Lightweight assistive technology: A wearable, optical-fiber gesture recognition system
Sanjay Seshan

TL;DR
This paper presents LiTe, a lightweight, wearable optical fiber-based gesture recognition system with high accuracy, aimed at assistive technology and sign language detection for the hearing impaired.
Contribution
Introduces a novel optical fiber-based gesture recognition system embedded in a wristband, demonstrating high accuracy with two different recognition approaches.
Findings
Achieved 99.8% accuracy with signature-based recognition.
Achieved 98.8% accuracy with neural network recognition.
Proves the feasibility of optical fiber sensors for gesture detection.
Abstract
The goal of this project is to create an inexpensive, lightweight, wearable assistive device that can measure hand or finger movements accurately enough to identify a range of hand gestures. One eventual application is to provide assistive technology and sign language detection for the hearing impaired. My system, called LiTe (Light-based Technology), uses optical fibers embedded into a wristband. The wrist is an optimal place for the band since the light propagation in the optical fibers is impacted even by the slight movements of the tendons in the wrist when gestures are performed. The prototype incorporates light dependent resistors to measure these light propagation changes. When creating LiTe, I considered a variety of fiber materials, light frequencies, and physical shapes to optimize the tendon movement detection so that it can be accurately correlated with different gestures. I…
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Taxonomy
TopicsHand Gesture Recognition Systems · Robot Manipulation and Learning · Soft Robotics and Applications
