Modelling Methodology for Physiology and Medicine, Second Edition, offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modeling methodology that is widely applicable to physiology and medicine. The second edition, which is completely updated and expanded, opens with a clear and integrated treatment of advanced methodology for developing mathematical models of physiology and medical systems. Readers are then shown how to apply this methodology beneficially to real-world problems in physiology and medicine, such as circulation and respiration. The focus of Modelling Methodology for Physiology and Medicine, Second Edition, is the methodology that underpins good modeling practice. It builds upon the idea of an integrated methodology for the development and testing of mathematical models. It covers many specific areas of methodology in which important advances have taken place over recent years and illustrates the application of good methodological practice in key areas of physiology and medicine. It builds on work that the editors have carried out over the past 30 years, working in cooperation with leading practitioners in the field. - Builds upon and enhances the reader's existing knowledge of modeling methodology and practice - Editors are internationally renowned leaders in their respective fields - Provides an understanding of modeling methodologies that can address real problems in physiology and medicine and achieve results that are beneficial either in advancing research or in providing solutions to clinical problems

Introduction to Modeling in Physiology and Medicine, Second Edition, develops a clear understanding of the fundamental principles of good modeling methodology. Sections show how to create valid mathematical models that are fit for a range of purposes. These models are supported by detailed explanation, extensive case studies, examples and applications. This updated edition includes clearer guidance on the mathematical prerequisites needed to achieve the maximum benefit from the material, a greater detail regarding basic approaches to modeling, and discussions on non-linear and stochastic modeling. The range of case study material has been substantially extended, with examples drawn from recent research experience. Key examples include a cellular model of insulin secretion and its extension to the whole-body level, a model of insulin action during a meal/oral glucose tolerance test, a large-scale simulation model of type 1 diabetes and its use in in silico clinical trials and drug trials. Covers the underlying principles of good quantitative modeling methodology, with applied biomedical engineering and bioscience examples to ensure relevance to students, current research and clinical practice Includes modeling data, modeling systems, linear and non-linear systems, model identification, parametric and non-parametric models, and model validation Presents clear, step-by-step working plus examples and extensive case studies that relate concepts to real world applications Provides end-of-chapter exercises and assignments to reinforce learning

Control Theory in Biomedical Engineering: Applications in Physiology and Medical Robotics highlights the importance of control theory and feedback control in our lives and explains how this theory is central to future medical developments. Control theory is fundamental for understanding feedback paths in physiological systems (endocrine system, immune system, neurological system) and a concept for building artificial organs. The book is suitable for graduate students and researchers in the control engineering and biomedical engineering fields, and medical students and practitioners seeking to enhance their understanding of physiological processes, medical robotics (legs, hands, knees), and controlling artificial devices (pacemakers, insulin injection devices).Control theory profoundly impacts the everyday lives of a large part of the human population including the disabled and the elderly who use assistive and rehabilitation robots for improving the quality of their lives and increasing their independence. - Gives an overview of state-of-the-art control theory in physiology, emphasizing the importance of this theory in the medical field through concrete examples, e.g., endocrine, immune, and neurological systems - Takes a comprehensive look at advances in medical robotics and rehabilitation devices and presents case studies focusing on their feedback control - Presents the significance of control theory in the pervasiveness of medical robots in surgery, exploration, diagnosis, therapy, and rehabilitation

The Annual Update compiles the most recent developments in experimental and clinical research and practice in one comprehensive reference book. The chapters are written by well recognized experts in the field of intensive care and emergency medicine. It is addressed to everyone involved in internal medicine, anesthesia, surgery, pediatrics, intensive care and emergency medicine.

Personalized Predictive Modeling in Diabetes features state-of-the-art methodologies and algorithmic approaches which have been applied to predictive modeling of glucose concentration, ranging from simple autoregressive models of the CGM time series to multivariate nonlinear regression techniques of machine learning. Developments in the field have been analyzed with respect to: (i) feature set (univariate or multivariate), (ii) regression technique (linear or non-linear), (iii) learning mechanism (batch or sequential), (iv) development and testing procedure and (v) scaling properties. In addition, simulation models of meal-derived glucose absorption and insulin dynamics and kinetics are covered, as an integral part of glucose predictive models. This book will help engineers and clinicians to: select a regression technique which can capture both linear and non-linear dynamics in glucose metabolism in diabetes, and which exhibits good generalization performance under stationary and non-stationary conditions; ensure the scalability of the optimization algorithm (learning mechanism) with respect to the size of the dataset, provided that multiple days of patient monitoring are needed to obtain a reliable predictive model; select a features set which efficiently represents both spatial and temporal dependencies between the input variables and the glucose concentration; select simulation models of subcutaneous insulin absorption and meal absorption; identify an appropriate validation procedure, and identify realistic performance measures. Describes fundamentals of modeling techniques as applied to glucose control Covers model selection process and model validation Offers computer code on a companion website to show implementation of models and algorithms Features the latest developments in the field of diabetes predictive modeling

This book comprehensively addresses the physics and engineering aspects of human physiology by using and building on first-year college physics and mathematics. Topics include the mechanics of the static body and the body in motion, the mechanical properties of the body, muscles in the body, the energetics of body metabolism, fluid flow in the cardiovascular and respiratory systems, the acoustics of sound waves in speaking and hearing, vision and the optics of the eye, the electrical properties of the body, and the basic engineering principles of feedback and control in regulating all aspects of function. The goal of this text is to clearly explain the physics issues concerning the human body, in part by developing and then using simple and subsequently more refined models of the macrophysics of the human body. Many chapters include a brief review of the underlying physics. There are problems at the end of each chapter; solutions to selected problems are also provided. This second edition enhances the treatments of the physics of motion, sports, and diseases and disorders, and integrates discussions of these topics as they appear throughout the book. Also, it briefly addresses physical measurements of and in the body, and offers a broader selection of problems, which, as in the first edition, are geared to a range of student levels. This text is geared to undergraduates interested in physics, medical applications of physics, quantitative physiology, medicine, and biomedical engineering.

Exploring roles critical to environmental toxicology, Modeling and Simulation in Ecotoxicology with Applications in MATLAB and Simulink covers the steps in modeling and simulation from problem conception to validation and simulation analysis. Using the MATLAB and Simulink programming languages, the book presents examples of mathematical functions a

This book comprehensively addresses the physical and engineering aspects of human physiology by using and building on first-year college physics and mathematics. It is the most comprehensive book on the physics of the human body, and the only book also providing theoretical background. The book is geared to undergraduates interested in physics, medical applications of physics, quantitative physiology, medicine, and biomedical engineering.

The elegant ‘interconnected mechanisms’ by which the gastrointestinal (GI) tract regulates food intake are a marvel of biology, but the redundancy (e.g., several hormones seem to have effects in food intake) of both GI (by means of hormones) and central nervous system (CNS, by means of satiety/satiation signals) pathways governing energy homeostasis poses formidable challenges for scientists trying to take a clear glimpse of this machinery, e.g. for designing anti-obesity and alike pharmaceuticals. In essence, notwithstanding the astonishing advancements made over the past few decades in unscrambling many of the molecular pathways involved in energy (homeostasis) regulation, a rather cloudy understanding of “how all the pieces fit together to function as an integrated system” is what can be found for the most part in the scientific community; we discuss that in part II of the work, in a single chapter divided in several sections for numerous imperative hormones, e.g. cholecystokinin. The current work is divided into three parts: part I is regarding fundamentals of physiology and mathematical modeling employed all over the work; part II is more generic and concerns several hormones (what we have called a “web of hormones”) and part III (divided into three chapters) is more specific, concerning a single hormone (i.e., ghrelin). The core of the work is part III, and to a certain extent part II, bearing mind we provide a literature review based on papers scattered/dispersed all over the medical science literature. The main objective of this work is proposing a mathematical model for ghrelin dynamics (Figure 70), a model centered on the gastrointestinal tract (stomach + small intestine, a two-compartment model), with daily-like dynamics, short-term dynamics; and, simultaneously, proposing a prototype for a systems biology like model (igure 40), a model based on numerous hormones, for understanding mathematically food intake/bodyweight control. Ghrelin is a quite powerful orexigenic hormone discovered in the late 1990s that controls appetite and energy homeostasis, alongside leptin and other hormones still to be investigated in depth by the medical sciences literature. Accordingly, we provide a (simple) mathematical model, consisting of a set of ordinary differential equations detailing ghrelin dynamics combined to gastrointestinal signals due to meals. Numerical simulations are able to replicate in silico available data from the literature; additionally, we were able to fit a reduced version of the basal model to experimental data. The model is developed as a module for a bigger potential multi-compartmental structure, detailing food and energy homeostasis within a sort of "a web of hormones" (see part II and the last chapter of part III). The present contribute is to recommend a primary mathematical model for ghrelin dynamics centered in the gastrointestinal tract, with potentiality to be applied also for postabsorptive states, left mainly as future works. We go on with the model by presenting mainly two variations, further unfolding is left as future endeavor: tastants and stochastic version. We test several optimization routines for the parameter estimation procedure, hybrid algorithms (global + local search), for parameter estimation, based on data published for humans (three meals a day). For all the routines, the best is a hybrid composed of simulating annealing as global search and pattern search as local search. In the objective function (sum of the squared errors, SSE), we apply artificial neural networks (a two-layer feedforward neural network) for generating new data from the data already published, a strategy adopted to increase the data set. In the last part of the chapter about ghrelin modeling (part III), we propose several prototypes for future works based on the basal models; the model used for parameter estimation is a “minimal/reduced” model; we also provide discussions and future works for the minimal model and parameter estimation. Key-words. Ghrelin; leptin; mathematical modelling; food intake; appetite; parameter estimation.

Biomedical Information Technology, Second Edition, contains practical, integrated clinical applications for disease detection, diagnosis, surgery, therapy and biomedical knowledge discovery, including the latest advances in the field, such as biomedical sensors, machine intelligence, artificial intelligence, deep learning in medical imaging, neural networks, natural language processing, large-scale histopathological image analysis, virtual, augmented and mixed reality, neural interfaces, and data analytics and behavioral informatics in modern medicine. The enormous growth in the field of biotechnology necessitates the utilization of information technology for the management, flow and organization of data. All biomedical professionals can benefit from a greater understanding of how data can be efficiently managed and utilized through data compression, modeling, processing, registration, visualization, communication and large-scale biological computing. - Presents the world's most recognized authorities who give their "best practices" - Provides professionals with the most up-to-date and mission critical tools to evaluate the latest advances in the field - Gives new staff the technological fundamentals and updates experienced professionals with the latest practical integrated clinical applications