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Metrology and Measurement Systems

The Journal of Committee on Metrology and Scientific Instrumentation of Polish Academy of Sciences

4 Issues per year


IMPACT FACTOR 2016: 1.598

CiteScore 2016: 1.58

SCImago Journal Rank (SJR) 2016: 0.460
Source Normalized Impact per Paper (SNIP) 2016: 1.228

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2300-1941
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Volume 23, Issue 3 (Sep 2016)

Issues

Evaluation of Perfusion and Thermal Parameters of Skin Tissue Using Cold Provocation and Thermographic Measurements

Maria Strąkowska
  • Lodz University of Technology, Faculty of Electrical, Electronic, Computer and Control Engineering, Wólczańska 211/215, 90-924 Łódź, Poland
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/ Robert Strąkowski
  • Lodz University of Technology, Faculty of Electrical, Electronic, Computer and Control Engineering, Wólczańska 211/215, 90-924 Łódź, Poland
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/ Michał Strzelecki
  • Corresponding author
  • Lodz University of Technology, Faculty of Electrical, Electronic, Computer and Control Engineering, Wólczańska 211/215, 90-924 Łódź, Poland
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/ Gilbert de Mey
  • University of Gent, Department of Electronics and Information Systems, B-9000 Gent, Sint Pieternieuwstraat 41, Belgium
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/ Bogusław Więcek
  • Lodz University of Technology, Faculty of Electrical, Electronic, Computer and Control Engineering, Wólczańska 211/215, 90-924 Łódź, Poland
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Published Online: 2016-07-14 | DOI: https://doi.org/10.1515/mms-2016-0032

Abstract

Measurement of the perfusion coefficient and thermal parameters of skin tissue using dynamic thermography is presented in this paper. A novel approach based on cold provocation and thermal modelling of skin tissue is presented. The measurement was performed on a person’s forearm using a special cooling device equipped with the Peltier module. The proposed method first cools the skin, and then measures the changes of its temperature matching the measurement results with a heat transfer model to estimate the skin perfusion and other thermal parameters. In order to assess correctness of the proposed approach, the uncertainty analysis was performed.

Keywords: active thermovision; perfusion; thermal model; skin tissue; measurement uncertainty

References

  • [1] Pennes, H.H. (1948). Analysis of tissue and arterial blood temperatures in the resting human forearm. Journal of Applied Physiology, 1(2), 93−122.Google Scholar

  • [2] Chen, M.M., Holmes, K.R. (1980). Microvascular Contributions in Tissue Heat Transfer. Annals of the New York Academy of Sciences, 335(1), 137−150.Google Scholar

  • [3] Wulff, W. (1974). The Energy Conservation Equation for Living Tissues. IEEE Transactions-Biomedical Engineering, 21(6), 494−495.Google Scholar

  • [4] Cho, Y.I. (1992). Bioengineering Heat Transfer. Advances in Heat Transfer, Hartnett, J.P., Irvine, T.F. (ed.), Academic Press Inc, San Diego, USA.Google Scholar

  • [5] Weinbaum, S., Jiji, L.M., Lemons, D.E. (1984) Theory and experiment for the effect of vascular microstructure on surface tissue heat transfer. Part I. Anatomical foundation and model conceptualization. ASME Journal of Biomechanical Engineering, 106(4), 321−330.Google Scholar

  • [6] Weinbaum, S., Jiji, L.M. (1985). A new simplified bioheat equation for the effect of blood flow on local average tissue temperature. ASME Journal of Biomechanical Engineering, 107(2), 131−139.Google Scholar

  • [7] Minkowycz, W.J., Sparrow, E.M., Abraham, J.P. (2009). Advances in Numerical Heat Transfer: Vol. 3. CRC Press, Boca Raton, USA.Google Scholar

  • [8] Zolfaghari, A., Maerefat, M. (2010). A New Simplified Thermoregulatory Bioheat Model for Evaluating Thermal Response of the Human Body to Transient Environmen. Building and Environment, 45(10), 2068−2076.Google Scholar

  • [9] Zolfaghari, A., Maerefat, M. (2011). Bioheat transfer. Developments in heat transfer, Dos Santos Bernardes, M.A. (ed.), InTech.Google Scholar

  • [10] Jasiński, M. (2008). Modelling of 1D bioheat transfer with perfusion coefficient dependent on tissue necrosis. ScientificResearch of the Institute of Mathematics and Computer Science, Czestochowa University of Technology, 7(1), 57−62.Google Scholar

  • [11] Khanafer, K., Vafai, K. (2009). Synthesis of mathematical models representing bioheat transport. Advances in Numerical Heat Transfer, CRC Press, New York, Chap. 1, 1−28.Google Scholar

  • [12] Ng, E.Y.K., Tan, H.M., Ooi, E.H. (2009). Boundary element method with bioheat equation for skin burn injury. Burns, 35(7), 987-997.Web of ScienceCrossrefGoogle Scholar

  • [13] Strakowska, M., De Mey, G., Wiecek B., Strzelecki, M. (2015). A three layer model for the thermal impedance of the human skin: modelling and experimental measurements. Journal of Mechanics in Medicine and Biolog, 15(4).Google Scholar

  • [14] Strakowska, M., Strzelecki, M., Kaszuba, A. (2014). Novel methodology of medical screening using IR thermography. SPA 2014. Signal Processing. Algorithms, Architecture, Arrangements, and Applicatiuons. Conference proceedings, 172−175.Google Scholar

  • [15] Strakowska, M., Kaszuba, A., Wiecek, B., Strzelecki, M. De Mey, G. (2015). System and software for thermal images screening in medicine - application to psoriasis. Quantitative InfraRed Thermography, 12(2), 127−136.Google Scholar

  • [16] Nowakowski, A., Kaczmarek, M. (2011). Active Dynamic Thermography − Problems of implementation in medical diagnostics. Quantitative InfraRed Thermography Journal, 8(1), 89−106.Google Scholar

  • [17] Yue, K., Zhang, X., Yu, F. (2004). An Analytic Solution of One-dimensional Steady-state Pennes’ Bioheat Transfer Equation in Cylindrical Coordinates. J. of Thermal Science, 13(3), 255−258.Google Scholar

  • [18] Shih, T.C., Yuan, P., Lin, W.L., Kou, H.S. (2007). Analytical analysis of the Pennes bioheat transfer equation with sinusoidal heat flux condition on skin surface. Medical Engineering & Physics, 29(9), 946-953.Web of ScienceGoogle Scholar

  • [19] Souza, C.F.L., Souza, M.V.C., Colac, M.J., Caldeira, A.B., Scofano Neto, F. (2014). Inverse determination of blood perfusion coefficient by using different deterministic and heuristic techniques. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 36(1), 193−206.Web of ScienceGoogle Scholar

  • [20] Strakowska, M, Strakowski, R., Wiecek, B., Strzelecki, M. (2012). Cross-correlation based movement correction method for biomedical dynamic infrared imaging. Proc. of the 11th International Conference on Quantitative InfraRed Thermography, Naples, Italy.Google Scholar

  • [21] Hooke, R., Jeeves, T.A. (1961). Direct search solution of numerical and statistical problems. Journal of the Association for Computing Machinery (ACM), 8(2), 212-229.Google Scholar

  • [22] Chinneck, J.W. (2009). Practical Optimization: A Gentle Introduction. Carleton University, Canada.Google Scholar

  • [23] Gowrishankar, T.R., Stewart, D.A, Gregory, M.T., Weaver, J.C. (2004). Transport lattice models of heat transport in skin with spatially heterogeneous, temperature-dependent perfusion. Biomedical Engineering Online, 3, 42.CrossrefGoogle Scholar

  • [24] Jiang, S.C., Ma, N., Li, H.J., Zhang, X.X. (2002). Effects of thermal properties and geometrical dimensions on skin burn injuries. Burns, 28(8), 713−717.CrossrefGoogle Scholar

  • [25] Evaluation of measurement data − Guide to the expression of uncertainty in measurement, JCGM 100:2008.Google Scholar

  • [26] Pacholski, K., Wiecek, B. (2015). Practical assessment of accuracy of thermographic indirect measurements. Measurement Automation Monitoring, 61(6), 278−281.Google Scholar

  • [27] Jakubowska, T., Wiecek, B., Wysocki, M., Drews-Peszynski, C., Strzelecki, M. (2004). Classification of breast thermal images using artificial neural networks. Proc. of 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 26, 1155−1158Google Scholar

  • [28] Gill, P. (2013). The critical evaluation of laser Doppler imaging in determining burn depth. International Journal Burns Trauma, 3(2), 72-77.Google Scholar

About the article

Received: 2016-02-07

Accepted: 2016-04-11

Published Online: 2016-07-14

Published in Print: 2016-09-01


Citation Information: Metrology and Measurement Systems, ISSN (Online) 2300-1941, DOI: https://doi.org/10.1515/mms-2016-0032.

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© Polish Academy of Sciences. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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