An efficient deep learning strategy for non-invasive optical fiber sensor monitoring of ECG signal reconstruction from ballistocardiogram

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

Abstract

In this paper, we established a non-invasive optical fiber sensor and a novel deep learning model for mapping BCG waveforms to ECG. Results show that the network could generate high-quality ECG signals from raw BCG.

Original languageEnglish
Title of host publication2025 23rd International Conference on Optical Communications and Networks, ICOCN 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331548759
DOIs
Publication statusPublished - Sept 2025
Event23rd International Conference on Optical Communications and Networks, ICOCN 2025 - Zhangjiajie, China
Duration: 28 Jul 202531 Jul 2025

Publication series

Name2025 23rd International Conference on Optical Communications and Networks, ICOCN 2025

Conference

Conference23rd International Conference on Optical Communications and Networks, ICOCN 2025
Country/TerritoryChina
CityZhangjiajie
Period28/07/2531/07/25

Keywords

  • ballistocardiograph
  • Cardiac vascular disease
  • deep learning
  • optical fiber sensor

ASJC Scopus subject areas

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

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