DESIGN AND DEVELOPMENT OF EXAM KIT FOR CHILDREN WITH DYSGRAPHIA DISORDER
DOI:
https://doi.org/10.5281/zenodo.21373793Keywords:
Dysgraphia, Machine Learning, Raspberry Pi, Computer Vision, Assistive Technology, Handwriting RecognitionAbstract
Dysgraphia is a learning disorder that affects handwriting abilities, making it difficult for children to express ideas effectively through writing. This paper presents the design and development of an assistive exam kit aimed at helping children with dysgraphia improve writing efficiency and accuracy. The proposed system integrates hardware and software components, including Raspberry Pi, sensors, and machine learning algorithms, to provide real-time assistance. The system leverages computer vision and neural networks to detect handwriting patterns and provide corrective feedback. This approach enhances learning outcomes, improves motor skills, and boosts confidence among affected children.
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