Extraction of the Structural Properties of Skin Tissue via Diffuse Reflectance Spectroscopy: An Inverse Methodology

Deep skin homogeneity and light diffusion: An accelerated Monte Carlo model for in vivo skin characterization and consumer perception

The appearance of healthy and youthful skin is related to many factors of the skin optical properties as perceived by our visual sense. The optics of light travelling through human tissues has been extensively investigated in the field of biomedical applications, including the experimental characterization and modelling of skin optics and the propagation of light such as lasers through the layers. This work presents an innovative approach to probe deep skin by means of spectrally and spatially resolved light diffusion in the different layers of skin. Dual hyperspectral measurements of the panellist's skin are performed in vivo on subjects to obtain reflectance and light diffusion spectra. Both are simultaneously fitted by a GPU-accelerated Monte Carlo model to obtain skin optical parameters as a function of depth. The results show a clear correlation between deep skin light diffusion at wavelengths above 590 nm and the subject age, which indicates a progressive degradation of skin homogeneity with age. The effect of this orange-red light diffusion background is to alter the colour tone of the skin. A skincare product is used to show that the warmer skin colour tone is clearly perceivable to consumers when evaluating facial images with and without the product. The product effect also correlates well with hyperspectral measurements. Lastly, this innovative approach demonstrates a first step in real-time skin characterization for consumers and opens the door to customized cosmetic solutions for individual needs.

Band selection for mapping chromophores of skin tissue

A numerical approach has been proposed to identify bands for optimally estimating the concentration of three types of viable chromophores within biological tissue. The bands are determined according to the condition number of absorption matrix associated with the attenuation coefficients of chromophores. The effectiveness of different sets of selected band combination was verified by using the spectral reflectance images of skin tissue acquired from standard forearm vascular occlusion tests via a spectroradiometer. Experimental results demonstrated that the concentration of chromophores within skin tissue could be estimated correctly and robustly only when the bands were deliberately selected.

Assessment of ROI Selection for Facial Video-Based rPPG

In general, facial image-based remote photoplethysmography (rPPG) methods use color-based and patch-based region-of-interest (ROI) selection methods to estimate the blood volume pulse (BVP) and beats per minute (BPM). Anatomically, the thickness of the skin is not uniform in all areas of the face, so the same diffuse reflection information cannot be obtained in each area. In recent years, various studies have presented experimental results for their ROIs but did not provide a valid rationale for the proposed regions. In this paper, to see the effect of skin thickness on the accuracy of the rPPG algorithm, we conducted an experiment on 39 anatomically divided facial regions. Experiments were performed with seven algorithms (CHROM, GREEN, ICA, PBV, POS, SSR, and LGI) using the UBFC-rPPG and LGI-PPGI datasets considering 29 selected regions and two adjusted regions out of 39 anatomically classified regions. We proposed a BVP similarity evaluation metric to find a region with high accuracy. We conducted additional experiments on the TOP-5 regions and BOT-5 regions and presented the validity of the proposed ROIs. The TOP-5 regions showed relatively high accuracy compared to the previous algorithm’s ROI, suggesting that the anatomical characteristics of the ROI should be considered when developing a facial image-based rPPG algorithm.