Physiological Systems Modeling, Simulation, and Control

Physiological systems modeling, simulation, and control is a research area integrating science and engineering and contributes to a continuous refinement of knowledge on how the body works. The roots of modeling a body area date back thousands of years, yet it was not until the 1950s that the tree of knowledge started to be fed with data-driven hypotheses and interventions. This chapter tries to organize disparate information of the most important modeling, simulation, and control perspectives into a coherent set of views currently applied to modern biological and medical research. It is addressed to researchers on human system physiological modeling, working both in academia and in industry to address current and future research goals.

[1]  D. T. Kaplan,et al.  Aging and the complexity of cardiovascular dynamics. , 1991, Biophysical journal.

[2]  R. P. Noble,et al.  Turnover of plasma cholesterol in man. , 1968, The Journal of clinical investigation.

[3]  A V Holden,et al.  Reentrant waves and their elimination in a model of mammalian ventricular tissue. , 1998, Chaos.

[4]  A Krogh,et al.  The number and distribution of capillaries in muscles with calculations of the oxygen pressure head necessary for supplying the tissue , 1919, The Journal of physiology.

[5]  D. Noble,et al.  Rectifying Properties of Heart Muscle , 1960, Nature.

[6]  Yung E Earm,et al.  A mathematical model of pacemaker activity recorded from mouse small intestine , 2006, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[7]  Peter Brown,et al.  Oscillations in the Basal Ganglia: The good, the bad, and the unexpected , 2005 .

[8]  J. Longrigg Presocratic Philosophy and Hippocratic Medicine , 1989, History of science; an annual review of literature, research and teaching.

[9]  Konstantina S. Nikita,et al.  Can we infer subthalamic nucleus spike trains from intranuclear local field potentials? , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[10]  Nicholas T. Carnevale,et al.  The NEURON Simulation Environment , 1997, Neural Computation.

[11]  A. Hodgkin,et al.  A quantitative description of membrane current and its application to conduction and excitation in nerve , 1952, The Journal of physiology.

[12]  D. Furley,et al.  Galen: On Respiration and the Arteries , 1984 .

[13]  G. Stewart,et al.  Researches on the Circulation Time and on the Influences which affect it , 1897, The Journal of physiology.

[14]  Bernhard O. Palsson,et al.  BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions , 2010, BMC Bioinformatics.

[15]  Robert E. Hampson,et al.  Nonlinear Dynamic Modeling of Spike Train Transformations for Hippocampal-Cortical Prostheses , 2007, IEEE Transactions on Biomedical Engineering.

[16]  John Enderle 12 – PHYSIOLOGICAL MODELING , 2005 .

[17]  D. Noble Cardiac Action and Pacemaker Potentials based on the Hodgkin-Huxley Equations , 1960, Nature.

[18]  G. W. Beeler,et al.  Reconstruction of the action potential of ventricular myocardial fibres , 1977, The Journal of physiology.

[19]  Teresa Ree Chay,et al.  Chaos in a three-variable model of an excitable cell , 1985 .

[20]  Miguel A. L. Nicolelis,et al.  Brain–machine interfaces: past, present and future , 2006, Trends in Neurosciences.

[21]  Ronald J. Williams,et al.  A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.

[22]  Jaimie M. Henderson,et al.  The STN beta-band profile in Parkinson's disease is stationary and shows prolonged attenuation after deep brain stimulation , 2009, Experimental Neurology.

[23]  D. Noble Modeling the Heart--from Genes to Cells to the Whole Organ , 2002, Science.

[24]  Ying Wang,et al.  Independent Effect of Visceral Adipose Tissue on Metabolic Syndrome in Obese Adolescents , 2008, Hormone Research in Paediatrics.

[25]  Hermano Igo Krebs,et al.  Therapeutic Robotics: A Technology Push , 2006, Proceedings of the IEEE.

[26]  Peter Brown,et al.  Basal ganglia local field potential activity: Character and functional significance in the human , 2005, Clinical Neurophysiology.

[27]  K. Nikita,et al.  An Insulin Infusion Advisory System for Type 1 Diabetes Patients based on Non-Linear Model Predictive Control Methods , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.