Influence of temporal noise on the skin blood flow measurements performed by cooled thermal imaging camera: limit possibilities within each physiological frequency range

Sagaidachnyi, A. A.; Volkov, Ivan U.; Fomin, A. V.

doi:10.1117/12.2229476

Cited by 4 publications

(7 citation statements)

References 7 publications

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“…The same effect is manifested earlier around 0.1 Hz in the study (Mizeva et al 2015b). At frequencies of about 0.2-0.3 Hz, the phase shift between temperature and blood flow oscillations can theoretically be expected for the full period (see figure 3), but this is difficult to prove experimentally due to the temporal noise (Sagaidachnyi et al 2016).…”

Section: Features Of the Phase Shift Between Temperature And Blood Fl...mentioning

confidence: 58%

Thermography-based blood flow imaging in human skin of the hands and feet: a spectral filtering approach

et al. 2017

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The determination of the relationship between skin blood flow and skin temperature dynamics is the main problem in thermography-based blood flow imaging. Oscillations in skin blood flow are the source of thermal waves propagating from micro-vessels toward the skin's surface, as assumed in this study. This hypothesis allows us to use equations for the attenuation and dispersion of thermal waves for converting the temperature signal into the blood flow signal, and vice versa. We developed a spectral filtering approach (SFA), which is a new technique for thermography-based blood flow imaging. In contrast to other processing techniques, the SFA implies calculations in the spectral domain rather than in the time domain. Therefore, it eliminates the need to solve differential equations. The developed technique was verified within 0.005-0.1 Hz, including the endothelial, neurogenic and myogenic frequency bands of blood flow oscillations. The algorithm for an inverse conversion of the blood flow signal into the skin temperature signal is addressed. The examples of blood flow imaging of hands during cuff occlusion and feet during heating of the back are illustrated. The processing of infrared (IR) thermograms using the SFA allowed us to restore the blood flow signals and achieve correlations of about 0.8 with a waveform of a photoplethysmographic signal. The prospective applications of the thermography-based blood flow imaging technique include non-contact monitoring of the blood supply during engraftment of skin flaps and burns healing, as well the use of contact temperature sensors to monitor low-frequency oscillations of peripheral blood flow.

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Section: Features Of the Phase Shift Between Temperature And Blood Fl...mentioning

confidence: 58%

Thermography-based blood flow imaging in human skin of the hands and feet: a spectral filtering approach

et al. 2017

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“…The temperature sensitivity of the IRT camera T620 that was used to measure skin temperature in this study is about 0.04°C. According to a study on the influence of temporal noise on skin blood flow measurements by IRT camera 29 , the upper‐frequency limit of temperature oscillations measured by an IRT camera with a sensitivity of 0.04°C is about only 0.05 Hz. Therefore, only temperature oscillations within endothelial (0.0095–0.02 Hz) and neurogenic (0.02–0.05 Hz) ranges can be recommended for the estimation of skin blood flow.…”

Section: Discussionmentioning

confidence: 99%

“…Another reason may be related to the better reproducibility and reliability of the LSCI technique compared with LDF, 8 which makes the phase relation of IRT and LSCI spectra statistically clearer.The low cross-correlation of LSCI and IRT spectra within highfrequency ranges is mainly caused by the small amplitude of skin temperature pulsations. The temperature sensitivity of the IRT camera T620 that was used to measure skin temperature in this study is about 0.04 • C. According to a study on the influence of temporal noise on skin blood flow measurements by IRT camera29 , the upperfrequency limit of temperature oscillations measured by an IRT camera with a sensitivity of 0.04 • C is about only 0.05 Hz. Therefore, only temperature oscillations within endothelial (0.0095-0.02 Hz) and neurogenic (0.02-0.05 Hz) ranges can be recommended for the estimation of skin blood flow.…”

mentioning

confidence: 92%

Spectral analysis of laser speckle contrast imaging and infrared thermography to assess skin microvascular reactive hyperemia

Querleux

Lei

et al. 2023

Skin Research and Technology

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Background Post‐occlusive reactive hyperemia (PORH) test with signal spectral analysis coupled provides potential indicators for the assessment of microvascular functions. Objective The objective of this study is to investigate the variations of skin blood flow and temperature spectra in the PORH test. Furthermore, to quantify the oscillation amplitude response to occlusion within different frequency ranges. Materials and methods Ten healthy volunteers participated in the PORH test and their hand skin temperature and blood flow images were captured by infrared thermography (IRT) and laser speckle contrast imaging (LSCI) system, respectively. Extracted signals from selected areas were then transformed into the time‐frequency space by continuous wavelet transform for cross‐correlation analysis and oscillation amplitude response comparisons. Results The LSCI and IRT signals extracted from fingertips showed stronger hyperemia response and larger oscillation amplitude compared with other areas, and their spectral cross‐correlations decreased with frequency. According to statistical analysis, their oscillation amplitudes in the PORH stage were obviously larger than the baseline stage within endothelial, neurogenic, and myogenic frequency ranges (p < 0.05), and their quantitative indicators of oscillation amplitude response had high linear correlations within endothelial and neurogenic frequency ranges. Conclusion Comparisons of IRT and LSCI techniques in recording the reaction to the PORH test were made in both temporal and spectral domains. The larger oscillation amplitudes suggested enhanced endothelial, neurogenic, and myogenic activities in the PORH test. We hope this study is also significant for investigations of response to the PORH test by other non‐invasive techniques.

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“…Analysis of useful and noise components of the temperature signal performed within time and spectral domains in order to estimate the frequency range permissible for established temperature -blood flow relation [5]. The analyzing signals appeared as shown in figure 1.…”

Section: Permissible Frequency Range Of Measurements and Sensitivity mentioning

confidence: 99%

“…Amplitude of temperature oscillations vs. frequency range on figure 4 can be approximated by the function aexp(-bf C ), where a=0.8, b=8, c=0.34, f -frequency of oscillations (see [5] for details). The empirical curve in figure 4 can be important to practice.…”

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confidence: 99%

Spectral filtering approach to the skin blood flow imaging in limbs via infrared thermography: its scope and limits

Sagaidachnyi¹,

Fomin²,

Skripal³

et al. 2016

Proceedings of the 2016 International Conference on Quantitative InfraRed Thermography

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We develop the new technique for skin blood flow imaging in limbs by means of infrared thermography. In contrast to the lock-in and pulsed phase thermography the proposed method does not use an external heater. Instead, we consider variation of blood volume within the vessels of limbs as a source of thermal waves, travelling through the biotissue. Thus, the blood flow dynamics serves as a non-periodical heater of biological tissue. To reconstruct the blood flow variation from dynamic thermograms we used the spectral filtering approach (SFA), which transforms the temperature signal into the blood flow signal. Reaction of lower limbs on the thermal impact is illustrated by examples of dynamics blood flow maps that are extracted from dynamic thermograms. Limitations and advantages of the blood flow exploration via infrared thermography within each of the frequency range have been discussed.

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Influence of temporal noise on the skin blood flow measurements performed by cooled thermal imaging camera: limit possibilities within each physiological frequency range

Cited by 4 publications

References 7 publications

Thermography-based blood flow imaging in human skin of the hands and feet: a spectral filtering approach

Thermography-based blood flow imaging in human skin of the hands and feet: a spectral filtering approach

Spectral analysis of laser speckle contrast imaging and infrared thermography to assess skin microvascular reactive hyperemia

Spectral filtering approach to the skin blood flow imaging in limbs via infrared thermography: its scope and limits

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