Evaluation of temporal scales of migration of cosmetic ingredients into the human skin by two-dimensional dynamic speckle analysis

  • E. Stoykova
  • B. Blagoeva
  • D. Nazarova
  • L. Nedelchev
  • T. Nikova
  • N. Berberova
  • Y.-M. Kim
  • H.-J. Kang
Article
  • 37 Downloads
Part of the following topical collections:
  1. Focus on Optics and Bio-photonics, Photonica 2017

Abstract

A variety of biomedical and food quality assessment tasks have been solved by statistical processing of speckle patterns formed on the surface of diffusely reflecting objects. The output of pointwise processing of a temporal sequence of correlated speckle images is a two-dimensional spatial contour map which characterizes the time scales of the ongoing physical or biological activity within the studied objects. In this work, we check efficiency of the dynamic speckle analysis for temporal characterization of migration of cosmetic ingredients from the skin surface to the lower skin layers. At illumination with a He–Ne laser, formation of speckle patterns on the skin surface is governed by the diffusely reflected photons which have undergone a lot of scattering events in the bulk of the tissue. This entails low time-correlation of the formed speckle patterns. Activity maps have been built for sections of treated and non-treated skin on the arm of a volunteer. We found out that a bare skin exhibited high activity which decreased for a skin treated by a cream or cosmetic oil. We proved that the observed difference between the activity maps for a bare skin and a treated skin would allow for monitoring of the time scales of penetration of various cosmetic products into the skin to perform their quality assessment.

Keywords

Dynamic speckle analysis Speckle patterns Activity maps Normalized correlation function Time lag Biological activity 

Notes

Acknowledgements

This work was supported by National Science Fund of Bulgaria (Ministry of Education and Science), Project DH-08/13, “Holographic imaging, beam shaping and speckle metrology with computer generated holograms”, and “The Cross-Ministry Giga Korea Project” Grant funded by the Korea government (Ministry of Science and Information Technology) (No. GK17C0200, Development of full-3D mobile display terminal and its contents).

References

  1. Arizaga, R., Cap, N., Rabal, H., Trivi, M.: Display of the local activity using dynamical speckle patterns. Opt. Eng. 41(2), 287–294 (2002)ADSCrossRefGoogle Scholar
  2. Braga, R., Fabbro, I., Borem, F., Rabelo, G., Arizaga, R., Rabal, H., Trivi, M.: Assessment of seed viability by laser speckle technique. Biosyst. Eng. 86(3), 287–294 (2003)CrossRefGoogle Scholar
  3. Braga, R., Rabelo, G., Granato, L., Santos, E., Machado, J., Arizaga, R., Rabal, H., Trivi, M.: Detection of fungi in beans by the laser biospeckle technique. Biosyst. Eng. 91(4), 465–469 (2005)CrossRefGoogle Scholar
  4. Braga, R., Dupuy, L., Pasqual, M., Cardoso, R.: Live biospeckle laser imaging of root tissues. Eur. Biophys. J. 38, 679–686 (2009)CrossRefGoogle Scholar
  5. Förster, M., Bolzinger, M.A., Ach, D., Montagnac, G., Briançon, S.: Ingredients tracking of cosmetic formulations in the skin: a confocal Raman microscopy investigation. Pharm. Res. 28, 858–865 (2011)CrossRefGoogle Scholar
  6. Goodman, J.: Speckle Phenomena in Optics: Theory and Applications. Roberts and Company Publishers, New York (2007)Google Scholar
  7. Ivanov, B., Stoykova, E., Berberova, N., Nikova, T., Krumov, E., Malinowski, N.: Dynamic speckle technique as a leaf contamination sensor. Bulg. Chem. Commun. 45, 149–153 (2013)Google Scholar
  8. Lyubenova, T., Stoykova, E., Nacheva, E., Ivanov, B., Panchev, I., Sainov, V.: Monitoring of bread cooling by statistical analysis of laser speckle patterns. Proc. SPIE 8770, 87700S (2013)ADSCrossRefGoogle Scholar
  9. Macedo, R., Barreto Filho, J., Braga Jr., R., Rabelo, G.: Sperm motility decreasing and semen fertility in the bull evaluated by biospeckle. Reprod. Fertil. Dev. 22, 170–171 (2009)CrossRefGoogle Scholar
  10. Mulone, C., Budini, N., Vincitorio, F., Freyre, C., López Díaz, A., Ramil Rego, A.: Analysis of strawberry ripening by dynamic speckle measurements. Proc. SPIE 8785, 87851X (2013)ADSCrossRefGoogle Scholar
  11. Murialdo, S., Sendra, G., Passoni, L., Arizaga, R., Gonzalez, J., Rabal, H., Trivi, M.: Analysis of bacterial chemotactic response using dynamic laser speckle. J. Biomed. Opt. 14, 064015 (2009)ADSCrossRefGoogle Scholar
  12. Petry, T., Bury, D., Fautz, R., Hauser, M., Huer, B., Markowetz, A., Mishra, S., Rettinger, K., Schuh, W., Teichert, T.: Review of data on the dermal penetration of mineral oils and waxes used in cosmetic applications. Toxicol. Lett. 280, 70–78 (2017)CrossRefGoogle Scholar
  13. Pot, L.M., Coenraads, P.J., Blömeke, B., Puppels, G.J., Caspers, P.J.: Real-time detection of p-phenylenediamine penetration into human skin by in vivo Raman spectroscopy. Contact Dermat 74(3), 152–158 (2016)CrossRefGoogle Scholar
  14. Rabal, H.J., Braga Jr., R.A. (eds.): Dynamic Laser Speckle and Applications. CRC Press, Boca Raton (2009)MATHGoogle Scholar
  15. Saúde, A., de Menezes, F., Freitas, P., Rabelo, G., Braga Jr., R.: Alternative measures for biospeckle image analysis. J. Opt. Soc. Am. A 29(8), 1648–1658 (2012)ADSCrossRefGoogle Scholar
  16. SCCS: Scientific Committee on Consumer Safety report SCCS/1564/15. The SCCS notes of guidance for the testing of cosmetic substances and their safety evaluation. 9th revision, revised version 25 April 2016. http://ec.europa.eu/health/scientific_committees/consumer_safety/docs/sccs_o_190.pdf (2016). Accessed Dec
  17. Stoykova, E., Roeva, T., Petrova, K., Petrov, T., Minkovsky, N.: Results of the trials and light delivery evaluation at low level laser therapy of acute and chronic pain. Proc. SPIE 5226, 418–422 (2003)ADSCrossRefGoogle Scholar
  18. Stoykova, E., Ivanov, B., Nikova, T.: Correlation-based pointwise processing of dynamic speckle patterns. Opt. Lett. 39(1), 115–118 (2014)ADSCrossRefGoogle Scholar
  19. Stoykova, E., Nazarova, D., Berberova, N., Gotchev, A.: Performance of intensity-based non-normalized pointwise algorithms in dynamic speckle analysis. Opt. Express 23(19), 25128–25142 (2015)ADSCrossRefGoogle Scholar
  20. Stoykova, E., Berberova, N., Kim, Y., Nazarova, D., Ivanov, B., Gotchev, A., Hong, J., Kang, H.: Dynamic speckle analysis with smoothed intensity-based maps. Opt. Laser Eng. 93, 55–65 (2017)CrossRefGoogle Scholar
  21. Xu, Z., Joenathan, C., Khorana, B.: Temporal and spatial properties of the timevarying speckles of botanical specimens. Opt. Eng. 34(5), 1487–1502 (1995)ADSCrossRefGoogle Scholar
  22. Zheng, B., Pleass, C., Ih, C.: Feature information extraction from dynamic biospeckle. Appl. Opt. 33(2), 231–237 (1994)ADSCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Optical Materials and TechnologiesBulgarian Academy of SciencesSofiaBulgaria
  2. 2.VR/AR Research CenterKorea Electronics Technology InstituteSeoulSouth Korea

Personalised recommendations