Affiliation:
1. Department of Information Systems, Faculty of Computing & Information Technology, King Abdulaziz University , Jeddah , 21589 , Kingdom of Saudi Arabia
2. Department of Computer Science, Faculty of Computing & Information Technology, King Abdulaziz University , Jeddah , 21589 , Saudi Arabia
Abstract
Abstract
Deaf-mute people have much potential to contribute to society. However, communication between deaf-mutes and non-deaf-mutes is a problem that isolates deaf-mutes from society and prevents them from interacting with others. In this study, an information technology intervention, intelligent gloves (IG), a prototype of a two-way communication glove, was developed to facilitate communication between deaf-mutes and non-deaf-mutes. IG consists of a pair of gloves, flex sensors, an Arduino nano, a screen with a built-in microphone, a speaker, and an SD card module. To facilitate communication from the deaf-mutes to the non-deaf-mutes, the flex sensors sense the hand gestures and connected wires, and then transmit the hand movement signals to the Arduino nano where they are translated into words and sentences. The output is displayed on a small screen attached to the gloves, and it is also issued as voice from the speakers attached to the gloves. For communication from the non-deaf-mutes to the deaf-mute, the built-in microphone in the screen senses the voice, which is then transmitted to the Arduino nano to translate it to sentences and sign language, which are displayed on the screen using a 3D avatar. A unit testing of IG has shown that it performed as expected without errors. In addition, IG was tested on ten participants, and it has been shown to be both usable and accepted by the target users.
Subject
Artificial Intelligence,Information Systems,Software
Reference21 articles.
1. World Health Organization. WHO: 1 in 4 people projected to have hearing problems by 2050; 1-Dec-2021. https://www.who.int/news/item/02-03-2021-who-1-in-4-people-projected-to-have-hearing-problems-by-2050.
2. National Association of the Deaf. Community and Culture – Frequently Asked Questions; 1-Dec-2021. https://www.nad.org/resources/american-sign-language/community-and-culture-frequently-asked-questions/.
3. Pezzino JM. Ethnography of deaf individuals: a struggle with health literacy. Rutgers University-Graduate School-Newark; 2021.
4. Mohd Jalani NN, Zamzuri ZF. iMalaySign: Malaysian sign language recognition mobile application using Convolutional Neural Network (CNN). Malaysia: Akademi Pengajian Bahasa; 2021.
5. Oudah M, Al-Naji A, Chahl J. Hand gesture recognition based on computer vision: a review of techniques. J Imaging. 2020;6(8):73.
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