Yoga Pose Detection And Correction System.
Inventors include Mrs. Nita Jayesh Mahale; Dr. Tushar Ram Sangole; Dr. Santosh Borde; and Dr. Prashant Kumbharkar.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: The present invention relates to a system and method for the detection, classification, and real-time correction of yoga postures using artificial intelligence. The disclosed system captures skeletal data from a practitioner through a camera or depth sensor, extracts anatomical keypoints using a trained pose estimation model, and compares the identified posture against a curated reference library of clinically validated yoga poses. When deviations beyond a defined angular threshold are detected, the system generates corrective guidance through auditory, visual, or haptic feedback channels, without requiring the physical presence of a trained instructor. The invention further incorporates a personalisation engine that adapts recommended yoga sequences according to a user's physiological profile, including age, mobility constraints, prior injuries, and health objectives such as cardiovascular rehabilitation, anxiety reduction, or musculoskeletal recovery. A secure cloud-based analytics module stores longitudinal session data and applies machine learning models to track practitioner progress, identify recurring alignment errors, and forecast therapeutic outcomes. The system is deployable across consumer-grade devices including smartphones, tablets, and smart mirrors, and is designed to operate without continuous network connectivity, thereby extending its reach to underserved and remote populations. The claimed invention addresses a documented gap in current digital wellness technology: the absence of a clinically informed, fully automated system capable of simultaneously detecting yoga posture accuracy and delivering evidence-based therapeutic guidance in real time. The system holds particular utility in chronic disease management settings, where supervised physical therapy is cost-prohibitive or geographically inaccessible. FIG 01.
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