Intellectual Property India Publishes Patent Application for 'A Computer Implemented Behavioural Signal Processing System For Skill Prediction And Adaptive Digital Activities In Early Learning Environments' Filed by Lalin L Laudis

MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641043642 A) filed by Lalin L Laudis, Kanniyakumari, Tamil Nadu, on April 6, for 'a computer implemented behavioural signal processing system for skill prediction and adaptive digital activities in early learning environments.'

Inventor(s) include Lalin L Laudis; and Anne G. S. Sheaba.

The application for the patent was published on May 29, under issue no. 22/2026.

According to the abstract released by the Intellectual Property India: "The present invention relates to a computer-implemented behavioural signal processing system for automated skill inference and adaptive digital activity configuration in early learning environments. The proposed system operates through a digital interaction interface (101) that delivers structured activity modules including learning activities, experiential activities, and reinforcement activities on an interactive computing device. During execution of these activities, a behavioural signal acquisition module (1 02) captures interaction signals such as response latency, task completion time, accuracy metrics, error patterns, gesture interactions, reinforcement responses, persistence behaviour, and improvement trends. The captured behavioural signals are processed through a signal preprocessing module (103) and converted into structured multidimensional feature vectors using a feature vector generation engine (I 04 ). These behavioural feature vectors are analysed by a machine learning inference engine (105) comprising a Rigorous Adaptive Convolutional Neural Network (R-ACNN) to generate probabilistic skill inference outputs. Based on the inferred skill characteristics, an adaptive activity configuration module (I 06) dynamically modifies subsequent digital activities to improve user engagement and learning effectiveness. The system further includes longitudinal behavioural data storage (1 07) and multi-role access interfaces including a mentor interface (108) and parent interface (109) for analytical visualization and reporting. The invention enables paperless digital learning environments with behavioural analytics-driven adaptive task configuration."

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