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Neural Network and Physiological Parameters Based Control of Artificial Pancreas for Improved Patient Safety

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Computational Science and Its Applications – ICCSA 2012 (ICCSA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7335))

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Abstract

Acyber-physical system (CPS) establishes a close interaction between system’s computational core and the control of physical process. In case of Diabetes, failure in endogenous insulin production requires exogenous infusion of required drug amount. We have proposed an architecture for artificial pancreas and checked its validity in simulations. The aim is to control blood glucose level (BGL) of a patient suffering from diabetes and to prevent the harmful state of Hypoglycemia. For this, vital signs monitoring is introduced through which hypoglycemic condition can be efficiently detected and avoided. Electrocardiogram, Heart beat rate, Electroencephalography and skin resistance are known to depict an irregularity in blood glucose. Upon detection, a specified amount of Glucagon is infused into patient’s body. The system consists of an insulin infusion and glucagon pump, through which insulin/glucagon is entered into the patient’s body subcutaneously, based on the current BGL. A neural network predictive controller is designed to keep the glucose level inside the desired ’safe range’. The simulations have shown that patient safety can be improved through this strategy.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National University of Sciences and Technology, Islamabad, Pakistan

    Saad Bin Qaisar, Salman H. Khan & Sahar Imtiaz

Authors
  1. Saad Bin Qaisar
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  2. Salman H. Khan
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  3. Sahar Imtiaz
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Editor information

Editors and Affiliations

  1. Laboratory of Urban and Territorial Systems, University of Basilicata, 10, Viale dell’Ateneo Lucano, 85100, Potenza, Italy

    Beniamino Murgante

  2. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli 1, 06123, Perugia, Italy

    Osvaldo Gervasi

  3. Department of Cyber Security Science, Federal University of Technology, Gidan Kwano Campus, Minna, Nigeria

    Sanjay Misra

  4. Faculty of Engineering, Department of Electronics Engineering and Telecommunications, State University of Rio de Janeiro, Rua Sao Francisco Xavier, 524, 50. andar, sala 5145-F, Maracana, 20.550-013, Rio de Janeiro, RJ, Brazil

    Nadia Nedjah

  5. Department of Production and Systems, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal

    Ana Maria A. C. Rocha

  6. School of Business Systems, Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  7. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, Higashi-ku, 813-8503, Fukuoka, Japan

    Bernady O. Apduhan

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© 2012 Springer-Verlag Berlin Heidelberg

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Qaisar, S.B., Khan, S.H., Imtiaz, S. (2012). Neural Network and Physiological Parameters Based Control of Artificial Pancreas for Improved Patient Safety. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31137-6_26

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  • DOI: https://doi.org/10.1007/978-3-642-31137-6_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31136-9

  • Online ISBN: 978-3-642-31137-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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