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17 February 2017 A multispectral testbed for cardiovascular sensing using imaging photoplethysmography
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Imaging photoplethysmography uses image sensors to measure changes in light absorption resulting from skin microvascular blood volume pulsations throughout the cardiac cycle. Imaging photoplethysmography has been demonstrated as an effective, non-contact means of assessing pulse rate, pulse rate variability, and respiration rate. Other potential uses include measuring spatial blood perfusion, oxygenation, and flow dynamics. Herein we demonstrate the development of a multispectral testbed for imaging photoplethysmography consisting of 12 monochromatic, 120fps imagers with 50nm, bandpass filters distributed from 400-750nm and contained in a 3D-printed, 4x3 grid housing mounted on a tripod positioned orthogonal to the subject. A co-located dual-CCD RGB/near-infrared imager records conventional RGB and NIR images expanding the spectral window recorded. After image registration, a multispectral image cube of the 13, partially overlapping bands is created. A spectrometer records high (spectral) resolution data from the participant’s right cheek using a collimating lens attached to the measurement fiber. In addition, a spatial array of 5 RGB imagers placed at 0°, ±20° and ±40° positions with respect to the subject is employed for motion and spatial robustness. All imagers are synchronized by a hardware trigger source synchronized with a reference, physiological measurement device recording the subject’s electrocardiography, bilateral fingertip and/or ear lobe photoplethysmography, bilateral galvanic skin response, and respiration signals. The development of the testbed and pilot data is presented. A full-scale evaluation of the spectral components of the imaging photoplethysmographic signal, optimization of iPPG SNR, and spatial perfusion and blood flow dynamics is currently underway.
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Ethan B. Blackford and Justin R. Estepp "A multispectral testbed for cardiovascular sensing using imaging photoplethysmography", Proc. SPIE 10072, Optical Diagnostics and Sensing XVII: Toward Point-of-Care Diagnostics, 100720R (17 February 2017);

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