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Wavelength-Selective Parallel Sensing of Soft Optical Fibers for Wearable Applications

  • Haewon Jeong
  • , Tian Wang
  • , Carlo Renzo Opreni
  • , Pai Zheng
  • , Josie Hughes

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Soft optical sensors are an exciting sensing technology for capturing the deformation of soft structures as they can easily fabricated and integrated. However, one key challenge is their scalability, as each fiberrequires a sensor, and to achieve large area, or multi-fiber sensing requires many optical sensors. We propose parallelizing optical waveguides with color LEDs so that each fiber transmits a distinct wavelength, requiring only one color sensor to detect multiple fibers. By creating a localized response through patterning of the fibers, and using different light wavelengths we show how 5 parallel optical fibers can be combined, and their deformation reconstructed. We integrate our parallel sensing approach into a wearable glove to show the scalability of this approach, showing how it can be used to detect the finger angle during multi-finger piano playing.

Original languageEnglish
Pages (from-to)12381-12388
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume10
Issue number12
DOIs
Publication statusPublished - Dec 2025

Keywords

  • bending sensor
  • Optical fiber sensor
  • parallel sensing
  • soft robotics
  • wearable device

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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