Literature DB >> 20147775

Comparison of respiratory-induced variations in photoplethysmographic signals.

Jin Li1, Jie Jin, Xiang Chen, Weixin Sun, Ping Guo.   

Abstract

Photoplethysmography (PPG) is an optical method for detecting blood volume changes in tissue. Respiratory-induced intensity, frequency and amplitude variations are contained in the PPG signal; thus, an understanding of the relationships between all of these variations and respiration is essential to advancing respiration monitoring based on PPG. This study investigated correlations between respiratory-induced variations extracted from PPG and simultaneous respiratory signals. PPG signals were recorded from 28 healthy subjects under eight different conditions. Six respiratory-induced variations, i.e. the period of the systole, diastole and pulse, the amplitude of the systole and diastole, and the intensity variation, were determined from the PPG signal. The results indicate that, compared with the period of the pulse, the period of the systole and diastole correlates weakly with respiration; the amplitude of the diastole has a stronger correlation with respiration than the amplitude of the systole. For men, when the respiratory rate is less than 10 breaths min(-1), the period of the pulse has the strongest correlation with respiration, whereas up to or above 15 breaths min(-1), the intensity variation becomes strongest in the sitting posture, while the amplitude of the diastole is strongest in the supine posture. For women, compared with the other variations, the period of the pulse has nearly the strongest correlation with respiration, independent of respiratory rate or posture.

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Year:  2010        PMID: 20147775     DOI: 10.1088/0967-3334/31/3/009

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


  7 in total

1.  Using the multi-parameter variability of photoplethysmographic signals to evaluate short-term cardiovascular regulation.

Authors:  Xiang Chen; Ning Liu; Yuanyuan Huang; Feng Yun; Jue Wang; Jin Li
Journal:  J Clin Monit Comput       Date:  2014-11-19       Impact factor: 2.502

2.  Robust respiration detection from remote photoplethysmography.

Authors:  Mark van Gastel; Sander Stuijk; Gerard de Haan
Journal:  Biomed Opt Express       Date:  2016-11-03       Impact factor: 3.732

3.  Estimation of respiratory rate from motion contaminated photoplethysmography signals incorporating accelerometry.

Authors:  Delaram Jarchi; Peter Charlton; Marco Pimentel; Alex Casson; Lionel Tarassenko; David A Clifton
Journal:  Healthc Technol Lett       Date:  2019-02-21

4.  Design and Implementation of Respiration Rate Measurement System Using an Information Filter on an Embedded Device.

Authors:  Radius Bhayu Prasetiyo; Kyu-Sang Choi; Gi-Hun Yang
Journal:  Sensors (Basel)       Date:  2018-11-30       Impact factor: 3.576

Review 5.  Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review.

Authors:  Peter H Charlton; Drew A Birrenkott; Timothy Bonnici; Marco A F Pimentel; Alistair E W Johnson; Jordi Alastruey; Lionel Tarassenko; Peter J Watkinson; Richard Beale; David A Clifton
Journal:  IEEE Rev Biomed Eng       Date:  2017-10-24

Review 6.  Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring.

Authors:  Jesse Fine; Kimberly L Branan; Andres J Rodriguez; Tananant Boonya-Ananta; Jessica C Ramella-Roman; Michael J McShane; Gerard L Coté
Journal:  Biosensors (Basel)       Date:  2021-04-16

7.  Extracting Instantaneous Respiratory Rate From Multiple Photoplethysmogram Respiratory-Induced Variations.

Authors:  Parastoo Dehkordi; Ainara Garde; Behnam Molavi; J Mark Ansermino; Guy A Dumont
Journal:  Front Physiol       Date:  2018-07-18       Impact factor: 4.566

  7 in total

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