Annotation of seismocardiogram using gyroscopic recordings

Chenxi Yang, Sunli Tang, Negar Tavassolian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

This paper introduces a novel setup and algorithm for the automatic annotation of seismocardiographic (SCG) recordings from a MEMS accelerometer. The setup utilizes gyroscopic recordings as a reference for the detection of isovolumic moment (IM) and aortic valve closure (AC) peaks. A method for deriving the rotational kinetic energy waveform is proposed and the coefficients are generated using singular vector decomposition (SVD). Experimental results on 5 subjects at rest indicate an IM detection rate of 96.9% and AC detection rate of 95.6% without envelope filtering. It is suggested that this algorithm is feasible as an ECG-free automatic peak annotation method of SCG recordings from subjects at rest.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE Biomedical Circuits and Systems Conference, BioCAS 2016
Pages204-207
Number of pages4
ISBN (Electronic)9781509029594
DOIs
StatePublished - 2016
Event12th IEEE Biomedical Circuits and Systems Conference, BioCAS 2016 - Shanghai, China
Duration: 17 Oct 201619 Oct 2016

Publication series

NameProceedings - 2016 IEEE Biomedical Circuits and Systems Conference, BioCAS 2016

Conference

Conference12th IEEE Biomedical Circuits and Systems Conference, BioCAS 2016
Country/TerritoryChina
CityShanghai
Period17/10/1619/10/16

Keywords

  • annotation
  • digital signal processing
  • gyroscope
  • seismocardiography (SCG)
  • singular vector decomposition (SVD)

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