Paper Title
A Survey of Gesture Prioritization Methods for Physically Challenged Persons

Abstract
In social life, we meet many physically challenged individuals. Sign language patterns vary from country to country and from region to region. It is a challenging task to access these sign language gestures through common platforms like Braille. A vast number of research papers are published, and various algorithms are proposed, such as bibliometric VOS Viewer software and character-based Braille translators using Res Net, to help physically challenged individuals access information. This research explores the methods and ways of prioritization of Indian Sign Language (ISL) gestures for effective understanding and translation into Braille by leveraging machine learning. Another important method, in addition to Braille, is gesture translation into text. This is done for wider coverage and the betterment of the physically challenged community. The advantage of this research is to enhance communication between individuals effectively and reliably. Keywords – Indian Sign Language (ISL), Gesture Recognition, Gesture Translation, Machine Learning, Computer Vision, Deep Learning, Braille Translation.