GestuLearn: Hand Tracking and Gesture Recognition Technology for Assistive Teaching in Special Education

Students with disabilities have received inadequate attention in terms of their engagement with technology. Research pertaining to this area is underdeveloped and while generic research often excludes this sector of the student population. Special education gives students with disabilities the opportunity to get quality education in line with their unique needs. As children progress through different stages, guided and comprehensive education becomes a cornerstone for maximizing their potential. Proper education equips them with the tools to navigate the challenges of abstract thinking and cultivates a well-rounded cognitive. Appropriate assistive technology has a direct impact on the well-being of children by supporting their functionality and inclusion into society, thereby increasing the opportunities for education. The project “GestuLearn” is an interactive learning system that utilizes real-time hand detection, tracking, and gesture recognition via computer vision, customized programming, and machine learning algorithms that is designed for assistive teaching to aid students with disabilities particularly the deaf, mute and with learning disabilities.

Authors

Publication Details

Published
2024-12-01
DOI
https://doi.org/10.1109/tencon61640.2024.10902904
Citations
1
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.37
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

GestuLearn: Hand Tracking and Gesture Recognition Technology for Assistive Teaching in Special Education

Adonis S. Santos, Marco A. Burdeos, Ivan Renz T. Eser
1 citations
Hand Gesture Recognition Systems
0.37
article

GestuLearn: Hand Tracking and Gesture Recognition Technology for Assistive Teaching in Special Education

Adonis S. Santos, Marco A. Burdeos, Ivan Renz T. Eser
article en
1 citations

Abstract

Students with disabilities have received inadequate attention in terms of their engagement with technology. Research pertaining to this area is underdeveloped and while generic research often excludes this sector of the student population. Special education gives students with disabilities the opportunity to get quality education in line with their unique needs. As children progress through different stages, guided and comprehensive education becomes a cornerstone for maximizing their potential. Proper education equips them with the tools to navigate the challenges of abstract thinking and cultivates a well-rounded cognitive. Appropriate assistive technology has a direct impact on the well-being of children by supporting their functionality and inclusion into society, thereby increasing the opportunities for education. The project “GestuLearn” is an interactive learning system that utilizes real-time hand detection, tracking, and gesture recognition via computer vision, customized programming, and machine learning algorithms that is designed for assistive teaching to aid students with disabilities particularly the deaf, mute and with learning disabilities.

Quality Education
Openalex Percentile: Top 34%
Hand Gesture Recognition Systems
0.37
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.