Date of Publication :25th February 2025

Abstract: The prevalence of hearing impairment poses significant challenges to effective communication and social integration between hearing and hearing impaired people in the world. The use of assistive smart glove helps impaired people to interact effectively with others. This research work design and implement an assistive smart glove device to recognize Alphabetsof American Sign language. The designed system incorporates an ESP32-S microcontroller, accelerometer with flex sensors to detect user hand gestures. The flex sensors were used to detect the degree of bending in the fingers, while the accelerometer measures the orientation of the hand. The data collected through the flex sensors and accelerometer, are then processed using ESP32-S to obtain digital signals. The signals obtained from correct gestures signed by experts are set as predefined rules to classify specific gestures. Subsequently, translating the recognize gesture into text through a mobile application via WiFi module and later converted into voice output. This prototype has been tested for its feasibility in converting American Sign Language Alphabets (A-Z) into text and voice output. The system provides a real-time translation of alphabet gestures and achieves an average recognition accuracy of 91.20%. The system has high accuracy, adaptability, and efficiency make it a valuable contribution to the field of human-computer interaction.

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