Mr. Ivan S. Zaletov Profile

Ivan S. Zaletov

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Publications (1)

Proceedings Article | 29 April 2022 Paper

Statistical and spectral properties of spatio-temporal skin temperature oscillations derived by sweat gland activity: thermal imaging exploration

Dmitry Mayskov, Andrey Fomin, Ivan Volkov, Ivan Zaletov, Anatoly Skripal, Andrey Sagaidachnyi

Proceedings Volume 12192, 121920Y (2022) https://doi.org/10.1117/12.2626927

KEYWORDS: Skin, Temperature metrology, Thermography, Wavelets, Hemodynamics, Statistical analysis, Nerve, Solids, Infrared radiation, Heart, Thermal imaging cameras

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The effect of sympathetic activation of sweat glands on the spatio-temporal distribution of skin temperature was studied. The practical significance of the study of sweat glands is supported by the fact that each sweat gland is controlled by the sympathetic cholinergic nerve. Dysfunction of the sympathetic nerve leads to inhibition of the activity of the sweat glands and accompanies many common diseases. In this study, the statistical and spectral properties of the dynamic infrared thermogram of skin with eccrine sweat glands during deep inspiratory gasp (breath test) were investigated. The number of open sweat pores was used as a ground truth measure for the activity of the sweat glands. Results: We found that the activation of the sweat glands, which characterizes the enhancement of the sympathetic response, leads to a change in the statistical spatial distribution of temperatures on the surface of the human body. The histogram of temperature showed a shift to the low-temperature region with a simultaneous increase in the standard deviation. The possibility of using the standard deviation and the skewness (asymmetry of the histogram) to assess the dynamics of the activity of sweat glands was shown. For the first time, the Statistical Pore Activation Index (SPAI) was introduced, which is more adaptive and shows greater accuracy than skewness. The activity of the sweat glands resulted in the appearance of spectral components within the region near 0.1 Hz, which is not typical for oscillations in skin temperature caused by hemodynamics. The results can be used for spectral separation of thermographic data from components caused by hemodynamics and activity of the sweat glands (vasomotor and sudomotor activities). Filtering the dynamic thermograms based on the investigated spectral and statistical features might serve as a method of mathematical processing for mapping the sweat glands and blood vessels on the skin surface. This might be used as a new diagnostic tool in the field of physiology and medicine.

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