Literature DB >> 35704121

Dynamic Phase Extraction: Applications in Pulse Rate Variability.

Christopher H Li1, Franklin S Ly2, Kegan Woodhouse2, John Chen2, Zhuowei Cheng3, Tyler Santander4, Nirmit Ashar3, Elyes Turki5, Henry T Yang2, Michael Miller4, Linda Petzold2,3, Paul K Hansma5,6.   

Abstract

Pulse rate variability is a physiological parameter that has been extensively studied and correlated with many physical ailments. However, the phase relationship between inter-beat interval, IBI, and breathing has very rarely been studied. Develop a technique by which the phase relationship between IBI and breathing can be accurately and efficiently extracted from photoplethysmography (PPG) data. A program based on Lock-in Amplifier technology was written in Python to implement a novel technique, Dynamic Phase Extraction. It was tested using a breath pacer and a PPG sensor on 6 subjects who followed a breath pacer at varied breathing rates. The data were then analyzed using both traditional methods and the novel technique (Dynamic Phase Extraction) utilizing a breath pacer. Pulse data was extracted using a PPG sensor. Dynamic Phase Extraction (DPE) gave the magnitudes of the variation in IBI associated with breathing [Formula: see text] measured with photoplethysmography during paced breathing (with premature ventricular contractions, abnormal arrhythmias, and other artifacts edited out). [Formula: see text] correlated well with two standard measures of pulse rate variability: the Standard Deviation of the inter-beat interval (SDNN) (ρ = 0.911) and with the integrated value of the Power Spectral Density between 0.04 and 0.15 Hz (Low Frequency Power or LF Power) (ρ = 0.885). These correlations were comparable to the correlation between the SDNN and the LF Power (ρ = 0.877). In addition to the magnitude [Formula: see text], Dynamic Phase Extraction also gave the phase between the breath pacer and the changes in the inter-beat interval (IBI) due to respiratory sinus arrythmia (RSA), and correlated well with the phase extracted using a Fourier transform (ρ = 0.857). Dynamic Phase Extraction can extract both the phase between the breath pacer and the changes in IBI due to the respiratory sinus arrhythmia component of pulse rate variability ([Formula: see text], but is limited by needing a breath pacer.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Lock-in amplifier; Photoplethysmography; Pulse rate variability; Respiratory sinus arrhythmia

Mesh:

Year:  2022        PMID: 35704121     DOI: 10.1007/s10484-022-09549-z

Source DB:  PubMed          Journal:  Appl Psychophysiol Biofeedback        ISSN: 1090-0586


  25 in total

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Authors:  A ANGELONE; N A COULTER
Journal:  J Appl Physiol       Date:  1964-05       Impact factor: 3.531

2.  Pulse rate variability is not a surrogate for heart rate variability.

Authors:  I Constant; D Laude; I Murat; J L Elghozi
Journal:  Clin Sci (Lond)       Date:  1999-10       Impact factor: 6.124

3.  Depression, heart rate variability, and acute myocardial infarction.

Authors:  R M Carney; J A Blumenthal; P K Stein; L Watkins; D Catellier; L F Berkman; S M Czajkowski; C O'Connor; P H Stone; K E Freedland
Journal:  Circulation       Date:  2001-10-23       Impact factor: 29.690

4.  A Method for More Accurate Determination of Resonance Frequency of the Cardiovascular System, and Evaluation of a Program to Perform It.

Authors:  Lorrie R Fisher; Paul M Lehrer
Journal:  Appl Psychophysiol Biofeedback       Date:  2021-10-16

5.  Photoplethysmography (PPG)-determined heart rate variability (HRV) and extracellular water (ECW) in the evaluation of chronic stress and inflammation.

Authors:  George P Chrousos; Nektaria Papadopoulou-Marketou; Flora Bacopoulou; Mariantonietta Lucafò; Andrea Gallotta; Dario Boschiero
Journal:  Hormones (Athens)       Date:  2022-01-14       Impact factor: 3.419

6.  Interchangeability between heart rate and photoplethysmography variabilities during sympathetic stimulations.

Authors:  K Charlot; J Cornolo; J V Brugniaux; J P Richalet; A Pichon
Journal:  Physiol Meas       Date:  2009-10-28       Impact factor: 2.833

7.  Respiratory sinus arrhythmia is associated with efficiency of pulmonary gas exchange in healthy humans.

Authors:  Nicholas D Giardino; Robb W Glenny; Soo Borson; Leighton Chan
Journal:  Am J Physiol Heart Circ Physiol       Date:  2003-01-23       Impact factor: 4.733

8.  Anxiety Disorders are Associated with Reduced Heart Rate Variability: A Meta-Analysis.

Authors:  John A Chalmers; Daniel S Quintana; Maree J-Anne Abbott; Andrew H Kemp
Journal:  Front Psychiatry       Date:  2014-07-11       Impact factor: 4.157

9.  Speckleplethysmographic (SPG) Estimation of Heart Rate Variability During an Orthostatic Challenge.

Authors:  Cody E Dunn; Derek C Monroe; Christian Crouzet; James W Hicks; Bernard Choi
Journal:  Sci Rep       Date:  2019-10-01       Impact factor: 4.379

10.  Heart rate variability as a biomarker for autonomic nervous system response differences between children with chronic pain and healthy control children.

Authors:  Subhadra Evans; Laura C Seidman; Jennie Ci Tsao; Kirsten C Lung; Lonnie K Zeltzer; Bruce D Naliboff
Journal:  J Pain Res       Date:  2013-06-12       Impact factor: 3.133

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