Abstract
Diabetes mellitus is a disease that may cause dysfunctions in the sympathetic and parasympathetic nervous system. Therefore, the pupillary reflex of diabetic patients shows characteristics that distinguish them from healthy people, such as pupil radius and contraction time. These features can be measured by the noninvasive way of dynamic pupillometry, and an analysis of the data can be used to check the existence of a neuropathy. In this paper, it is proposed the use of artificial neural networks for helping screening the diabetes occurrence through the dynamic characteristics of the pupil, with successful results.
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References
Mandrup-Poulsen, T.: Recent advances – diabetes. Brit. Med. J. 316, 1221–1225 (1998)
Widman, S., Ladner, E., Lottenberg, S.: Diabetes. Senac, São Paulo (1989)
Pittasch, D., Lobmann, R., Behrens-Baumann, W., Lehnert, H.: Pupil signs of sympathetic autonomic neuropathy in patients with type 1 diabetes. Diabetes Care 25, 1545–1550 (2002)
Fotiou, F., Fountoulakis, K.N., Goulas, A., Alexopoulos, L., Palikaras, A.: Automated standardized pupillometry with optical method for purposes of clinical practice and research. Clin. Physiol. 20, 336–347 (2000)
Dütsch, M., Marthol, H., Michelson, G., Neundörfer, N., Hilz, M.J.: Pupillography refines the diagnosis of diabetic autonomic neuropathy. J. Neurol. Sci. 222, 75–81 (2004)
Cahill, M., Eustace, P., Jesus, V.: Pupillary autonomic denervation with increasing duration of diabetes mellitus. Brit. J. Ophthalmol. 85, 1225–1230 (2001)
Ferrari, G.L., Marques, J.L.B., Gandhi, R.A., Heller, S., Schneider, F.K., Tesfaye, S., Gamba, H.R.: Using dynamic pupillometry as a simple screening tool to detect autonomic neuropathy in patients with diabetes: a pilot study. Biomed. Eng. Online 9, 26–41 (2010)
Haykin, S.: Neural Networks and Learning Machines. Prentice Hall, Upper Saddle River (2009)
Yano, V., Zimmer, A., Ferrari, G.L.: Análise da Variação do Reflexo Pupilar entre Pacientes Diabéticos para Aplicação em Sistema Biométrico. In: XXII Congresso Brasileiro de Engenharia Biomédica, UFSJ (2010)
Weiqi, Y., Lu, X., Zhonghua, L.: A Novel Iris Localization Algorithm Based on the Gray Distributions of Eye Images. In: 27th IEEE Annual International Conference of the Engineering in Medicine and Biology Society, pp. 6504–6507. IEEE Press, Shanghai (2005)
Weisstein, E.W.: Levenberg-Marquardt Method (2010), http://mathworld.wolfram.com/Levenberg-MarquardtMethod.html
Maffra, F.A., Gattass, M.: Método de Levenberg-Marquardt. PUC-Rio, Rio de Janeiro (2008)
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Yano, V., Ferrari, G., Zimmer, A. (2011). Using the Pupillary Reflex as a Diabetes Occurrence Screening Aid Tool through Neural Networks. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21596-4_5
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DOI: https://doi.org/10.1007/978-3-642-21596-4_5
Publisher Name: Springer, Berlin, Heidelberg
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