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

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          Abstract

          Heart rate variability (HRV) provides insight into cardiovascular health and autonomic function. Electrocardiography (ECG) provides gold standard HRV measurements but is inconvenient for continuous acquisition when monitored from the extremities. Optical techniques such as photoplethysmography (PPG), often found in health and wellness trackers for heart rate measurements, have been used to estimate HRV peripherally but decline in accuracy during increased physical stress. Speckleplethysmography (SPG) is a recently introduced optical technique that provides benefits over PPG, such as increased signal amplitude and reduced susceptibility to temperature-induced vasoconstriction. In this research, we compare SPG and PPG to ECG for estimation of HRV during an orthostatic challenge performed by 17 subjects. We find that SPG estimations of HRV are highly correlated to ECG HRV for both time and frequency domain parameters and provide increased accuracy over PPG estimations of HRV. The results suggest SPG measurements are a viable alternative for HRV estimation when ECG measurements are impractical.

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          Most cited references 25

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          A quantitative systematic review of normal values for short-term heart rate variability in healthy adults.

          Heart rate variability (HRV) is a known risk factor for mortality in both healthy and patient populations. There are currently no normative data for short-term measures of HRV. A thorough review of short-term HRV data published since 1996 was therefore performed. Data from studies published after the 1996 Task Force report (i.e., between January 1997 and September 2008) and reporting short-term measures of HRV obtained in normally healthy individuals were collated and factors underlying discrepant values were identified. Forty-four studies met the pre-set inclusion criteria involving 21,438 participants. Values for short-term HRV measures from the literature were lower than Task Force norms. A degree of homogeneity for common measures of HRV in healthy adults was shown across studies. A number of studies demonstrate large interindividual variations (up to 260,000%), particularly for spectral measures. A number of methodological discrepancies underlined disparate values. These include a systematic failure within the literature (a) to recognize the importance of RR data recognition/editing procedures and (b) to question disparate HRV values observed in normally healthy individuals. A need for large-scale population studies and a review of the Task Force recommendations for short-term HRV that covers the full-age spectrum were identified. Data presented should be used to quantify reference ranges for short-term measures of HRV in healthy adult populations but should be undertaken with reference to methodological factors underlying disparate values. Recommendations for the measurement of HRV require updating to include current technologies. ©2010, The Authors. Journal compilation ©2010 Wiley Periodicals, Inc.
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            Photoplethysmography pulse rate variability as a surrogate measurement of heart rate variability during non-stationary conditions.

            In this paper we assessed the possibility of using the pulse rate variability (PRV) extracted from the photoplethysmography signal as an alternative measurement of the HRV signal in non-stationary conditions. The study is based on analysis of the changes observed during a tilt table test in the heart rate modulation of 17 young subjects. First, the classical indices of HRV analysis were compared to the indices from PRV in intervals where stationarity was assumed. Second, the time-varying spectral properties of both signals were compared by time-frequency (TF) and TF coherence analysis. Third, the effect of replacing PRV with HRV in the assessment of the changes of the autonomic modulation of the heart rate was considered. Time-invariant HRV and PRV indices showed no statistically significant differences (p > 0.05) and high correlation (>0.97). Time-frequency analysis revealed that the TF spectra of both signals were highly correlated (0.99 +/- 0.01); the difference between the instantaneous power, in the LF and HF bands, obtained from HRV and PRV was small (<10(-3) s(-2)) and their temporal patterns were highly correlated (0.98 +/- 0.04 and 0.95 +/- 0.06 in the LF and HF bands, respectively) and TF coherence in the LF and HF bands was high (0.97 +/- 0.04 and 0.89 +/- 0.08, respectively). Finally, the instantaneous power in the LF band was observed to significantly increase during head-up tilt by both HRV and PRV analysis. These results suggest that although some differences in the time-varying spectral indices extracted from HRV and PRV exist, mainly in the HF band associated with respiration, PRV could be used as a surrogate of HRV during non-stationary conditions, at least during the tilt table test.
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              Power spectrum analysis of heart rate variability: a tool to explore neural regulatory mechanisms.

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                Author and article information

                Contributors
                choib@uci.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                1 October 2019
                1 October 2019
                2019
                : 9
                Affiliations
                [1 ]ISNI 0000 0001 0668 7243, GRID grid.266093.8, Beckman Laser Institute and Medical Clinic, , University of California, ; Irvine, California 92612 USA
                [2 ]ISNI 0000 0001 0668 7243, GRID grid.266093.8, Department of Biomedical Engineering, , University of California, ; Irvine, California 92697 USA
                [3 ]ISNI 0000 0001 0668 7243, GRID grid.266093.8, Edwards Lifesciences Center for Advanced Cardiovascular Technology, University of California, ; Irvine, California 92697 USA
                [4 ]ISNI 0000 0001 0668 7243, GRID grid.266093.8, Department of Neurology, University of California, ; Irvine, California 92697 USA
                [5 ]ISNI 0000 0001 0668 7243, GRID grid.266093.8, Department of Ecology and Evolutionary Biology, University of California, ; Irvine, California 92697 USA
                [6 ]ISNI 0000 0001 0668 7243, GRID grid.266093.8, Department of Surgery, University of California, ; Irvine, California 92697 USA
                Article
                50526
                10.1038/s41598-019-50526-0
                6773734
                31575905
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                Funding
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: P41EB015890
                Award Recipient :
                Categories
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                © The Author(s) 2019

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                translational research, diagnosis

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