Hand Gesture Recognition Using Glove Mounted Sensor Data

This paper presents a method to recognise fine motor hand movements and visualise them in virtual space by using a smart glove. Sensors mounted on the glove provide data to determine the position of the hands. The presented system is capable of real-time motion recognition by processing continuously incoming sensor data, making it suitable for solving complex problems such as interaction with the VR/ AR world, sign language translation or even as a training tool for physiotherapists. A microcontroller-based glove is built for the project, which monitors head and hand position as well as finger joint curvature, drawing inspiration from open source projects such as OpenGloves and LucidVR. Sensor data from the Oculus Rift VR glasses and the glove is extracted and displayed using the SteamVR extension in the Unity video game engine. The data is streamed to the gesture recognition server, which classifies the motion into one of the predefined hand motion classes. The paper demonstrates the practical utility of the smart glove through a simulated traffic management system. The user can control traffic using the glove by predefined hand movements. The virtual space is based on the U nity3D game engine and Unity VR technology.

Authors

Institutions

Publication Details

Published
2024-09-19
DOI
https://doi.org/10.1109/sisy62279.2024.10737608
Citations
2
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.74
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hand Gesture Recognition Using Glove Mounted Sensor Data

Csaba Sulyok, Dávid Varga, Ferenc Füstos, Katalin Péter et al.
2 citations
Hand Gesture Recognition Systems
0.74
article

Hand Gesture Recognition Using Glove Mounted Sensor Data

Csaba Sulyok, Dávid Varga, Ferenc Füstos, Katalin Péter, Szabolcs Hanzel, Tamás Kari
article en
2 citations

Abstract

This paper presents a method to recognise fine motor hand movements and visualise them in virtual space by using a smart glove. Sensors mounted on the glove provide data to determine the position of the hands. The presented system is capable of real-time motion recognition by processing continuously incoming sensor data, making it suitable for solving complex problems such as interaction with the VR/ AR world, sign language translation or even as a training tool for physiotherapists. A microcontroller-based glove is built for the project, which monitors head and hand position as well as finger joint curvature, drawing inspiration from open source projects such as OpenGloves and LucidVR. Sensor data from the Oculus Rift VR glasses and the glove is extracted and displayed using the SteamVR extension in the Unity video game engine. The data is streamed to the gesture recognition server, which classifies the motion into one of the predefined hand motion classes. The paper demonstrates the practical utility of the smart glove through a simulated traffic management system. The user can control traffic using the glove by predefined hand movements. The virtual space is based on the U nity3D game engine and Unity VR technology.

Babeș-Bolyai University (RO)
Affordable and clean energy
Openalex Percentile: Top 27%
Hand Gesture Recognition Systems
0.74
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.

Hand Gesture Recognition Using Glove Mounted Sensor Data — Csaba Sulyok, Dávid Varga, et al. · (2024) | TGRS Research Map | TGRS