Narrow Results

The skin is the largest (and the most exposed) organ of the body both in terms of surface area and weight. Its care is of great importance for both aesthetics and health issues. Often, the skin appearance gives us information about the skin health status as well as hints at the biological age. Therefore, the skin surface characterization is of great significance for dermatologists as well as for cosmetic scientists in order to evaluate the effectiveness of medical or cosmetic treatments. So far, no in vivo measurements regarding skin topography characterization could be achieved routinely to evaluate skin aging. This work describes how a portable capacitive device, normally used for fingerprint acquisition, can be utilized to achieve measures of skin aging routinely. The capacitive images give a high resolution (50 μm) representation of skin topography, in terms of wrinkles and cells. In this work, we have addressed the latter: through image segmentation techniques, cells have been localized and identified and a feature related to their area distribution has been generated. Accurate experiments accomplished in vivo show how the feature we conceived is linearly related to skin aging. Besides, since this finding has been achieved using a low cost portable device, this could boost research in this field as well as open doors to an application based on an embedded system.

Quantitative evaluation of the changes in skin topographic structures are of great importance in the dermocosmetic field to assess subjects response to medical or cosmetic treatments. Although many devices and methods are known to measure these changes, they are not suitable for a routine approach and most of them are invasive. Moreover, it has always been difficult to give a measure of the skin health status as well as of the human aging process by simply analyzing the skin surface appearance. This work describes how a portable capacitive device could be utilized to achieve measurements of skin ageing in vivo and routinely. The capacitive images give a high resolution representation of the skin micro-relief, both in terms of skin surface tissue and wrinkles. In a previous work we dealt with the former; here we have addressed the latter. The algorithm we have developed allowed us to extract two original features from wrinkles: the first is based on photometric properties while the second has been achieved through the multiresolution analysis of the wavelet transform. Accurate experiments accomplished on 87 subjects show how the features we conceived are related to skin ageing.