A machine-learning model for quantitative characterization of human skin using photothermal radiometry and diffuse reflectance spectroscopy

Author(s):  
Nina Verdel ◽  
Jovan Tanevski ◽  
Sašo Džeroski ◽  
Boris Majaron
Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 302
Author(s):  
Ana Marin ◽  
Nina Verdel ◽  
Matija Milanič ◽  
Boris Majaron

We have augmented a recently introduced method for noninvasive analysis of skin structure and composition and applied it to monitoring of dynamical processes in traumatic bruises. The approach combines diffuse reflectance spectroscopy in visible spectral range and pulsed photothermal radiometry. Data from both techniques are analyzed simultaneously using a numerical model of light and heat transport in a four-layer model of human skin. Compared to the earlier presented approach, the newly introduced elements include two additional chromophores (β-carotene and bilirubin), individually adjusted thickness of the papillary dermal layer, and analysis of the bruised site using baseline values assessed from intact skin in its vicinity. Analyses of traumatic bruises in three volunteers over a period of 16 days clearly indicate a gradual, yet substantial increase of the dermal blood content and reduction of its oxygenation level in the first days after injury. This is followed by the emergence of bilirubin and relaxation of all model parameters towards the values characteristic for healthy skin approximately two weeks after the injury. The assessed parameter values and time dependences are consistent with existing literature. Thus, the presented methodology offers a viable approach for objective characterization of the bruise healing process.


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