Extracting features from Raman spectra for skin xerosis detection

Raman Spectroscopy has proved to be an efficient method in medicine for detecting alterations in bio – molecules structures and it is being used for detection of different diseases specifically skin lesions recently .In this paper , we studied skin roughness, so called skin xerosis , with Raman Spectroscopy technique. The main goal of this study was to determine the features from the Raman spectral data associated with skin xerosls . The Raman spectral dataset was constructed from two classes of spectral data , 70 spectra of normal intact skin and 70 spectra of irritated rough skin. Roughness irritation was done by sodium dodecyl sulfate (SDS) non-ionic surfactant applied once a day on rat skin within a week .The spectra were obtained from two rats from legs and dorsal anatomical regions. Some features related to specific bond vibrations of water , lipid and protein structures were extracted from the spectra . T- test statistical analysis was then utilized to determine if the specified feature could discriminate the two classes of spectral data. The statistical analysis of water content and lipid structures between two classes showed a significant difference by p-value <<0.1, whereas alterations in features related to proteins were not remarkable between two classes of data. These result suggest that changes in content and lipid structures results in skin roughness.

Keywords:

Raman Spectroscopy , Skin , T- test , statistical analysis , feature extraction , roughnee , xerosis