Sign Language Recognition System using Flex Sensor Network

Abstract

This journal work on sign language recognition system using flex sensor network aims to x-ray the implementation of a sign language recognition system using smart gloves, raspberry pi, python and C language. Therefore, research into sign language interpretation using gestures has been explored progressively during recent decades to serve as an auxiliary tool for deaf and mute people to blend into society without barriers. In this work, a smart sign language interpretation system using a wearable hand device. This wearable system utilizes five flex-sensors, then using a PIC microcontroller, raspberry pi, python and C language to create a real-time Sign Language Recognition system. In this journal work, a sensor-based sign language recognition can serve as a key for overcoming many difficulties and providing convenience for human life. The ability of machines to understand human activities and their meaning can be utilized in a vast array of applications. This work provides a thorough technique in recent hand gesture and sign language recognition. After implementation, the system was able to output up to thirty-one phrases successfully. This paper was focused on improving the accuracy and usability of the system by optimizing the sensor placement and developing a user-friendly interface.