Diagnosis of Skin Vascular Complications Revealed by Time-Frequency Analysis and Laser Doppler Spectrum Decomposition

Abstract

Nowadays, photonics-based techniques are used extensively in various applications, including functional clinical diagnosis, progress monitoring in treatment, and provision of metrological control. In fact, in the frame of practical implementation of optical methods, such as laser Doppler flowmetry (LDF), the qualitative interpretation and quantitative assessment of the detected signal remains vital and urgently required. In the conventional LDF approach, the key measured parameters, index of microcirculation and perfusion rate, are proportional to an averaged concentration of red blood cells (RBC) and their average velocity within a diagnostic volume. These quantities compose mixed signals from different vascular beds with a range of blood flow velocities and are typically expressed in relative units. In the current paper we introduce a new signal processing approach for the decomposition of LDF power spectra in terms of ranging blood flow distribution by frequency series. The developed approach was validated in standard occlusion tests conducted on healthy volunteers, and applied to investigate the influence of local pressure rendered by a probe on the surface of the skin. Finally, in limited clinical trials, we demonstrate that the approach can significantly improve the diagnostic accuracy of detection of microvascular changes in the skin of the feet in patients with Diabetes Mellitus type 2, as well as age-specific changes. The results obtained show that the developed approach of LDF signal decomposition provides essential new information about blood flow and blood microcirculation and has great potential in the diagnosis of vascular complications associated with various diseases.

Publication DOI: https://doi.org/10.1109/TBME.2022.3181126
Divisions: College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT)
College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Additional Information: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ Funding: The authors acknowledge the support of the Academy of Finland (grants No. 318281, 326204). This work has also been partially supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No.863214 - NEUROPA project, a grant under the Decree of the Government of the Russian Federation No. 220 of 09 April 2010 (Agreement No. 075-15-2021-615 of 04 June 2021) and the Ministry of Science and Higher Education of the Russian Federation, within the framework of State support for the creation and development of World-Class Research Centres, “Digital Biodesign and Personalized Healthcare” No. 075-15-2020-926 and Russian Foundation for Basic Research, project No. 19-32-90253. The collection of the clinical data was funded by the Russian Foundation for Basic Research (RFBR), grant No. 20-08-01153. The processing of the data from the heating test experiment was funded by the Russian Science Foundation, grant No. 20-75-00123 (Corresponding author: Evgeny A. Zherebtsov)
Uncontrolled Keywords: Biomedical measurement,Biomedical optical imaging,Blood,Blood flow,Diabetes Mellitus,Laser Doppler flowmetry,Optical scattering,Research and development,Skin,blood flow,microcirculation,optical Doppler effect,skin blood perfusion,Biomedical Engineering
Publication ISSN: 1558-2531
Last Modified: 24 Apr 2024 07:22
Date Deposited: 16 Jun 2022 12:37
Full Text Link:
Related URLs: https://ieeexpl ... cument/9792227/ (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2022-06-09
Published Online Date: 2022-06-09
Accepted Date: 2022-06-01
Authors: Zherebtsov, Evgeny
Kozlov, Igor
Dremin, Viktor (ORCID Profile 0000-0001-6974-3505)
Bykov, Alexander
Dunaev, Andrey
Meglinski, Igor (ORCID Profile 0000-0002-7613-8191)

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