Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/7581
Title: Refining the infinity glove with custom user-defined capabilities
Authors: Omran, Wassim
Advisors: Moussa, Maria 
Keywords: Hand Gesture Recognition, Text-To-Speech Conversion, Speech-To-Text, Flex Sensors, MPU6050, ESP32S, Machine Learning.
Subjects: University of Balamand--Dissertations
Dissertations, Academic
Issue Date: 2024
Publisher: [Kalhat, Lebanon] : [University of Balamand], 2024
Abstract: 
Fostering seamless communication between verbal and sign languages is essential for our daily
interactions. Technology has significantly enhanced accessibility, particularly by streamlining
intercultural communication.
Unfortunately, despite these advancements, a notable communication barrier remains between
verbal and sign languages, even within the same culture. This gap often results in
misunderstandings and frustration. To tackle this issue, introducing an intelligent sign language
glove promises to facilitate effective communication for both parties.
The project aims to showcase the functionality of The Infinity Glove and illustrates its
effectiveness in assisting individuals with hearing/speaking challenges in communicating with
others.
Focusing on improving accessibility aims to enhance the lives of differently abled communities
and foster inclusivity.
The Infinity Glove is tailored to recognize American sign language as its primary mode of
communication. Equipped with multiple sensors, it can detect hand gestures and finger
movements and display the sign language output as a spoken letter, number, word, or sentence
on the mobile application
Description: 
Includes bibliographical references (p. 61-63)
URI: https://scholarhub.balamand.edu.lb/handle/uob/7581
Type: Thesis
Appears in Collections:UOB Theses and Projects

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