Literature DB >> 23348575

Evaluation of pulse rate variability obtained by the pulse onsets of the photoplethysmographic signal.

H F Posada-Quintero1, D Delisle-Rodríguez, M B Cuadra-Sanz, R R Fernández de la Vara-Prieto.   

Abstract

This work presents the evaluation of pulse rate variability (PRV) obtained from pulse onsets of photoplethysmographic (PPG) signals. Three published algorithms were used to determine the pulse onsets: diastolic point, maximum second derivative and tangent intersection. Temporal series of pulse onsets were obtained for each method, and several variability indices were derived from these series. Simultaneous ECG and PPG records were acquired from 37 healthy volunteers to evaluate the interchangeability between PRV indices and heart rate variability (HRV) indices by the Bland-Altman method. Furthermore, the concordance correlation coefficient was used to correlate the indices. In all the cases, PRV indices obtained through the tangent intersection method showed better accuracy and precision (Bland-Altman analysis, bias ± 1.96 standard deviation: low frequency, LF(ms)(2) = -28.06 ± 72.68; high frequency, HF(ms)(2) = -68.23 ± 192.85; high frequency in normalized units, HF(nu) =-2.02 ± 7.08; LF/HF = 0.17 ± 0.71) and higher correlation (concordance correlation coefficients: low frequency, LF(ms)(2) = 0.99; high frequency, HF(ms)(2) = 0.98; high frequency in normalized units, HF(nu) = 0.97; LF/HF = 0.90) with HRV indices than other methods, and could be used as a good surrogate of HRV.

Mesh:

Year:  2013        PMID: 23348575     DOI: 10.1088/0967-3334/34/2/179

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  9 in total

1.  Accurate measurement of the pulse wave delay with imaging photoplethysmography.

Authors:  Alexei A Kamshilin; Igor S Sidorov; Laura Babayan; Maxim A Volynsky; Rashid Giniatullin; Oleg V Mamontov
Journal:  Biomed Opt Express       Date:  2016-11-16       Impact factor: 3.732

2.  Validation of pulse rate variability as a surrogate for heart rate variability in chronically instrumented rabbits.

Authors:  Peter R Pellegrino; Alicia M Schiller; Irving H Zucker
Journal:  Am J Physiol Heart Circ Physiol       Date:  2014-05-02       Impact factor: 4.733

3.  Wearable Photoplethysmography for Cardiovascular Monitoring.

Authors:  Peter H Charlton; Panicos A Kyriaco; Jonathan Mant; Vaidotas Marozas; Phil Chowienczyk; Jordi Alastruey
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2022-03-11       Impact factor: 10.961

4.  Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients.

Authors:  Elisa Mejía-Mejía; James M May; Mohamed Elgendi; Panayiotis A Kyriacou
Journal:  NPJ Digit Med       Date:  2021-05-14

5.  Extraction of heart rate variability from smartphone photoplethysmograms.

Authors:  Rong-Chao Peng; Xiao-Lin Zhou; Wan-Hua Lin; Yuan-Ting Zhang
Journal:  Comput Math Methods Med       Date:  2015-01-12       Impact factor: 2.238

6.  Mild Dehydration Identification Using Machine Learning to Assess Autonomic Responses to Cognitive Stress.

Authors:  Hugo F Posada-Quintero; Natasa Reljin; Aurelie Moutran; Dimitrios Georgopalis; Elaine Choung-Hee Lee; Gabrielle E W Giersch; Douglas J Casa; Ki H Chon
Journal:  Nutrients       Date:  2019-12-23       Impact factor: 5.717

7.  Verification of the Propagation Range of Respiratory Strain Using Signal Waveform Measured by FBG Sensors.

Authors:  Shouhei Koyama; Atsushi Fujimoto; Yuma Yasuda; Yuuki Satou
Journal:  Sensors (Basel)       Date:  2020-12-10       Impact factor: 3.576

8.  Baroreflex Sensitivity Measured by Pulse Photoplethysmography.

Authors:  Jesús Lázaro; Eduardo Gil; Michele Orini; Pablo Laguna; Raquel Bailón
Journal:  Front Neurosci       Date:  2019-04-18       Impact factor: 4.677

9.  Enhancing the Robustness of Smartphone Photoplethysmography: A Signal Quality Index Approach.

Authors:  Ivan Liu; Shiguang Ni; Kaiping Peng
Journal:  Sensors (Basel)       Date:  2020-03-30       Impact factor: 3.576

  9 in total

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