Using Heart Rate Variability for Automated Identification of Exercise Exertion Levels

Joseph Finkelstein, In Cheol Jeong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Heart rate monitoring is being used to estimate activity of autonomous nervous system by analysing heart rate variability (HRV). HRV has been recently shown to be effective means to monitor efficacy of exercise in patients with cardiovascular conditions and older adults. Whether HRV can be used to identify exercise exertion levels is unknown. There are multiple approaches to analyse HRV however it is not clear which approach is optimal in assessing cycling exercise. Previous studies demonstrated potential of analysis of short-term sequences of beat-by-beat heart rate data in a time domain for continuous monitoring of levels of physiological stress. The goal of this study was to assess the potential value of short-term HRV analysis during cycling exercise for automated identification of exercise exertion level. HRV indices were compared during rest, height of exercise exertion, and exercise recovery. Comparative analysis of HRV during cycling exercise demonstrated responsiveness of time-domain indices to different phases of an exercise program. Using discriminant analysis, canonical discriminant functions were built which correctly identified 100% of 'highest level of exertion' and 80.0% of 'rest' episodes. HRV demonstrated high potential in monitoring autonomic balance and exercise exertion during cycling exercise program.

Original languageEnglish (US)
Title of host publicationDriving Quality in Informatics
Subtitle of host publicationFulfilling the Promise
EditorsKaren Courtney, Alex Kuo, Omid Shabestari
PublisherIOS Press
Pages137-141
Number of pages5
ISBN (Electronic)9781614994879
DOIs
StatePublished - Jan 1 2015
EventInternational Conference on Information Technology and Communication in Health, ITCH 2015 - Victoria, Canada
Duration: Feb 26 2015Mar 1 2015

Publication series

NameStudies in Health Technology and Informatics
Volume208
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

OtherInternational Conference on Information Technology and Communication in Health, ITCH 2015
CountryCanada
CityVictoria
Period2/26/153/1/15

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Keywords

  • Personal health systems
  • exercise
  • heart rate variability
  • signal processing
  • telerehabilitation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Finkelstein, J., & Jeong, I. C. (2015). Using Heart Rate Variability for Automated Identification of Exercise Exertion Levels. In K. Courtney, A. Kuo, & O. Shabestari (Eds.), Driving Quality in Informatics: Fulfilling the Promise (pp. 137-141). (Studies in Health Technology and Informatics; Vol. 208). IOS Press. https://doi.org/10.3233/978-1-61499-488-6-137