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      Comparison of speckleplethysmographic (SPG) and photoplethysmographic (PPG) imaging by Monte Carlo simulations and in vivo measurements

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          Abstract

          Noncontact photoplethysmography (PPG) is limited by a poor signal-to-noise ratio (SNR). A solution to this limitation is the use of alternate sources of optical contrast to generate a complementary pulsatile waveform. One such source is laser speckle contrast, which is modulated in biological tissues by the flow rate of red blood cells. Averaging a region of interest from a speckle contrast image over time allows for the calculation of a speckleplethysmogram (SPG). Similar to PPG, SPG enables monitoring of heart rate and respiratory rate. A gap in the knowledge base exists as to the precise spatiotemporal relationship between PPG and SPG signals. We have developed an eight-layer tissue model to simulate both PPG and SPG signals in a reflectance geometry via Monte Carlo methods. We modeled PPG by compression of the upper and lower blood nets due to expansion of the larger arterial layer below. The in silico PPG peak-to-peak amplitude percent was greater at 532 nm than at 860 nm (5.6% vs. 3.0%, respectively), which matches trends from the literature. We modeled SPG by changing flow speeds of red blood cells in both the capillaries and arterioles over the cardiac cycle. The in silico SPG peak-to-peak amplitude percent was 24% at 532 nm and 40% at 860 nm. In silico results are similar to in vivo results measured with a two-camera set up for simultaneous imaging of PPG and SPG. Both in silico and in vivo data suggest SPG has a much larger SNR than PPG, which may prove beneficial for noncontact, wide-field optical monitoring of cardiovascular health.

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          Microcirculation in hypertension: a new target for treatment?

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            Flow visualization by means of single-exposure speckle photography

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              Contactless multiple wavelength photoplethysmographic imaging: a first step toward "SpO2 camera" technology.

              We describe a route toward contactless imaging of arterial oxygen saturation (SpO2) distribution within tissue, based upon detection of a two-dimensional matrix of spatially resolved optical plethysmographic signals at different wavelengths. As a first step toward SpO2-imaging we built a monochrome CMOS-camera with apochromatic lens and 3lambda-LED-ringlight (lambda1 = 660 nm, lambda2 = 810 nm, lambda3 = 940 nm; 100 LEDs lambda(-1)). We acquired movies at three wavelengths while simultaneously recording ECG and respiration for seven volunteers. We repeated this experiment for one volunteer at increased frame rate, additionally recording the pulse wave of a pulse oximeter. Movies were processed by dividing each image frame into discrete Regions of Interest (ROIs), averaging 10 x 10 raw pixels each. For each ROI, pulsatile variation over time was assigned to a matrix of ROI-pixel time traces with individual Fourier spectra. Photoplethysmograms correlated well with respiration reference traces at three wavelengths. Increased frame rates revealed weaker pulsations (main frequency components 0.95 and 1.9 Hz) superimposed upon respiration-correlated photoplethysmograms, which were heartbeat-related at three wavelengths. We acquired spatially resolved heartbeat-related photoplethysmograms at multiple wavelengths using a remote camera. This feasibility study shows potential for non-contact 2-D imaging reflection-mode pulse oximetry. Clinical devices, however, require further development.
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                Author and article information

                Journal
                Biomed Opt Express
                Biomed Opt Express
                BOE
                Biomedical Optics Express
                Optical Society of America
                2156-7085
                15 August 2018
                01 September 2018
                15 August 2018
                : 9
                : 9
                : 4306-4316
                Affiliations
                [1 ]Beckman Laser Institute and Medical Clinic, University of California-Irvine, 1002 Health Sciences Road East, Irvine, CA 92612, USA
                [2 ]Department of Biomedical Engineering, University of California, Irvine, 3120 Natural Sciences II, Irvine, CA 92697, USA
                [3 ]Edwards Lifesciences Center for Advanced Cardiovascular Technology, University of California, Irvine, 2400 Engineering Hall, Irvine, CA 92697, USA
                [4 ]Department of Surgery, University of California, Irvine, 333 City Boulevard West, Suite 1600, Orange, CA 92868, USA
                Author notes
                Article
                332266
                10.1364/BOE.9.004306
                6157764
                © 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

                © 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

                Funding
                Funded by: Arnold and Mabel Beckman Foundation 10.13039/100000997
                Funded by: National Institutes of Health (NIH) 10.13039/100000002
                Award ID: EB015890
                Award ID: HL116270
                Award ID: TR001415
                Funded by: National Science Foundation (NSF) 10.13039/100000001
                Award ID: DGE 1321846
                Funded by: University of California, Irvine (UCI) 10.13039/100008476
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