Page 48 - Control Theory in Biomedical Engineering

Modeling and control in physiology 35

Alvarez-Arenas, A., Starkov, K., Calvo, G., 2019. Ultimate dynamics and optimal control of
a multi-compartment model of tumor resistance to chemotherapy. Discrete Continuous
Dyn. Syst. Ser. B 24 (5), 2017–2038.
Ambrosi, D., Quarteroni, A., Rozza, G., 2012. Modeling of Physiological Flows, Modeling,
Simulation and Applications. Springer Science & Business Media.
Anderson, D., 2013. Compartmental Modeling and Tracer Kinetics. Springer Science &
Business Media.
Anderson, A., Quaranta, V., 2008. Integrative mathematical oncology. Nat. Rev. Cancer
8 (3), 277.
Aon, M.A., Cortassa, S., Lloyd, D., 2011. Chaos in biochemistry and physiology.
In: Encyclopedia of Molecular Cell Biology and Molecular Medicine. Wiley-VCH Ver-
lag GmbH & Co. KGaA, Weinheim, Germany.
Aram, Z., et al., 2017. Using chaotic artificial neural networks to model memory in the brain.
Commun. Nonlinear Sci. Numer. Simul. 44, 449–459.
Arjun, A., Saharan, L., Tadesse, Y., 2016. Design of a 3D printed hand prosthesis actuated by
nylon 6-6 polymer based artificial muscles. In: 2016 IEEE International Conference on
Automation Science and Engineering (CASE). IEEE, pp. 910–915.
Badawi, H.F., El Saddik, A., 2020. Biofeedback in healthcare: State of the art and meta
review. In: Connected Health in Smart Cities. Springer International Publishing,
Cham, pp. 113–142.
Baghdadi, G., et al., 2015. A chaotic model of sustaining attention problem in attention def-
icit disorder. Commun. Nonlinear Sci. Numer. Simul. 20 (1), 174–185.
Balakrishnan, N.P., Rangaiah, G.P., Samavedham, L., 2011. Review and analysis of blood
glucose (BG) models for type 1 diabetic patients. Ind. Eng. Chem. Res. 50 (21),
12041–12066.
Banks, H., 2013. Modeling and Control in the Biomedical Sciences. Springer Science &
Business Media.
Baxt, W.G., 1994. Complexity, chaos and human physiology: the justification for non-linear
neural computational analysis. Cancer Lett. 77 (2–3), 85–93.
Bayani, A., et al., 2018. A chaotic model of migraine headache considering the dynamical
transitions of this cyclic disease. EPL 123 (1), 10006.
Bekey, G., Beneken, J., 1978. Identification of biological systems: a survey. Automatica
14 (1), 41–47.
Bell, G.I., 1973. Predator-prey equations simulating an immune response. Math. Biosci.
16 (3–4), 291–314.
˚
Bellman, R., Astr€om, K.J., 1970. On structural identifiability. Math. Biosci. 7 (3–4), 329–339.
Bellu, G., et al., 2007. DAISY: A new software tool to test global identifiability of biological
and physiological systems. Comput. Methods Prog. Biomed. 88 (1), 52–61.
Ben Saad, A., Boubaker, O., Elhadj, Z., 2019. PD bifurcation and chaos behavior in a
predator-prey model with Allee effect and seasonal perturbation. In: Recent Advances
in Chaotic Systems and Synchronization. Academic Press, pp. 211–232. https://doi.org/
10.1016/B978-0-12-815838-8.00011-X.
Benzinger, T.H., 1969. Heat regulation: homeostasis of central temperature in man. Physiol.
Rev. 49 (4), 671–759.
Bergman, R.N., et al., 1979. Quantitative estimation of insulin sensitivity. Am. J. Physiol.
Endocrinol. Metab. 236 (6), E667.
Berntson, G.G., Cacioppo, J.T., Bosch, J.A., 2016. From homeostasis to allodynamic regu-
lation. In: Handbook of Psychophysiology. Cambridge University Press, pp. 401–426.
Bertram, R., 2011. Mathematical modeling in neuroendocrinology. Compr. Physiol. 5 (2),
911–927.
Bessonov, N., et al., 2016. Methods of blood flow modelling. Math. Model. Nat. Phenom.
Edited by V. Volpert. vol. 11(1), 1–25.