M. Dhana Durga, S. Santhosha Kumari, I. Navya Sri, R. Dinesh Babu, V. Mahendra Kumar, V. Sandhya | International Journal of Embedded Systems and Emerging Technologies | Vol 12, Issue 01 | ISSN: 2456-723X
Abstract
Communication is a fundamental human right, yet over 70 million individuals worldwide who are deaf or speech-impaired face daily barriers in expressing their needs in healthcare, education, workplaces, and emergencies. Sign language serves as the primary mode of communication for this population; however, it is not universally understood by the hearing community, creating a persistent and critical gap in accessibility. Existing assistive solutions such as camera-based AI translators require high computational power, stable internet connectivity, and controlled lighting conditions, making them unsuitable for portable, real-world deployment. This paper presents HandSpeak, a wearable embedded sign language translation system designed to bridge this communication divide affordably and reliably. The system integrates an Arduino Mega 2560 microcontroller, four flex sensors forming voltage-divider circuits on a glove, an SSD1306 OLED display for real-time text output, and an A7670C 4G GSM module for emergency SMS communication. The firmware, developed in Embedded C/C++ using Arduino IDE 2.x, continuously polls sensor inputs and maps gesture patterns to one of four predefined outputs: SICK, EMERGENCY, HELP, and WATER. Upon detection of the EMERGENCY gesture, the system automatically dispatches an alert SMS to five predefined contacts without requiring any internet connectivity. The entire system is fabricated at a cost of approximately INR 2,500–3,500, making it one of the most cost-effective embedded sign language translators reported in recent literature. Prototype testing validated 100% gesture recognition accuracy after per-sensor calibration, sub-150 ms display response, and reliable SMS delivery across all five emergency contacts.
Keywords - Sign Language Translation, Flex Sensors, Arduino Mega 2560, OLED Display, GSM Module, Gesture Recognition, Wearable Assistive Technology, Embedded Systems.
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How to cite this article
@article{DurgaMD2026,
author = {M. Dhana Durga and S. Santhosha Kumari and I. Navya Sri and R. Dinesh Babu and V. Mahendra Kumar and V. Sandhya},
title = {DESIGNING OF AN EMBEDDED SYSTEM FOR SIGN LANGUAGE TRANSLATION},
journal = {International Journal of Embedded Systems and Emerging Technologies},
year = {2026},
volume = {12},
number = {01},
issn = {2456-723X},
url = {https://journalspub.com/publication/ijeset/article=25732}
}