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This paper reports a noninvasive method for evaluating skin aging based on near-infrared diffuse reflectance (NIR-DR) spectroscopy. Skin aging can be attributed to photoaging and chronological aging. Both types of aging are heavily involved in the skin changes that occur as we get older, for example, wrinkles or sagging skin. Our goal is to develop a noninvasive way to assess changes taking place inside the skin for each type of aging by using NIR-DR spectroscopy. Interior skin damages caused by photoaging and chronological aging were studied for an ultraviolet-B (UVB)-irradiated hairless mouse group (24 mice) and a non-irradiated group (29 mice) by using NIR-DR spectroscopy and principal component analysis (PCA). The results suggested the possibility of monitoring the contribution and the quantitative assessment of both types of aging taking place inside the skin by using the 5990-5490 cm(-1) and 5000-4480 cm(-1) regions of NIR-DR spectra. For the photoaging, structural changes in proteins are most clearly reflected by a shift of the band near 4880 cm(-1) due to a combination of amide A and amide II modes. On the other hand, the chronological aging is associated with a change in collagen quantity as is seen in the intensity changes in NIR bands assigned to collagen. NIR-DR spectroscopy and PCA may allow us to noninvasively assess the degree of photoaging and chronological aging as the degeneration of elasticity in collagen protein and the degradation of protein quantity, respectively.

This paper reports a non-invasive method for estimating skin thickness by using near infrared diffuse reflectance (NIR-DR) spectroscopy. Skin thickness is an important skin property in cosmetology, dermatology and pharmaceutical science. It varies significantly between the face and other body parts and changes with age and environment factors. Differences in skin thickness reflect the structural conditions of the epidermis and dermis. However, current methods for measuring skin thickness are complex and require cumbersome equipment. Therefore, we herein propose a NIR-DR and partial least squares (PLS) regression method for non-destructive skin thickness estimation. NIR-DR spectra were measured for UV-irradiated and non-irradiated skin on the backs of hairless mice and denuded back skin. Skin thickness increased gradually with the amount of UV irradiation, while changing little with physiological age. To obtain reference data, optical microscope measurements were carried out for denuded skin and total thickness and thickness of epidermis and dermis were determined. PLS regression was performed for the whole spectrum and selected regions specific for particular functional groups in order to estimate total thickness and thickness of epidermis and dermis. In the 6939-5990 cm-1 and 5242-4609 cm-1 regions, the bands due to amide groups of proteins appeared to contribute to models with the best coefficients of determination (R 2 cv) and standard error of cross-validation results; for total thickness, thickness of epidermis, and dermis, these were 0.79 and 25.80 µm, 0.72 and 21.87 µm and 0.77 and 8.16 µm, respectively. The results revealed that the wavenumbers contributing to the prediction of skin thickness differ between the epidermis and dermis.

The objective of the present study is to develop a novel nondestructive, simple, and quick method to evaluate the friction, twist, and gloss of human hair based on near-infrared diffuse reflectance (NIR-DR) spectroscopy and chemometrics. NIR-DR spectra were measured for human hair, which was collected from eleven Japanese women (age 5-44 years), by use of an optical fiber probe. Partial least squares (PLS) regression has been applied to the NIR-DR spectra of human hair after mean centering (MC), standard normal variate (SNV), and first derivative (1d) or second derivative (2d) analysis to develop calibration models that predict the friction, twist, and gloss of human hair. We identified the most suitable wavenumber region for the evaluation of each physical property. Correlation coefficients and standard errors of calibration of the PLS calibration models for the friction, twist, and gloss of hair were calculated to be 0.96 and 0.023, 0.81 and 3.27, and 0.90 and 0.36, respectively. Thus, the calibration models have high accuracy.

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