Kozlov, I.; Zherebtsov, E.; Masalygina, G.; Podmasteryev, K.; Dunaev, A. Laser Doppler Spectrum Analysis Based on Calculation of Cumulative Sums Detects Changes in Skin Capillary Blood Flow in Type 2 Diabetes Mellitus. Diagnostics 2021, 11, 267. https://doi.org/10.3390/diagnostics11020267
Laser Doppler spectrum analysis based on calculation of cumulative sums detects changes in skin capillary blood flow in type 2 diabetes mellitus
|Author:||Kozlov, Igor1; Zherebtsov, Evgeny1,2; Masalygina, Galina3;|
1Research and Development Center of Biomedical Photonics, Orel State University, 302026 Orel, Russia
2Optoelectronics and Measurement Techniques Unit, University of Oulu, 90570 Oulu, Finland
3Orel Regional Clinical Hospital, 302028 Orel, Russia
|Online Access:||PDF Full Text (PDF, 6.9 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021051029329
Multidisciplinary Digital Publishing Institute,
|Publish Date:|| 2021-05-10
In this article, we introduce a new method of signal processing and data analysis for the digital laser Doppler flowmetry. Our approach is based on the calculation of cumulative sums over the registered Doppler power spectra. The introduced new parameter represents an integral estimation for the redistribution of moving red blood cells over the range of speed. The prototype of the device implementing the technique is developed and tested in preliminary clinical trials. The methodology was verified with the involvement of two age groups of healthy volunteers and in a group of patients with type 2 diabetes mellitus. The main practical result of the study is the development of a set of binary linear classifiers that allow the method to identify typical patterns of the microcirculation for the healthy volunteers and diabetic patients based on the presented diagnostic algorithm.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
217 Medical engineering
The reported study was funded by the Russian Foundation for Basic Research (RFBR), project numbers 19-32-90253. E. Zherebtsov acknowledges the funding from the Academy of Finland (grant number 318281, data analysis) and Russian Science Foundation (grant number 20-75-00123, development of the experimental setup).
|Academy of Finland Grant Number:||
318281 (Academy of Finland Funding decision)
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).