MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641074236 A) filed by Kesavamoorthy R.; Manjula Subramaniam; P. Robert; and Cmr Institute Of Technology, Bengaluru on June 15, 2026, for System And Method For Ai-Based Gamified Assessment And Adaptive Diagnosis Of Autism Using Multimodal Gesture And Motion Tracking.
Inventors include Manjula Subramaniam; P. Robert; and Dr. Kesavamoorthy R..
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: The present invention discloses a system and method for AI-based gamified assessment and adaptive diagnosis of autism spectrum disorder using multimodal gesture and motion tracking. The system comprises an input module configured to capture video and motion data of a subject by means of at least one camera and optional inertial sensors; a gamified interaction engine that presents, on a display device, task-based scenarios including imitation, object-following, response and pointing tasks; an artificial intelligence processing engine configured to extract and fuse, through an attention-based fusion model, multimodal features comprising skeletal pose features, gaze direction, facial-landmark features and temporal response-latency features, thereby computing an engagement score, a motor-coordination index, a social- response score and an autism-spectrum-disorder likelihood score; an adaptive engine that modifies in real time the task type, complexity or difficulty in response to the subject's measured behavioural metrics, thereby forming a closed-loop interaction system; and a diagnostic output module that computes a developmental-age mapping and renders an explainable diagnostic report comprising an autism-spectrum-disorder likelihood score, domain-wise developmental scores, top contributing behavioural cues and follow-up recommendations. The invention enables real-time, objective, scalable, engaging and explainable assessment of autism spectrum disorder, suitable for clinical, school and home-based deployment using a standard camera-equipped computing device, and is particularly suited to low- and middle-income settings where the availability of specialist clinicians is limited.
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