University of Oulu

E. Zherebtsov, I. Kozlov, V. Dremin, A. Bykov, A. Dunaev and I. Meglinski, "Diagnosis of Skin Vascular Complications Revealed by Time-Frequency Analysis and Laser Doppler Spectrum Decomposition," in IEEE Transactions on Biomedical Engineering, vol. 70, no. 1, pp. 3-14, Jan. 2023, doi: 10.1109/TBME.2022.3181126

Diagnosis of skin vascular complications revealed by time-frequency analysis and laser doppler spectrum decomposition

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Author: Zherebtsov, Evgeny1,2; Kozlov, Igor2; Dremin, Viktor3,2;
Organizations: 1Opto-Electronics and Measurement Techniques, University of Oulu, Oulu, Finland
2R&D Center of Biomedical Photonics, Orel State University, Orel, Russia
3College of Engineering and Physical Sciences, Aston University, U.K.
4Opto-Electronics and Measurement Techniques, University of Oulu, Finland
5Institute of Clinical Medicine N.V. Sklifosovsky, I.M. Sechenov First Moscow State Medical University Bol’shaya Pirogovskaya Ulitsa, Russia
6Institute of Engineering Physics for Biomedicine, National Research Nuclear University (MEPhI), Russia
7Immanuel Kant Baltic Federal University, Russia
8Interdisciplinary Laboratory of Biophotonics, Tomsk State University, Russia
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 17.2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2023-03-02


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.

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Series: IEEE transactions on bio-medical engineering
ISSN: 0018-9294
ISSN-E: 1558-2531
ISSN-L: 0018-9294
Volume: 70
Issue: 1
Pages: 3 - 14
DOI: 10.1109/TBME.2022.3181126
Type of Publication: A1 Journal article – refereed
Field of Science: 114 Physical sciences
Funding: This work was supported in part by the Academy of Finland under Grants 318281 and 326204, in part by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 863214-NEUROPA Project, in part by the Decree of the Government of the Russian Federation under Grant 220 of 09 April 2010 and under Grant 075-15-2021-615 of 04 June 2021, in part by the Ministry of Science and Higher Education of the Russian Federation through State support for the creation and development of World-Class Research Centres, Digital Biodesign and Personalized Healthcare under Grant 075-15-2020-926, and in part by the Russian Foundation for Basic Research, under Project 19-32-90253. The collection of the clinical data was supported by the Russian Foundation for Basic Research (RFBR) under Grant 20-08-01153. The processing of the data from the heating test experiment was supported by the Russian Science Foundation, under Grant 20-75-00123.
EU Grant Number: (863214) NEUROPA - Non-invasive dynamic neural control by laser-based technology
Academy of Finland Grant Number: 318281
Detailed Information: 318281 (Academy of Finland Funding decision)
326204 (Academy of Finland Funding decision)
Copyright information: © The Author(s) 2022. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see