Literature DB >> 19848857

A comparison of photoplethysmography and ECG recording to analyse heart rate variability in healthy subjects.

G Lu1, F Yang, J A Taylor, J F Stein.   

Abstract

Measures of heart rate variability (HRV) are widely used to assess autonomic nervous system (ANS) function. The signal from which they are derived requires accurate determination of the interval between successive heartbeats; it can be recorded via electrocardiography (ECG), which is both non-invasive and widely available. However, methodological problems inherent in the recording and analysis of ECG traces have motivated a search for alternatives. Photoplethysmography (PPG) constitutes another means of determining the timing of cardiac cycles via continuous monitoring of changes in blood volume in a portion of the peripheral microvasculature. This technique measures pulse waveforms, which in some instances may prove a practical basis for HRV analysis. We investigated the feasibility of using earlobe PPG to analyse HRV by applying the same analytic process to PPG and ECG recordings made simultaneously. Comparison of 5-minute recordings demonstrated a very high degree of correlation in the temporal and frequency domains and in nonlinear dynamic analyses between HRV measures derived from PPG and ECG. Our results confirm that PPG provides accurate interpulse intervals from which HRV measures can be accurately derived in healthy subjects under ideal conditions, suggesting this technique may prove a practical alternative to ECG for HRV analysis. This finding is of particular relevance to the care of patients suffering from peripheral hyperkinesia or tremor, which make fingertip PPG recording impractical, and following clinical interventions known to introduce electrical artefacts into the electrocardiogram.

Entities:  

Mesh:

Year:  2009        PMID: 19848857     DOI: 10.3109/03091900903150998

Source DB:  PubMed          Journal:  J Med Eng Technol        ISSN: 0309-1902


  43 in total

1.  Using a Calculated Pulse Rate with an Artificial Neural Network to Detect Irregular Interbeats.

Authors:  Bih-Chyun Yeh; Wen-Piao Lin
Journal:  J Med Syst       Date:  2015-12-07       Impact factor: 4.460

2.  Effect of changes in sympathovagal balance on the accuracy of heart rate variability obtained from photoplethysmography.

Authors:  Xiang Chen; Yuan-Yuan Huang; Feng Yun; Tian-Jun Chen; Jin Li
Journal:  Exp Ther Med       Date:  2015-10-02       Impact factor: 2.447

3.  Comparison of foot finding methods for deriving instantaneous pulse rates from photoplethysmographic signals.

Authors:  Mathilde C Hemon; Justin P Phillips
Journal:  J Clin Monit Comput       Date:  2015-04-24       Impact factor: 2.502

4.  Comparison of short-term heart rate variability indexes evaluated through electrocardiographic and continuous blood pressure monitoring.

Authors:  Riccardo Pernice; Michal Javorka; Jana Krohova; Barbora Czippelova; Zuzana Turianikova; Alessandro Busacca; Luca Faes
Journal:  Med Biol Eng Comput       Date:  2019-02-07       Impact factor: 2.602

Review 5.  Heart Rate Variability: An Old Metric with New Meaning in the Era of using mHealth Technologies for Health and Exercise Training Guidance. Part One: Physiology and Methods.

Authors:  Nikhil Singh; Kegan James Moneghetti; Jeffrey Wilcox Christle; David Hadley; Daniel Plews; Victor Froelicher
Journal:  Arrhythm Electrophysiol Rev       Date:  2018-08

6.  Measurement fidelity of heart rate variability signal processing: the devil is in the details.

Authors:  Denise C Jarrin; Jennifer J McGrath; Sabrina Giovanniello; Paul Poirier; Marie Lambert
Journal:  Int J Psychophysiol       Date:  2012-07-20       Impact factor: 2.997

7.  Brain hypoactivation, autonomic nervous system dysregulation, and gonadal hormones in depression: a preliminary study.

Authors:  Laura M Holsen; Jong-Hwan Lee; Sarah B Spaeth; Lauren A Ogden; Anne Klibanski; Susan Whitfield-Gabrieli; Richard P Sloan; Jill M Goldstein
Journal:  Neurosci Lett       Date:  2012-02-25       Impact factor: 3.046

8.  Determination of heart rate variability with an electronic stethoscope.

Authors:  Haroon Kamran; Isaac Naggar; Francisca Oniyuke; Mercy Palomeque; Priya Chokshi; Louis Salciccioli; Mark Stewart; Jason M Lazar
Journal:  Clin Auton Res       Date:  2012-09-27       Impact factor: 4.435

9.  Photoplethysmography variability as an alternative approach to obtain heart rate variability information in chronic pain patient.

Authors:  Chiung-Cheng Chuang; Jing-Jhao Ye; Wan-Chun Lin; Kuan-Ting Lee; Yu-Ting Tai
Journal:  J Clin Monit Comput       Date:  2015-02-24       Impact factor: 2.502

10.  Extraction of heart rate from functional near-infrared spectroscopy in infants.

Authors:  Katherine L Perdue; Alissa Westerlund; Sarah A McCormick; Charles A Nelson
Journal:  J Biomed Opt       Date:  2014-06       Impact factor: 3.170

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