Separate extraction of human eccrine sweat gland activity and peripheral hemodynamics from high- and low-quality thermal imaging data

Abstract

Sweat gland activity and peripheral hemodynamics, which characterize the function of sympathetic cholinergic nerve fibers and the manifestation mechanisms of vascular tone regulation, respectively, can be detected via dynamic thermography of the skin. Thus, they are useful parameters for diagnosing various forms of neuropathy and functional circulatory disorders. Both parameters affect the dynamics of the skin temperature; therefore, for an adequate description of thermographic data, it is necessary to build models that consider both these coexisting components simultaneously.

Purpose: The objective of this study was to determine the spatiotemporal and statistical features of dynamic thermograms of skin areas with sweat glands and to develop methods for the extraction of temperature components mediated by sweat gland activity (T_sweat) separately from hemodynamics (T_blood) based on thermograms of high and low temperature resolutions.

Methods: To separate the T_sweat and T_blood components, simultaneous thermographic and photoplethysmographic (PPG) measurements were performed in the area of the fingers during a deep inspiratory gasp (DIG). PPG data, which were obtained solely by hemodynamics, were converted into a temperature signal (T_blood) using the spectral filtering approach. By calculating the difference between the skin (T_skin) and blood (T_blood) temperature components, the T_sweat component was determined, which characterizes sweat gland activity and the integrity of the cholinergic sympathetic nerve fibers that innervate them. The T_sweat component was compared with the active sweat pore count curve, which was determined by the adaptive detection of local temperature minima. Thermographic and PPG measurements were performed for 3 min on a group of 15 volunteers during the DIG test. The skin temperature was measured using a cooled thermal imaging camera in the spectral range of 8-9 μm with a temperature sensitivity of 0.02 °C. PPG measurements were performed using a reflectance sensor with a central wavelength of 800 nm. Wavelet analysis with the Morlet basis function was used to preliminarily determine the spectrum of spontaneous temperature oscillations in an area of the skin with and without sweat pores. Statistical parameters of the histogram, such as the standard deviation and the statistical pore activation index (SPAI) - which is proposed in this paper were used in the DIG test to detect sweat gland activity with low-temperature resolution thermograms. The temporal dynamics of the statistical parameters were compared with the dynamics of the sweat pore count.

Results: The T_sweat component was correlated with the sweat pore count on the thermogram with a coefficient of 0.75, confirming the dependence of this temperature component on the sweat gland activity and the need for considering this activity in the analysis of the spatiotemporal dynamics of the human skin temperature. The use of the proposed SPAI and standard deviation allows the detection of sweat gland activity even with thermograms of a low temperature resolution. The use of an integrated map of the sweat gland activity will help the specialist to assess the degree of integrity of the innervation of skin areas in a single image. The primary assessment of the spectrum of temperature oscillations at rest indicated that spontaneous sweat gland activity is accompanied by high-frequency oscillations in the skin temperature localized in the area of sweat pores, within the frequency range of 0.07-0.3 Hz. This suggests the possibility of spectral separation of the temperature component mediated by sweat gland activity from the hemodynamic component, which dominates in the region of <0.1 Hz. The proposed two-component approach for the analysis of skin temperature dynamics allows separate assessment of sympathetic innervation and rhythms of hemodynamic regulation using dynamic thermograms.

Keywords: Deep inspiratory gasp; Infrared thermography; Skin temperature; Sudomotor; Sweat glands; Wavelet analysis.