Development Of A Hand Gesture Tracking Drawing System For Kids Learning Media Using Neural Network

Harun, Ghulam Ahmad Gymnastiar (2025) Development Of A Hand Gesture Tracking Drawing System For Kids Learning Media Using Neural Network. Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

This study presents the development of a Hand Movement Tracking System for Drawing, designed as an interactive learning tool for children aged 5–10 years.By leveraging an artificial neural network integrated with computer vision technology, the system accurately detects and interprets hand movements to facilitate real-time drawing on a digital interface, thereby fostering creativity and engagement in an educational environment. The system combines MediaPipe for real-time hand landmark detection, TensorFlow for motion classification, and a child- friendly interface to ensure accessibility and ease of use. Experimental evaluations demonstrate 90% motion recognition accuracy under varying lighting conditions, surpassing the initial benchmark of 85% through preprocessing optimization and model training. The system promotes the development of motor skills and cognitive engagement by facilitating intuitive motionbased interactions, eliminating the need for traditional input devices.

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