MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202621093400 A) filed by Rk University on July 31, 2026, for Deep Learning-Based Mobility Assessment System For Personalized Walking Aid Design And Fall Prevention.
Inventors include Amit Lathigara; Nirav Bhatt; Paresh Tanna; Homera Durani; and Chhaya Patel.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: Abstract DEEP LEARNING-BASED MOBILITY ASSESSMENT SYSTEM FOR PERSONALIZED WALKING AID DESIGN AND FALL PREVENTION A system for personalized walking-aid design from mobility data includes a Movement Capture Arrangement, a Pose Reconstruction Network, a Biomechanical Feature Engine, a Aid Design Parameter Generator, and a Design Review Interface. The system receives movement video, body-landmark trajectories, force or pressure measurements, reach envelope, hand position, and assisted walking trials. The acquired observations are checked for quality, source association, and timing before a model-ready representation is generated. The Biomechanical Feature Engine produces an analytical result and a confidence indication. The Aid Design Parameter Generator applies a stored response criterion and determines whether to release an output, request reacquisition, or require review. The Design Review Interface provides recommended aid geometry, support characteristics, and a design review record. The system particularly performs deriving user-specific aid dimensions and support parameters from reconstructed movement and biomechanical features. An event record stores input identifiers, a processing version, the analytical result, and the delivered response to maintain traceability between acquisition, processing, and output. Fig. 1 Dated July 30, 2026 / Mungalpara Jigneshbhai Chhaganbhai IN/PA- 2640 Agent for the Applicant
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