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 publicationStudies in Health Technology and Informatics
PublisherIOS Press
Pages137-141
Number of pages5
Volume208
ISBN (Print)9781614994879
DOIs
StatePublished - 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)09269630
ISSN (Electronic)18798365

Other

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

Fingerprint

Heart Rate
Exercise
Monitoring
Physiological Stress
Neurology
Discriminant analysis
Discriminant Analysis
Nervous System
Recovery

Keywords

  • exercise
  • heart rate variability
  • Personal health systems
  • 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 Studies in Health Technology and Informatics (Vol. 208, pp. 137-141). (Studies in Health Technology and Informatics; Vol. 208). IOS Press. https://doi.org/10.3233/978-1-61499-488-6-137

Using Heart Rate Variability for Automated Identification of Exercise Exertion Levels. / Finkelstein, Joseph; Jeong, In Cheol.

Studies in Health Technology and Informatics. Vol. 208 IOS Press, 2015. p. 137-141 (Studies in Health Technology and Informatics; Vol. 208).

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

Finkelstein, J & Jeong, IC 2015, Using Heart Rate Variability for Automated Identification of Exercise Exertion Levels. in Studies in Health Technology and Informatics. vol. 208, Studies in Health Technology and Informatics, vol. 208, IOS Press, pp. 137-141, International Conference on Information Technology and Communication in Health, ITCH 2015, Victoria, Canada, 2/26/15. https://doi.org/10.3233/978-1-61499-488-6-137
Finkelstein J, Jeong IC. Using Heart Rate Variability for Automated Identification of Exercise Exertion Levels. In Studies in Health Technology and Informatics. Vol. 208. IOS Press. 2015. p. 137-141. (Studies in Health Technology and Informatics). https://doi.org/10.3233/978-1-61499-488-6-137
Finkelstein, Joseph ; Jeong, In Cheol. / Using Heart Rate Variability for Automated Identification of Exercise Exertion Levels. Studies in Health Technology and Informatics. Vol. 208 IOS Press, 2015. pp. 137-141 (Studies in Health Technology and Informatics).
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