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Comparison of HRV parameters derived from photoplethysmography and electrocardiography signals

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

Details

Original languageEnglish
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Pages5952-5955
Number of pages4
DOIs
StatePublished - 2015
Publication typeA4 Article in a conference publication
EventAnnual International Conference of the IEEE Engineering in Medicine and Biology Society -
Duration: 1 Jan 1900 → …

Conference

ConferenceAnnual International Conference of the IEEE Engineering in Medicine and Biology Society
Period1/01/00 → …

Abstract

Heart rate variability (HRV) has become a useful tool in analysis of cardiovascular system in both research and clinical fields. HRV has been also used in other applications such as stress level estimation in wearable devices. HRV is normally obtained from ECG as the time interval of two successive R waves. Recently PPG has been proposed as an alternative for ECG in HRV analysis to overcome some difficulties in measurement of ECG. In addition, PPG-HRV is also used in some commercial devices such as modern optical wrist-worn heart rate monitors. However, some researches have shown that PPG is not a surrogate for heart rate variability analysis. In this work, HRV analysis was applied on beat-to-beat intervals obtained from ECG and PPG in 19 healthy male subjects. Some important HRV parameters were calculated from PPG-HRV and ECG-HRV. Maximum of PPG and its second derivative were considered as two methods for obtaining the beat-to-beat signals from PPG and the results were compared with those achieved from ECG-HRV. Our results show that the smallest error happens in SDNN and SD2 with relative error of 2.46% and 2%, respectively. The most affected parameter is pNN50 with relative error of 29.89%. In addition, in our trial, using the maximum of PPG gave better results than its second derivative.

ASJC Scopus subject areas

Keywords

  • Biomedical monitoring, Electrocardiography, Heart rate variability, Interpolation, Monitoring, Photoplethysmography

Publication forum classification

Field of science, Statistics Finland

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