Autors: Mateev, V. M., Marinova, I. Y.
Title: Noninvasive blood flow sensing from surface skin measurements
Keywords: Blood, Blood vessels, Hemodynamics, Voltage distribution mea

Abstract: Electromagnetic flow sensing method is proposed for non-invasive vascular measurements from surface skin. Method is performed by multielectrode voltage measurements acquired over skin surface. A forward 3D electromagnetic, finite element method model (FEM) is developed for skin voltage distribution calculation. FEM model represents the anatomically precise geometrical model of human leg with known blood flow speed in its vessels and tissue electrical conductivities. Induced voltages on leg surface are measured by multielectrode measurement system. Using these data an inverse source problem is formulated and solved. Inverse source problem uses the Green's function for Helmholtz's equation.


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Proceedings of the International Conference on Sensing Technology, ICST. 13th International Conference on Sensing Technology, ICST 2019, vol. ICST 2019, issue 2019, pp. Article number 9047719, 2019, Austria, IEEE Computer Society, DOI 10.1109/ICST46873.2019.9047719

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Цитирания (Citation/s):
1. Yang, D., Wang, Y., Xu, B., Wang, X., Liu, Y., Cheng, T., A deep neural network method for arterial blood flow profile reconstruction, (2021) Entropy, 23 (9), art. no. 1114, DOI: 10.3390/e23091114 - 2021 - в издания, индексирани в Scopus или Web of Science

Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus