A Deep Learning-Based Model for Human Non-Invasive Vital Sign Signal Monitoring with Optical Fiber Sensor

Qichang Zhang, Weimin Lyu, Qing Wang, Changyuan Yu

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

1 Citation (Scopus)

Abstract

This paper proposes a non-contact monitoring system using an optical fiber sensor and deep learning techniques for accurate vital sign measurements. The system combines a Mach-Zehnder interferometer-based monitor with LSTM networks, outperforming traditional methods and offering potential applications in medical diagnostics.

Original languageEnglish
Title of host publication2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350312614
DOIs
Publication statusPublished - Nov 2023
Event2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023 - Wuhan, China
Duration: 4 Nov 20237 Nov 2023

Publication series

Name2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

Conference

Conference2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023
Country/TerritoryChina
CityWuhan
Period4/11/237/11/23

Keywords

  • CEEMDAN
  • EEMD
  • LSTM
  • MZI
  • optical fiber sensor
  • vital signs monitoring

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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