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. 2020 Jul 2;10:10884. doi: 10.1038/s41598-020-67647-6

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© 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/.

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To evaluate peripheral hemodynamics we calculate pulse rate variability, pulse amplitude and vasomotion measures. We capture videos from digital cameras, segment a skin region (either on the face or on the hand) and calculate spatial averages of the color channel signals within the region of interest. We then recover the total blood concentration using a calibrated model-based approach. Finally we extract frequency domain measures of the physiological parameters. The face images used are examples provided with consent to be published in an online open-access publication.