Ballistocardiography reconstruction based on optical fiber sensor using deep learning algorithm

Shuyang Chen, Fengze Tan, Weimin Lyu, Changyuan Yu

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

Abstract

Ballistocardiography (BCG) is the record of body recoils resulted from heart ejection during each cardiac cycle. To detect the detail information in the BCG signal, high sensitivity optical fiber Mach-Zehnder interferometer (MZI) is adopted to fabricate the cushion-type monitor. However, the bias point of the interferometer drifts with the environment affection, which will result in signal fading. In this paper, generative adversarial network (GAN) is proposed to solve the signal distortion problem in the BCG monitoring. The results show that GAN can reconstruct BCG signals with a good performance.

Original languageEnglish
Title of host publicationOptoelectronics and Communications Conference, OECC 2021
PublisherOSA - The Optical Society
ISBN (Electronic)9781557528209
Publication statusPublished - Jul 2021
Event26th Optoelectronics and Communications Conference, OECC 2021 - Virtual, Online, China
Duration: 3 Jul 20217 Jul 2021

Publication series

NameOptics InfoBase Conference Papers

Conference

Conference26th Optoelectronics and Communications Conference, OECC 2021
Country/TerritoryChina
CityVirtual, Online
Period3/07/217/07/21

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

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