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      Extracting the Jugular Venous Pulse from Anterior Neck Contact Photoplethysmography

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          Abstract

          The jugular venous pulse (JVP) is the reference physiological signal used to detect right atrial and central venous pressure (CVP) abnormalities in cardio-vascular diseases (CVDs) diagnosis. Invasive central venous line catheterization has always been the gold standard method to extract it reliably. However, due to all the risks it entails, novel non-invasive approaches, exploiting distance cameras and lasers, have recently arisen to measure the JVP at the external and internal jugular veins. These remote options however, constraint patients to very specific body positions in front of the imaging system, making it inadequate for long term monitoring. In this study, we demonstrate, for the first time, that reflectance photoplethysmography (PPG) can be an alternative for extracting the JVP from the anterior jugular veins, in a contact manner. Neck JVP-PPG signals were recorded from 20 healthy participants, together with reference ECG and arterial finger PPG signals for validation. B-mode ultrasound imaging of the internal jugular vein also proved the validity of the proposed method. The results show that is possible to identify the characteristic a, c, v pressure waves in the novel signals, and confirm their cardiac-cycle timings in consistency with established cardiac physiology. Wavelet coherence values (close to 1 and phase shifts of ±180°) corroborated that neck contact JVP-PPG pulses were negatively correlated with arterial finger PPG. Average JVP waveforms for each subject showed typical JVP pulses contours except for the singularity of an unknown "u" wave occurring after the c wave, in half of the cohort. This work is of great significance for the future of CVDs diagnosis, as it has the potential to reduce the risks associated with conventional catheterization and enable continuous non-invasive point-of-care monitoring of CVP, without restricting patients to limited postures.

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          A Comprehensive Examination of Topographic Thickness of Skin in the Human Face

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            Non-contact hemodynamic imaging reveals the jugular venous pulse waveform

            Cardiovascular monitoring is important to prevent diseases from progressing. The jugular venous pulse (JVP) waveform offers important clinical information about cardiac health, but is not routinely examined due to its invasive catheterisation procedure. Here, we demonstrate for the first time that the JVP can be consistently observed in a non-contact manner using a photoplethysmographic imaging system. The observed jugular waveform was strongly negatively correlated to the arterial waveform (r = −0.73 ± 0.17), consistent with ultrasound findings. Pulsatile venous flow was observed over a spatially cohesive region of the neck. Critical inflection points (c, x, v, y waves) of the JVP were observed across all participants. The anatomical locations of the strongest pulsatile venous flow were consistent with major venous pathways identified through ultrasound.
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              Monitoring cardiac function in intensive care.

              Systolic cardiac function results from the interaction of four interdependent factors: heart rate, preload, contractility, and afterload. Heart rate can be quantified easily at the bedside, while preload estimation has traditionally relied on invasive pressure measurements, both central venous and pulmonary artery wedge. These have significant clinical limitations; however, adult literature has highlighted the superiority of several novel preload measures. Measurement of contractility and afterload is difficult; thus in clinical practice the bedside assessment of cardiac function is represented by cardiac output. A variety of techniques are now available for cardiac output measurement in the paediatric patient. This review summarises cardiac function and cardiac output measurement in terms of methodology, interpretation, and their contribution to the concepts of oxygen delivery and consumption in the critically ill child.
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                Author and article information

                Contributors
                irene.garcia-lopez15@imperial.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                26 February 2020
                26 February 2020
                2020
                : 10
                : 3466
                Affiliations
                ISNI 0000 0001 2113 8111, GRID grid.7445.2, Department of Electrical and Electronic Engineering, , Imperial College London, ; London, SW7 2AZ United Kingdom
                Author information
                http://orcid.org/0000-0003-4891-2175
                Article
                60317
                10.1038/s41598-020-60317-7
                7044195
                32103056
                ea2f9651-039c-4066-936c-784bdb475b1c
                © The Author(s) 2020

                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/.

                History
                : 3 October 2019
                : 8 February 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/100010663, EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council);
                Award ID: 724334
                Award Recipient :
                Categories
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                © The Author(s) 2020

                Uncategorized
                prognostic markers,cardiology,cardiovascular diseases,diagnosis,medical imaging
                Uncategorized
                prognostic markers, cardiology, cardiovascular diseases, diagnosis, medical imaging

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