Abstract
Objective: Spectral analysis of laser Doppler flowmetry (LDF) signals has been widely used in studies of physiological vascular function regulation. An alternative to LDF is the laser speckle contrast imaging method (LSCI), which is based on the same physical principle. In contrast to LDF, LSCI provides non-scanning full-field imaging of a relatively wide skin area and offers high spatial and temporal resolutions, which allows visualization of microvascular structure. This circumstance, together with a large number of works which had shown the effectiveness of temporal LSCI analysis, gave impetus to experimental studies of the relation between LDF and LSCI used to monitor the temporal dynamics of blood flow. Methods: Continuous wavelet transform was applied to construct a time-frequency representation of a signal. Results: Analysis of 10 minute LDF and LSCI output signals recorded simultaneously revealed rather high correlation between oscillating components. It was demonstrated for the first time that the spectral energy of oscillations in the 0.01-2 Hz frequency range of temporal LSCI recordings carries the same information as the conventional LDF recordings and hence it reflects the same physiological vascular tone regulation mechanisms. Conclusion: The approach proposed can be used to investigate speckle pattern dynamics by LSCI in both normal and pathological conditions. Significance: The results of research on the influence of spatial binning and averaging on the spectral characteristics of perfusion monitored by LSCI are of considerable interest for the development of LSCI systems optimized to evaluate temporal dynamics.
Original language | English |
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Article number | 8886444 |
Pages (from-to) | 1882-1889 |
Number of pages | 8 |
Journal | IEEE Transactions on Biomedical Engineering |
Volume | 67 |
Issue number | 7 |
Early online date | 29 Oct 2019 |
DOIs | |
Publication status | Published - Jul 2020 |
Bibliographical note
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- blood microcirculation
- laser Doppler flowmetry
- Laser speckle contrast imaging
- oscillations
- wavelets