Abstract :

This Paper Presents A Comprehensive Investigation Into Smart Glove Technology, A Novel Wearable Sensory Device Designed For Real-time Gesture Recognition And Intuitive Human-machine Interaction. Smart Gloves Integrate Multiple Sensing Modalities Including Pressure Sensors, Inertial Measurement Units (IMUs), And Flex Sensors Embedded Within Textile Substrates. Advanced Machine Learning Algorithms, Particularly Deep Neural Networks And Convolutional Neural Networks (CNNs), Are Employed To Process Sensory Data And Recognize Complex Hand Gestures With High Accuracy. Our System Achieves 94.3% Gesture Recognition Accuracy On A Dataset Of 450 Gesture Sequences. This Paper Explores Sensor Fusion Techniques, Discusses Hardware-software Integration, And Presents Comparative Analysis With Existing Gesture Recognition Systems. Applications Range From Augmented Reality Interfaces To Assistive Technologies For Individuals With Motor Disabilities. The Proposed System Demonstrates Robust Performance In Real-time Processing Scenarios With Minimal Latency (avg 45ms). Results Indicate Significant Potential For Integration Into Consumer Wearable Devices And Industrial Applications.

Published:

02-4-2026

Issue:

Vol. 26 No. 4 (2026)

Page Nos:

174-178

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite