Sign Language Gesture Recognition Using Sensory Gloves for the Deaf

Sign language users and non-signature communication is improved by using sign language using signal conversion technology, allowing visual gestures from sign language to be translated into spoken and sounds. It breaks down barriers to communication very effectively by interpreting sign language and adding emotions with highly developed gestures and facial recognition. The extended components are used in both hardware and software to generate accurate hand movements such as flex sensors, accelerometers and gloves with gyroscopes. Data processing and wireless communication are performed by the ESP32 module. All of these gestures are interpreted by algorithms for machine learning to meet with corresponding speech. This is done in an idle and anaconda environment. The machine also includes expression and detection of emotions, allowing you to understand the sounds behind the signs and make communication more powerful. Information is transmitted via text about language technology via audible language. Gloves are specifically manufactured for those who use Indian sign language and can only wear them on the other hand. This technique improves communication by changing sign language to an audible language and simultaneously adding more advanced gestures and facial expression detection.

Authors

Publication Details

Published
2025-08-07
DOI
https://doi.org/10.1109/netact65906.2025.11188093
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sign Language Gesture Recognition Using Sensory Gloves for the Deaf

S. Suresh, R Ritika, Shivani Asok, D B Sreelekshmy
Hand Gesture Recognition Systems
article

Sign Language Gesture Recognition Using Sensory Gloves for the Deaf

S. Suresh, R Ritika, Shivani Asok, D B Sreelekshmy
article en

Abstract

Sign language users and non-signature communication is improved by using sign language using signal conversion technology, allowing visual gestures from sign language to be translated into spoken and sounds. It breaks down barriers to communication very effectively by interpreting sign language and adding emotions with highly developed gestures and facial recognition. The extended components are used in both hardware and software to generate accurate hand movements such as flex sensors, accelerometers and gloves with gyroscopes. Data processing and wireless communication are performed by the ESP32 module. All of these gestures are interpreted by algorithms for machine learning to meet with corresponding speech. This is done in an idle and anaconda environment. The machine also includes expression and detection of emotions, allowing you to understand the sounds behind the signs and make communication more powerful. Information is transmitted via text about language technology via audible language. Gloves are specifically manufactured for those who use Indian sign language and can only wear them on the other hand. This technique improves communication by changing sign language to an audible language and simultaneously adding more advanced gestures and facial expression detection.

Openalex Percentile: Top 72%
Hand Gesture Recognition Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Sign Language Gesture Recognition Using Sensory Gloves for the Deaf — S. Suresh, R Ritika, et al. · (2025) | TGRS Research Map | TGRS