Real-Time Human Sleep Conditions Monitoring with Optical Fiber Interferometer Based on a Novel Machine Learning Method

Qing Wang, Ke Li, Xiang Wang, Jing Zhou, Changyuan Yu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Optical fiber sensor with fiber interferometer can obtain human vital signs signals more accurately and effectively. A novel machine learning model (PGSVM) is proposed to monitor sleep conditions better with the proposed optical fiber sensor.

Original languageEnglish
Title of host publication2024 22nd International Conference on Optical Communications and Networks, ICOCN 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350367652
DOIs
Publication statusPublished - Jul 2024
Event22nd International Conference on Optical Communications and Networks, ICOCN 2024 - Harbin, China
Duration: 26 Jul 202429 Jul 2024

Publication series

Name2024 22nd International Conference on Optical Communications and Networks, ICOCN 2024

Conference

Conference22nd International Conference on Optical Communications and Networks, ICOCN 2024
Country/TerritoryChina
CityHarbin
Period26/07/2429/07/24

Keywords

  • Fiber Interferometer
  • Machine Learning
  • Optical Fiber Sensor
  • PGSVM
  • Sleep Monitoring
  • Vital Signs

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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