Skip to main content
Log in

Abstract

Mathematical simulations are of increasing relevance for applications in engineering and the life sciences. Disciplines like epidemiology, biomechanics, medical image processing, just to name a few, are subject of academic research since decades. With modern numerical methods and the advent of increasing computing power not just simulations of biological systems are within reach, but also questions of optimizing the systems to aim at a certain goal can be addressed. In this paper, we will discuss some examples from epidemiology as well as biomechanical models for muscles. All these models are based on a set of differential equations. Defining a suitable cost functional to measure the distance to the goal of our optimization, mathematical tools from constrained optimization can be applied to solve optimization problems and to derive suitable numerical algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Tröltzsch, F.: Optimale Steuerung partieller Differentialgleichungen, 311 pp. Vieweg + Teubner, Wiesbaden (2009)

  2. Aldila, D., Götz, T., Soewono, E.: An optimal control problem arising from a dengue disease transmission model. Math. Biosci. 242(1), 9–16 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  3. Wijaya, K.P., Götz, T., Soewono, E.: An optimal control model of mosquito reduction management in a dengue endemic region. Int. J. Biomath. 7(5), 1450,056 (2014). doi:10.1142/S1793524514500569

  4. Rockenfeller, R., Goetz, T.: Optimal control of isometric muscle dynamics. J. Math. Fundam. Sci. 47(1), 12–30 (2015). doi:10.5614/j.math.fund.sci.2015.47.1.2

  5. Hinze, M., Pinnau, R., Ulbrich, S.: Optimization with PDE Cconstraints, Mathematical Modelling: Theory and Application, vol. 23. Springer-Verlag, New York (2009)

    Google Scholar 

  6. Bailey, N.: The mathematical theory of infectious diseases and its applications, 2nd Edition. Charles Griffin & Company Ltd (1975)

  7. Dietz, K.: Transmission and control of arbovirus diseases. In: Ludwig, D., Cooke, K.L. (eds.) Epidemiology, pp. 104–121. SIAM, Philadelphia (1975)

  8. Wijaya, K.P., Götz, T., Soewono, E.: Advances in mosquito dynamics modeling. Arxiv 1503, 02573 (2015)

    Google Scholar 

  9. Bauer, S., Gruber, K., Kilian, F.: 3d-computermodell der menschlichen lendenwirbelsäule—entwicklung und anwendungsmöglichkeiten in der medizin. Biomedizinische Technik, Gemeinsame Jahrestagung der Deutschen. Österreichi. de Gruyter, Rostock (2010)

    Google Scholar 

  10. Grujicic, M., Pandurangan, B., Xie, X., Gramopadhye, A., Wagner, D., Ozen, M.: Musculoskeletal computational analysis of the influence of car-seat design/adjustments on long-distance driving fatigue. Int. J. Ind. Ergon. 40(3), 345–355 (2010). doi:10.1016/j.ergon.2010.01.002 http://www.sciencedirect.com/science/article/pii/S016981411000003X

  11. Seyfarth, A., Grimmer, S., Häufle, D.F.B., Kalveram, K.T.: Can robots help to understand human locomotion? Automatisierungstechnik 60(11), 653–661 (2012). URL http://dblp.uni-trier.de/db/journals/at/at60.htmlSeyfarthGHK12

  12. Keppler, V.: Biomechanische modellbildung zur simulation zweier mensch-maschinen-schnittstellen. Ph.D. thesis, Eberhard-Karls-Universität zu Tübingen, Fakultät für Mathematik und Physik (2003)

  13. Hill, A.V.: The heat of shortening and the dynamic constants of muscle. Proc. R. Soc. Lond. B 126, 136–195 (1938)

    Article  Google Scholar 

  14. Günther, M., Schmitt, S., Wank, V.: High-frequency oscillations as a consequence of neglected serial damping in Hill-type muscle models. Biol. Cybern. 1(97), 63–79 (2007)

    Article  Google Scholar 

  15. Haeufle, D., Günther, M., Bayer, A., Schmitt, S.: Hill-type muscle model with serial damping and eccentric force–velocity relation. J. Biomech. 47(6), 1531–1536 (2014)

    Article  Google Scholar 

  16. Hatze, H.: A myocybernetic control model of skeletal muscle. Biol. Cybern. 25(2), 103–119 (1977)

    Article  MATH  Google Scholar 

  17. Wank, V.: Muscle growth and fiber type composition in hind limb muscles during postnatal development in pigs. Cells Tissues Organs 182, 171–181 (2006)

    Article  Google Scholar 

  18. Hawkins, D., Hull, M.L.: Muscle forces as affected by fatigue: mathematical model and experimental verification. J. Biomech. 26(9), 1117–1128 (1993)

    Article  MATH  Google Scholar 

  19. Zajac, F.E.: Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit. Rev. Biomed. Eng. 17(4), 359–411 (1989)

    Google Scholar 

Download references

Acknowledgments

Karunia Putra Wijaya has been financially supported by Indonesia Endowment Fund for Education (LPDP)

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Götz.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Götz, T., Rockenfeller, R. & Wijaya, K.P. Optimization problems in epidemiology, biomechanics & medicine. Int J Adv Eng Sci Appl Math 7, 25–32 (2015). https://doi.org/10.1007/s12572-015-0130-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12572-015-0130-5

Keywords

Navigation