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Sign Language Glove
Author(s)
Date Issued
January 1, 2025
Type
Conference Paper
Abstract
Communication barriers for speech-impaired and hearing-impaired people persist due to the time and effort to learn different sign languages. To address this, we develop sign language gloves, allowing sign language users to communicate with others without extensive training. Our approach begins with American Sign Language (ASL), utilising open-source somatosensory gloves to capture Metacarpophalangeal (MCP) joint movements and flex sensors to detect Proximal interphalangeal (PIP) joint movements. The collected data are processed and trained using deep learning techniques to improve recognition accuracy. This system aims to enhance accessibility and facilitate interaction between sign language users and non-sign language users.
Citation
Bmeicon 2025 17th Biomedical Engineering International Conference, 2025