35-04 : Modélisation des systèmes physiologiques

35-01 Génie biomédical général
35-02 Instrumentation biomédicale
35-03 Traitement d'images médicales
35-05 Biophysique
35-06 Biomatériaux
35-07 Biomécanique
35-08 Génie de la réhabilitation
35-09 Informatique biomédicale
35-10 Capteurs et mesures biomédicaux
35-11 Traitement des biosignaux

Ouvrages de la bibliothèque en indexation 35-04

Computational Models for the Human Body Vol. XII / N. Ayache

Public ISBD Titre : Computational Models for the Human Body Vol. XII : special volume Type de document : texte imprimé Auteurs : N. Ayache, Auteur Editeur : Amsterdam,Boston,Heidelberg... : Elsevier Année de publication : 2004 Collection : Handbook of Numerical Analysis Importance : 670 p. Présentation : couv. ill.,ill. Format : 24,5 cm. ISBN/ISSN/EAN : 978-0-444-51566-7 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Provides a better understanding of the physiological and mechanical behaviour of the human body and the design of tools for their realistic numerical simulations, including concrete examples of such computational models. This book covers a large range of methods and an illustrative set of applications. Note de contenu : Contents of Volume XII Special volume : computational models for the human body General preface Foreword -Mathematical modelling and numerical simulation of the cardiovascular system -Computational methods for cardiac electrophysiology -Mathematical analysis, controllability and numerical simulation of a simple model of avascular tumor growth -Human models for crash and impact simulation -Soft Tissue Modeling for Surgery Simulation -Recovering Displacements and Deformations from 3D Medical Images -Using biomechanical models -Methods for Modeling and Predicting Mechanical Deformations of the breast under external perturbations Computational Models for the Human Body Vol. XII : special volume [texte imprimé] / N. Ayache, Auteur . - Amsterdam,Boston,Heidelberg... : Elsevier, 2004 . - 670 p. : couv. ill.,ill. ; 24,5 cm.. - (Handbook of Numerical Analysis) . ISBN : 978-0-444-51566-7 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Provides a better understanding of the physiological and mechanical behaviour of the human body and the design of tools for their realistic numerical simulations, including concrete examples of such computational models. This book covers a large range of methods and an illustrative set of applications. Note de contenu : Contents of Volume XII Special volume : computational models for the human body General preface Foreword -Mathematical modelling and numerical simulation of the cardiovascular system -Computational methods for cardiac electrophysiology -Mathematical analysis, controllability and numerical simulation of a simple model of avascular tumor growth -Human models for crash and impact simulation -Soft Tissue Modeling for Surgery Simulation -Recovering Displacements and Deformations from 3D Medical Images -Using biomechanical models -Methods for Modeling and Predicting Mechanical Deformations of the breast under external perturbations

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
2577	35-04-01	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	2577

Introduction to Modeling in Physiology and MedicineC / Claudio Cobelli

Public ISBD Titre : Introduction to Modeling in Physiology and MedicineC Type de document : texte imprimé Auteurs : Claudio Cobelli, Auteur ; Ewart Carson, Auteur Editeur : Amsterdam,Boston,Heidelberg... : Elsevier Academic Press Année de publication : 2008 Collection : Academic Press Series in Biomedical Engineering Importance : 324 p. Présentation : couv. ill. en coul., ill. Format : 24,8 cm. ISBN/ISSN/EAN : 978-0-12-160240-6 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : This unified modeling textbook for students of biomedical engineering provides a complete course text on the foundations, theory and practice of modeling and simulation in physiology and medicine. It is dedicated to the needs of biomedical engineering and clinical students, supported by applied BME applications and examples. • Developed for biomedical engineering and related courses: speaks to BME students at a level and in a language appropriate to their needs, with an interdisciplinary clinical/engineering approach, quantitative basis, and many applied examples to enhance learning • Delivers a quantitative approach to modeling and also covers simulation: the perfect foundation text for studies across BME and medicine • Extensive case studies and engineering applications from BME, plus end-of-chapter exercises and a separate Instructor’s manual Note de contenu : CONTENTS CHAPTER 1 INTRODUCTION CHAPTER 2 PHYSIOLOGICAL COMPLEXITY AND THE NEED FOR MODELS 2.2 Complexity 2.3 Feedback 2.4 Control in Physiological Systems 2.5 Hierarchy 2.6 Redundancy 2.7 Function and Behavior and their Measurement 2.8 Challenges to Understanding CHAPTER 3 MODELS AND THE MODELING PROCESS 3.5 Model Formulation 3.6 Model Identification 3.7 Model Validation 3.8 Model Simulation CHAPTER 4 MODELING THE DATA 4.2 The Basis of Data Modeling 4.3 The Why and When of Data Models 4.4 Approaches to Data Modeling 4.5 Modeling a Single Variable Occurring Spontaneously 4.6 Modeling a Single Variable in Response to a Perturbation 4.7 Two Variables Causally Related 4.8 Input/output Modeling for Control 4.9 Input/output Modeling: Impulse Response and Deconvolution CHAPTER 5 MODELING THE SYSTEM 5.2 Static Models 5.3 Linear Modeling 5.4 Distributed Modeling 5.5 Nonlinear Modeling 5.6 Time-varying Modeling 5.7 Stochastic Modeling CHAPTER 6 MODEL IDENTIFICATION 6.2 Data for Identification 6.3 Errors 6.4 The Way Forward CHAPTER 7 PARAMETRIC MODELING – THE IDENTIFIABILITY PROBLEM 7.4 Linear Models: The Transfer Function Method 7.5 Nonlinear Models: The Taylor Series Expansion Method 7.6 Qualitative Experimental Design CHAPTER 8 PARAMETRIC MODELS – THE ESTIMATION PROBLEM 8.2 Linear and Nonlinear Parameters 8.3 Regression: Basic Concepts 8.4 Linear Regression 8.5 Nonlinear Regression 8.6 Tests for Model Order 8.7 Maximum Likelihood Estimation 8.8 Bayesian Estimation 8.9 Optimal Experimental Design CHAPTER 9 NON-PARAMETRIC MODELS – SIGNAL ESTIMATION 9.2 Why is Deconvolution Important? 9.3 The Problem 9.4 Difficulty of the Deconvolution Problem 9.5 The Regularization Method CHAPTER 10 MODEL VALIDATION 10.3 Validation Strategies 10.4 Good Practice in Good Modeling CHAPTER 11 CASE STUDIES 11.1 Case Study 1: A Sum of Exponentials Tracer Disappearance Model 11.2 Case Study 2: Blood Flow Modeling 11.3 Case Study 3: Cerebral Glucose Modeling 11.4 Case Study 4: Models of the Ligand-Receptor System 11.5 Case Study 5: A Simulation Model of the Glucose-Insulin System 11.5.1 Model Formulation 11.5.2 Results 11.6 Case Study 6: A Model of Insulin Control 11.7 Case Study 7: Illustrations of Bayesian Estimation INDEX Introduction to Modeling in Physiology and MedicineC [texte imprimé] / Claudio Cobelli, Auteur ; Ewart Carson, Auteur . - Amsterdam,Boston,Heidelberg... : Elsevier Academic Press, 2008 . - 324 p. : couv. ill. en coul., ill. ; 24,8 cm.. - (Academic Press Series in Biomedical Engineering) . ISBN : 978-0-12-160240-6 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : This unified modeling textbook for students of biomedical engineering provides a complete course text on the foundations, theory and practice of modeling and simulation in physiology and medicine. It is dedicated to the needs of biomedical engineering and clinical students, supported by applied BME applications and examples. • Developed for biomedical engineering and related courses: speaks to BME students at a level and in a language appropriate to their needs, with an interdisciplinary clinical/engineering approach, quantitative basis, and many applied examples to enhance learning • Delivers a quantitative approach to modeling and also covers simulation: the perfect foundation text for studies across BME and medicine • Extensive case studies and engineering applications from BME, plus end-of-chapter exercises and a separate Instructor’s manual Note de contenu : CONTENTS CHAPTER 1 INTRODUCTION CHAPTER 2 PHYSIOLOGICAL COMPLEXITY AND THE NEED FOR MODELS 2.2 Complexity 2.3 Feedback 2.4 Control in Physiological Systems 2.5 Hierarchy 2.6 Redundancy 2.7 Function and Behavior and their Measurement 2.8 Challenges to Understanding CHAPTER 3 MODELS AND THE MODELING PROCESS 3.5 Model Formulation 3.6 Model Identification 3.7 Model Validation 3.8 Model Simulation CHAPTER 4 MODELING THE DATA 4.2 The Basis of Data Modeling 4.3 The Why and When of Data Models 4.4 Approaches to Data Modeling 4.5 Modeling a Single Variable Occurring Spontaneously 4.6 Modeling a Single Variable in Response to a Perturbation 4.7 Two Variables Causally Related 4.8 Input/output Modeling for Control 4.9 Input/output Modeling: Impulse Response and Deconvolution CHAPTER 5 MODELING THE SYSTEM 5.2 Static Models 5.3 Linear Modeling 5.4 Distributed Modeling 5.5 Nonlinear Modeling 5.6 Time-varying Modeling 5.7 Stochastic Modeling CHAPTER 6 MODEL IDENTIFICATION 6.2 Data for Identification 6.3 Errors 6.4 The Way Forward CHAPTER 7 PARAMETRIC MODELING – THE IDENTIFIABILITY PROBLEM 7.4 Linear Models: The Transfer Function Method 7.5 Nonlinear Models: The Taylor Series Expansion Method 7.6 Qualitative Experimental Design CHAPTER 8 PARAMETRIC MODELS – THE ESTIMATION PROBLEM 8.2 Linear and Nonlinear Parameters 8.3 Regression: Basic Concepts 8.4 Linear Regression 8.5 Nonlinear Regression 8.6 Tests for Model Order 8.7 Maximum Likelihood Estimation 8.8 Bayesian Estimation 8.9 Optimal Experimental Design CHAPTER 9 NON-PARAMETRIC MODELS – SIGNAL ESTIMATION 9.2 Why is Deconvolution Important? 9.3 The Problem 9.4 Difficulty of the Deconvolution Problem 9.5 The Regularization Method CHAPTER 10 MODEL VALIDATION 10.3 Validation Strategies 10.4 Good Practice in Good Modeling CHAPTER 11 CASE STUDIES 11.1 Case Study 1: A Sum of Exponentials Tracer Disappearance Model 11.2 Case Study 2: Blood Flow Modeling 11.3 Case Study 3: Cerebral Glucose Modeling 11.4 Case Study 4: Models of the Ligand-Receptor System 11.5 Case Study 5: A Simulation Model of the Glucose-Insulin System 11.5.1 Model Formulation 11.5.2 Results 11.6 Case Study 6: A Model of Insulin Control 11.7 Case Study 7: Illustrations of Bayesian Estimation INDEX

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
2567	35-04-04	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	2567
2568	35-04-04	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	2568

Modelling and Control in Biomedical Systems 2006 / David Dagan Feng

Public ISBD Titre : Modelling and Control in Biomedical Systems 2006 : including biological systems; a proceedings volume from the 6th IFAC symposium, Reims, France 20-22 Septembre 2006 Type de document : texte imprimé Auteurs : David Dagan Feng, Auteur ; Olivier Dubois, Auteur ; Janan Zaytoon, Auteur Editeur : Kidlington, Oxford, USA : Elsevier Année de publication : 2006 Importance : 563 p. Présentation : ill. Format : 29,8 cm. ISBN/ISSN/EAN : 978-0-08-044530-4 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Modelling and Control in Biomedical Systems (including Biological Systems) was held in Reims, France, 20-22 August 2006. This Symposium was organised by the University of Reims Champagne Ardenne and the Société de l’Electricité, de l’Electronique et des TIC (SEE). The Symposium attracted practitioners in engineering, information technology, mathematics, medicine and biology, and other related disciplines, with authors from 24 countries. Besides the abstracts of the four plenary lectures, this volume contains the 92 papers that were presented by their authors at the Symposium. The papers included two invited keynote presentations given by internationally prominent and well-recognised research leaders: Claudio Cobelli, whose talk is titled "Dynamic modelling in diabetes: from whole body to genes"; and Irving J. Bigio, whose talk is titled "Elastic scattering spectroscopy for non-invasive detection of cancer". Two prestigious industrial speakers were also invited to give keynote presentations: Terry O'Brien from LIDCO, whose talk is titled "LIDCO: From the laboratory to protocolized goal directed therapy"; and Lorenzo Quinzio of Philips, whose talk is titled "Clinical decision support in monitoring and information systems". A valuable source of information on the state-of- the-art in Modelling and Control in Biomedical Systems Including abstracts of four plenary lectures, and 92 papers presented by their authors Note de contenu : Contents CONTENTS PART I: KEYNOTE PAPERS PART II: OPTICAL METHODS FOR IN-VIVO DIAGNOSIS / CLINICAL DIAGNOSIS BY IMAGE PROCESSING PART III: IDENTIFICATION AND SIGNAL PROCESSING IN BIOMEDICAL SYSTEMS PART IV: BIOMEDICAL FUNCTIONAL IMAGING PART V: BIOMEDICAL SYSTEM CONTROL PART VI: MODELLING, PHYSIOLOGICAL SYSTEMS, BIOINFORMATICS AND HEATH CARE Modelling and Control in Biomedical Systems 2006 : including biological systems; a proceedings volume from the 6th IFAC symposium, Reims, France 20-22 Septembre 2006 [texte imprimé] / David Dagan Feng, Auteur ; Olivier Dubois, Auteur ; Janan Zaytoon, Auteur . - Kidlington, Oxford, USA : Elsevier, 2006 . - 563 p. : ill. ; 29,8 cm. ISBN : 978-0-08-044530-4 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Modelling and Control in Biomedical Systems (including Biological Systems) was held in Reims, France, 20-22 August 2006. This Symposium was organised by the University of Reims Champagne Ardenne and the Société de l’Electricité, de l’Electronique et des TIC (SEE). The Symposium attracted practitioners in engineering, information technology, mathematics, medicine and biology, and other related disciplines, with authors from 24 countries. Besides the abstracts of the four plenary lectures, this volume contains the 92 papers that were presented by their authors at the Symposium. The papers included two invited keynote presentations given by internationally prominent and well-recognised research leaders: Claudio Cobelli, whose talk is titled "Dynamic modelling in diabetes: from whole body to genes"; and Irving J. Bigio, whose talk is titled "Elastic scattering spectroscopy for non-invasive detection of cancer". Two prestigious industrial speakers were also invited to give keynote presentations: Terry O'Brien from LIDCO, whose talk is titled "LIDCO: From the laboratory to protocolized goal directed therapy"; and Lorenzo Quinzio of Philips, whose talk is titled "Clinical decision support in monitoring and information systems". A valuable source of information on the state-of- the-art in Modelling and Control in Biomedical Systems Including abstracts of four plenary lectures, and 92 papers presented by their authors Note de contenu : Contents CONTENTS PART I: KEYNOTE PAPERS PART II: OPTICAL METHODS FOR IN-VIVO DIAGNOSIS / CLINICAL DIAGNOSIS BY IMAGE PROCESSING PART III: IDENTIFICATION AND SIGNAL PROCESSING IN BIOMEDICAL SYSTEMS PART IV: BIOMEDICAL FUNCTIONAL IMAGING PART V: BIOMEDICAL SYSTEM CONTROL PART VI: MODELLING, PHYSIOLOGICAL SYSTEMS, BIOINFORMATICS AND HEATH CARE

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
2571	35-04-02	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	2571
2572	35-04-02	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	2572

Modelling methodology for physiology and medicine / Ewart Carson

Public ISBD Titre : Modelling methodology for physiology and medicine Type de document : texte imprimé Auteurs : Ewart Carson, Auteur ; Claudio Cobelli, Auteur Editeur : Amsterdam,Boston,Heidelberg... : Elsevier Academic Press Année de publication : 2001 Collection : Academic Press Series in Biomedical Engineering Importance : 421 p. Présentation : couv. ill. en coul., ill. Format : 24 cm. ISBN/ISSN/EAN : 978-0-12-160245-1 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Modelling Methodology for Physiology and Medicine offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modelling methodology that is widely applicable to physiology and medicine. The book 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. Builds upon and enhances the readers existing knowledge of modelling methodology and practice Editors are internationally renowned leaders in their respective fields Note de contenu : Contents: Chapter 1. An Introduction to Modelling Methodology 1.1 Introduction 1.2 The Need for Models 1.3 Approaches to Modelling 1.4 Simulation 1.5 Model Identification Chapter 2. Control in Physiology And Medicine 2.1 Introduction 2.2 A Systems and Control Approach 2.3 Control Mechanisms in Physiology 2.4 Control System Representations of the Clinical Process 2.5 Control System Approaches to Drug Therapy Planning and Administration Chapter 3. Deconvolution 3.1 Introduction 3.2 Problem Statement 3.3 Difficulty of the Deconvolution Problem 3.4 The Regularization Method 3.5 Other Deconvolution Methods 3.6 Conclusions 3.7 Acknowledgements Chapter 4. A priori Identifiability of Physiological Parametric Models 4.1 Introduction 4.2 The System-Experiment Model 4.3 A Priori Identifiability 4.4 Available Methods 4.5 An Identifiability Algorithm for Nonlinear Models 4.6 An Identifiability Algorithm for Linear Compartmental Models Appendix A: The Characteristic Set Appendix B: THE Gröbner Basis Chapter 5. Parameter Estimation 5.1 Introduction 5.2 Least Squares and Maximum Likelihood Estimators 5.3 Bayesian Estimator 5.4 Population Kinetic Analysis 5.5 Acknowledgement Chapter 6. Tracer Experiment Design for Metabolic Fluxes Estimation in Steady and Nonsteady State 6.1 Introduction 6.2 Fundamentals 6.3 Accessible-Pool and System Fluxes 6.4 The Tracer Probe 6.5 Estimation of Tracee Fluxes in Steady State 6.6 Estimation of Nonsteady-State Fluxes Chapter 7. Physiological Modelling of Positron Emission Tomography Images 7.1 Introduction 7.2 Modeling Strategies 7.3 Positron Emission Tomography Measurement Error 7.4 Models of Regional Glucose Metabolism 7.5 Models of [15O]H2O Kinetics to Assess Blood Flow 7.6 Models of the Ligand-Receptor System Chapter 8. Identification and Physiological Interpretation of Aortic Impedance in Modelling 8.1 Introduction 8.2 The Modelling Process and Related Problems of Identifiability and Determinacy 8.3 Vascular Impedance 8.4 Data-Driven Models of Vascular Impedance (Frequency Response Technique) 8.5 Historical Development of Windkessel Models 8.6 Where Windkessel Models' Identification Meets Physiological Interpretation 8.7 Contradictions in Clinically Oriented Compliance Estimation Methods (How the Viscoelastic Windke 8.8 Distributed Description of Linear Arterial Systems to Infer Aortic Wave Reflection 8.9 Identifiability: A Key Issue in the Assessment of Physiological Relevance of T-Tube Model Chapter 9. Mathematical Modelling of Pulmonary Gas Exchange 9.1 Standard Equations Used to Describe Gas Transport in the Lungs 9.2 Models of Diffusion Limitation 9.3 Models of Ventilation Perfusion Mismatch 9.4 Application of Mathematical Models of Ventilation, Perfusion, and Diffusion Appendix A. GLossary Appendix B. Calculations Necessary to Convert Inspired Gas at ATPD to BTPS Chapter 10. Mathematical Models of Respiratory Mechanics 10.1 Introduction 10.2 Breathing Mechanics: Basic Concepts 10.3 First-Order Models 10.4 Second-Order Models 10.5 Respiratory Oscillation Mechanics 10.6 Simulation Models of Breathing Mechanics Chapter 11. Insulin Modelling 11.1 Introduction 11.2 Models of Whole-body Insulin Kinetics 11.3 An Organ Model of Insulin Secretion 11.4 Estimation of Insulin Secretion by Deconvolution 11.5 A Structural Model to Estimate Insulin Secretion and Secretory Indices 11.6 Estimation of Hepatic Insulin Extraction Chapter 12. Glucose Modeling 12.1 Introduction 12.2 Models of Whole-body Kinetics in Steady State 12.3 Models of Regional Kinetics in Steady State 12.4 Models of Whole-body Kinetics in Nonsteady State 12.5 Models of Glucose and Insulin Control on Glucose Metabolism 12.6 Simulation Models Chapter 13. Blood-Tissue Exchange Modelling 13.1 Introduction 13.2 Experimental Approaches 13.3 Models of Blood-Tissue Exchange Index Modelling methodology for physiology and medicine [texte imprimé] / Ewart Carson, Auteur ; Claudio Cobelli, Auteur . - Amsterdam,Boston,Heidelberg... : Elsevier Academic Press, 2001 . - 421 p. : couv. ill. en coul., ill. ; 24 cm.. - (Academic Press Series in Biomedical Engineering) . ISBN : 978-0-12-160245-1 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Modelling Methodology for Physiology and Medicine offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modelling methodology that is widely applicable to physiology and medicine. The book 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. Builds upon and enhances the readers existing knowledge of modelling methodology and practice Editors are internationally renowned leaders in their respective fields Note de contenu : Contents: Chapter 1. An Introduction to Modelling Methodology 1.1 Introduction 1.2 The Need for Models 1.3 Approaches to Modelling 1.4 Simulation 1.5 Model Identification Chapter 2. Control in Physiology And Medicine 2.1 Introduction 2.2 A Systems and Control Approach 2.3 Control Mechanisms in Physiology 2.4 Control System Representations of the Clinical Process 2.5 Control System Approaches to Drug Therapy Planning and Administration Chapter 3. Deconvolution 3.1 Introduction 3.2 Problem Statement 3.3 Difficulty of the Deconvolution Problem 3.4 The Regularization Method 3.5 Other Deconvolution Methods 3.6 Conclusions 3.7 Acknowledgements Chapter 4. A priori Identifiability of Physiological Parametric Models 4.1 Introduction 4.2 The System-Experiment Model 4.3 A Priori Identifiability 4.4 Available Methods 4.5 An Identifiability Algorithm for Nonlinear Models 4.6 An Identifiability Algorithm for Linear Compartmental Models Appendix A: The Characteristic Set Appendix B: THE Gröbner Basis Chapter 5. Parameter Estimation 5.1 Introduction 5.2 Least Squares and Maximum Likelihood Estimators 5.3 Bayesian Estimator 5.4 Population Kinetic Analysis 5.5 Acknowledgement Chapter 6. Tracer Experiment Design for Metabolic Fluxes Estimation in Steady and Nonsteady State 6.1 Introduction 6.2 Fundamentals 6.3 Accessible-Pool and System Fluxes 6.4 The Tracer Probe 6.5 Estimation of Tracee Fluxes in Steady State 6.6 Estimation of Nonsteady-State Fluxes Chapter 7. Physiological Modelling of Positron Emission Tomography Images 7.1 Introduction 7.2 Modeling Strategies 7.3 Positron Emission Tomography Measurement Error 7.4 Models of Regional Glucose Metabolism 7.5 Models of [15O]H2O Kinetics to Assess Blood Flow 7.6 Models of the Ligand-Receptor System Chapter 8. Identification and Physiological Interpretation of Aortic Impedance in Modelling 8.1 Introduction 8.2 The Modelling Process and Related Problems of Identifiability and Determinacy 8.3 Vascular Impedance 8.4 Data-Driven Models of Vascular Impedance (Frequency Response Technique) 8.5 Historical Development of Windkessel Models 8.6 Where Windkessel Models' Identification Meets Physiological Interpretation 8.7 Contradictions in Clinically Oriented Compliance Estimation Methods (How the Viscoelastic Windke 8.8 Distributed Description of Linear Arterial Systems to Infer Aortic Wave Reflection 8.9 Identifiability: A Key Issue in the Assessment of Physiological Relevance of T-Tube Model Chapter 9. Mathematical Modelling of Pulmonary Gas Exchange 9.1 Standard Equations Used to Describe Gas Transport in the Lungs 9.2 Models of Diffusion Limitation 9.3 Models of Ventilation Perfusion Mismatch 9.4 Application of Mathematical Models of Ventilation, Perfusion, and Diffusion Appendix A. GLossary Appendix B. Calculations Necessary to Convert Inspired Gas at ATPD to BTPS Chapter 10. Mathematical Models of Respiratory Mechanics 10.1 Introduction 10.2 Breathing Mechanics: Basic Concepts 10.3 First-Order Models 10.4 Second-Order Models 10.5 Respiratory Oscillation Mechanics 10.6 Simulation Models of Breathing Mechanics Chapter 11. Insulin Modelling 11.1 Introduction 11.2 Models of Whole-body Insulin Kinetics 11.3 An Organ Model of Insulin Secretion 11.4 Estimation of Insulin Secretion by Deconvolution 11.5 A Structural Model to Estimate Insulin Secretion and Secretory Indices 11.6 Estimation of Hepatic Insulin Extraction Chapter 12. Glucose Modeling 12.1 Introduction 12.2 Models of Whole-body Kinetics in Steady State 12.3 Models of Regional Kinetics in Steady State 12.4 Models of Whole-body Kinetics in Nonsteady State 12.5 Models of Glucose and Insulin Control on Glucose Metabolism 12.6 Simulation Models Chapter 13. Blood-Tissue Exchange Modelling 13.1 Introduction 13.2 Experimental Approaches 13.3 Models of Blood-Tissue Exchange Index

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
2557	35-04-06	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	2557
2558	35-04-06	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	2558

Numerical methods in biomedical engineering / Stanley M. Dunn

Public ISBD Titre : Numerical methods in biomedical engineering Type de document : texte imprimé Auteurs : Stanley M. Dunn, Auteur ; Alkis Constantinides, Auteur ; Prabhas V. Moghe, Auteur Editeur : Amsterdam,Boston,Heidelberg... : Elsevier Academic Press Année de publication : 2006 Collection : Academic Press Series in Biomedical Engineering Importance : 615 p. Présentation : couv. ill. en coul., ill. Format : 24,7 cm. ISBN/ISSN/EAN : 978-0-12-186031-8 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Numerical Modeling in Biomedical Engineering brings together the integrative set of computational problem solving tools important to biomedical engineers. Through the use of comprehensive homework exercises, relevant examples and extensive case studies, this book integrates principles and techniques of numerical analysis. Covering biomechanical phenomena and physiologic, cell and molecular systems, this is an essential tool for students and all those studying biomedical transport, biomedical thermodynamics & kinetics and biomechanics. · Supported by Whitaker Foundation Teaching Materials Program; ABET-oriented pedagogical layout · MATLAB problem sets and examples available electronically; UNIX, Windows, Mac OS compatible · Extensive hands-on homework exercises Note de contenu : Table of contents Preface Organization and Outline of the Book Part I: Fundamentals Chapter 1 Modeling Biosystems 1.1 Biomedical Engineering 1.2 Fundamental Aspects of Biomedical Engineering 1.3 Constructing Engineering Models 1.4 Examples of Solving Biomedical Engineering Models by Computer 1.5 Overview of the Text 1.6 Lessons Learned in this Chapter 1.7 Problems Chapter 2 Introduction to Computing 2.1 Introduction 2.2 The Role of Computers in Biomedical Engineering 2.3 Programming Language Tools and Techniques 2.4 Fundamentals of Data Structures for MATLAB 2.5 An Introduction to Object-Oriented Systems 2.6 Analyzing Algorithms and Programs Chapter 3 Concepts of Numerical Analysis 3.1 Scientific Computing 3.2 Numerical Algorithms and Errors 3.3 Taylor Series 3.4 Keeping Errors Small 3.5 Floating-Point Representation in MATLAB Part II: Steady-State Behavior Chapter 4 Linear Models of Biological Systems 4.2 Examples of Linear Biological Systems 4.3 Simultaneous Linear Algebraic Equations 4.4 The Gauss-Jordan Reduction Method 4.5 Iterative Approach for Solution of Linear Systems Chapter 5 Nonlinear Equations in Biomedical Engineering 5.2 General Form of Nonlinear Equations 5.3 Examples of Nonlinear Equations in Biomedical Engineering 5.4 The Method of Successive Substitution 5.5 The Method of False Position (Linear Interpolation) 5.6 The Newton-Raphson Method 5.7 Newton’s Method for Simultaneous Nonlinear Equations Part III: Dynamic Behavior Chapter 6 Finite Difference Methods, Interpolation and Integration 6.2 Symbolic Operators 6.3 Backward Finite Differences 6.4 Forward Finite Differences 6.5 Central Finite Differences 6.6 Interpolating Polynomials 6.7 Interpolation of Equally Spaced Points 6.8 Interpolation of Unequally Spaced Points 6.9 Integration Formulas 6.10 The Newton-Cotes Formulas of Integration Chapter 7 Dynamic Systems: Ordinary Differential Equations 7.2 Classification of Ordinary Differential Equations 7.3 Transformation to Canonical Form 7.4 Nonlinear Ordinary Differential Equations 7.5 Linear Ordinary Differential Equations 7.6 Steady-State Solutions and Stability Analysis 7.7 Numerical Stability and Error Propagation 7.8 Advanced Examples Chapter 8 Dynamic Systems: Partial Differential Equations 8.2 Examples of PDEs in Biomedical Engineering 8.3 Classification of Partial Differential Equations 8.4 Initial and Boundary Conditions 8.5 Solution of Partial Differential Equations 8.6 Polar Coordinate Systems 8.7 Stability Analysis 8.8 PDE Toolbox in MATLAB Part IV: Modeling Tools and Applications Chapter 9 Measurements, Models and Statistics 9.1 The Role of Numerical Methods 9.2 Measurements, Errors and Uncertainty 9.3 Descriptive Statistics 9.4 Inferential Statistics 9.5 Least Squares Modeling 9.6 Curve Fitting 9.7 Fourier Transforms Chapter 10 Modeling Biosystems 10.1 Numerical Modeling of Bioengineering Systems 10.2 PhysioNet, PhysioBank, and PhysioToolkit 10.2.1 ECG simulation 10.3 Signal Processing: EEG Data 10.4 Diabetes and Insulin Regulation 10.5 Renal Clearance 10.6 Correspondence Problems and Motion Estimation 10.7 PHYSBE Simulations Appendices Appendix A: Introduction to MATLAB Appendix B: Introduction to Simulink Appendix C: Review of Linear Algebra and Related MATLAB Commands Appendix D: Analytical Solutions of Differential Equations Appendix E: Numerical Stability and Other Topics Index Numerical methods in biomedical engineering [texte imprimé] / Stanley M. Dunn, Auteur ; Alkis Constantinides, Auteur ; Prabhas V. Moghe, Auteur . - Amsterdam,Boston,Heidelberg... : Elsevier Academic Press, 2006 . - 615 p. : couv. ill. en coul., ill. ; 24,7 cm.. - (Academic Press Series in Biomedical Engineering) . ISBN : 978-0-12-186031-8 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Numerical Modeling in Biomedical Engineering brings together the integrative set of computational problem solving tools important to biomedical engineers. Through the use of comprehensive homework exercises, relevant examples and extensive case studies, this book integrates principles and techniques of numerical analysis. Covering biomechanical phenomena and physiologic, cell and molecular systems, this is an essential tool for students and all those studying biomedical transport, biomedical thermodynamics & kinetics and biomechanics. · Supported by Whitaker Foundation Teaching Materials Program; ABET-oriented pedagogical layout · MATLAB problem sets and examples available electronically; UNIX, Windows, Mac OS compatible · Extensive hands-on homework exercises Note de contenu : Table of contents Preface Organization and Outline of the Book Part I: Fundamentals Chapter 1 Modeling Biosystems 1.1 Biomedical Engineering 1.2 Fundamental Aspects of Biomedical Engineering 1.3 Constructing Engineering Models 1.4 Examples of Solving Biomedical Engineering Models by Computer 1.5 Overview of the Text 1.6 Lessons Learned in this Chapter 1.7 Problems Chapter 2 Introduction to Computing 2.1 Introduction 2.2 The Role of Computers in Biomedical Engineering 2.3 Programming Language Tools and Techniques 2.4 Fundamentals of Data Structures for MATLAB 2.5 An Introduction to Object-Oriented Systems 2.6 Analyzing Algorithms and Programs Chapter 3 Concepts of Numerical Analysis 3.1 Scientific Computing 3.2 Numerical Algorithms and Errors 3.3 Taylor Series 3.4 Keeping Errors Small 3.5 Floating-Point Representation in MATLAB Part II: Steady-State Behavior Chapter 4 Linear Models of Biological Systems 4.2 Examples of Linear Biological Systems 4.3 Simultaneous Linear Algebraic Equations 4.4 The Gauss-Jordan Reduction Method 4.5 Iterative Approach for Solution of Linear Systems Chapter 5 Nonlinear Equations in Biomedical Engineering 5.2 General Form of Nonlinear Equations 5.3 Examples of Nonlinear Equations in Biomedical Engineering 5.4 The Method of Successive Substitution 5.5 The Method of False Position (Linear Interpolation) 5.6 The Newton-Raphson Method 5.7 Newton’s Method for Simultaneous Nonlinear Equations Part III: Dynamic Behavior Chapter 6 Finite Difference Methods, Interpolation and Integration 6.2 Symbolic Operators 6.3 Backward Finite Differences 6.4 Forward Finite Differences 6.5 Central Finite Differences 6.6 Interpolating Polynomials 6.7 Interpolation of Equally Spaced Points 6.8 Interpolation of Unequally Spaced Points 6.9 Integration Formulas 6.10 The Newton-Cotes Formulas of Integration Chapter 7 Dynamic Systems: Ordinary Differential Equations 7.2 Classification of Ordinary Differential Equations 7.3 Transformation to Canonical Form 7.4 Nonlinear Ordinary Differential Equations 7.5 Linear Ordinary Differential Equations 7.6 Steady-State Solutions and Stability Analysis 7.7 Numerical Stability and Error Propagation 7.8 Advanced Examples Chapter 8 Dynamic Systems: Partial Differential Equations 8.2 Examples of PDEs in Biomedical Engineering 8.3 Classification of Partial Differential Equations 8.4 Initial and Boundary Conditions 8.5 Solution of Partial Differential Equations 8.6 Polar Coordinate Systems 8.7 Stability Analysis 8.8 PDE Toolbox in MATLAB Part IV: Modeling Tools and Applications Chapter 9 Measurements, Models and Statistics 9.1 The Role of Numerical Methods 9.2 Measurements, Errors and Uncertainty 9.3 Descriptive Statistics 9.4 Inferential Statistics 9.5 Least Squares Modeling 9.6 Curve Fitting 9.7 Fourier Transforms Chapter 10 Modeling Biosystems 10.1 Numerical Modeling of Bioengineering Systems 10.2 PhysioNet, PhysioBank, and PhysioToolkit 10.2.1 ECG simulation 10.3 Signal Processing: EEG Data 10.4 Diabetes and Insulin Regulation 10.5 Renal Clearance 10.6 Correspondence Problems and Motion Estimation 10.7 PHYSBE Simulations Appendices Appendix A: Introduction to MATLAB Appendix B: Introduction to Simulink Appendix C: Review of Linear Algebra and Related MATLAB Commands Appendix D: Analytical Solutions of Differential Equations Appendix E: Numerical Stability and Other Topics Index

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Signals and systems for bioengineers / John Semmlow

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Signals and systems for bioengineers / John Semmlow

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