Electromyography based Gesture Recognition: An Implementation of Hand Gesture Analysis Using Sensors

Author:

Khan Talha,Shaheer Ahmed ,Syed Safdar Ali Rizvi ,Sadique Ahmad ,Nitasha Khan

Abstract

Motion sign-based language has an important role in the mute community, that is for data transmission. Usually, silent and dumb people counter very difficult situations to convey information to normal people. This paper proposes research that can ease the life of the deaf community. The work presented in this paper is a communication bridge between normal-hearing persons and persons with less hearing ability or impaired persons. The proposed research ‘Gesture–Talk’ can be used as an interpreter between any normal person and deaf and mute persons. The Gesture–Talk is based on the language used in Pakistan which is Pakistan Sign Language (PSL), which is a standard language used by deaf persons in Pakistan. Using Gesture–Talk, PSL can be translated into voice. The idea is to develop a small portable application that can be used as a middle layer application between normal and deaf people. The authors have used an electrical sensor that will collect the data by detecting electrical pulses that will be sent to the microcomputer (raspberry pi 3) where the data will be processed and sent to the speaker from which voice will be generated. A cost-effective and novel approach has been proposed in this research paper compared to the other existing approaches. Moreover, Artificial Intelligence (AI) based predictive or classification algorithms may be applied for the best optimal results.  

Publisher

Sir Syed University of Engineering and Technology

Reference35 articles.

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1. Enhancing sign language recognition using CNN and SIFT: A case study on Pakistan sign language;Journal of King Saud University - Computer and Information Sciences;2024-02

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