
Numerical Methods in Biomedical Engineering
Hardcover | 7 November 2005
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640 Pages
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· 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
Industry Reviews
Preface | p. xiii |
Fundamentals | |
Modeling Biosystems | p. 1 |
Biomedical Engineering | p. 1 |
Fundamental Aspects of Biomedical Engineering | p. 3 |
Constructing Engineering Models | p. 3 |
A framework for problem solving | p. 4 |
Formulating the mathematical expression of conservation | p. 5 |
Using balance equations | p. 7 |
How conservation laws lead to the Nernst equation | p. 7 |
Examples of Solving Biomedical Engineering Models by Computer | p. 9 |
Modeling rtPCR efficiency | p. 9 |
Modeling transcranial magnetic stimulation | p. 13 |
Modeling cardiac electrophysiology | p. 14 |
Using numerical methods to model the response of the cardiovascular system to gravity | p. 15 |
Overview of the Text | p. 17 |
Part I: Fundamentals | p. 18 |
Part II: Steady-state behavior (algebraic models) | p. 19 |
Part III: Dynamic biosystems (differential equations) | p. 19 |
Part IV: Modeling tools and applications | p. 19 |
Lessons Learned in this Chapter | p. 20 |
Problems | p. 20 |
References | p. 21 |
Introduction to Computing | p. 23 |
Introduction | p. 23 |
The Role of Computers in Biomedical Engineering | p. 24 |
Programming Language Tools and Techniques | p. 27 |
Sequences of statements | p. 27 |
Programs that are sequences of statements | p. 28 |
Conditional execution | p. 28 |
Simple control flow using if...then...else | p. 29 |
Use of the switch statement | p. 31 |
Iteration | p. 34 |
The use of while loops | p. 34 |
Using for...end loops | p. 36 |
Encapsulation | p. 37 |
Using scripts and functions | p. 37 |
Fundamentals of Data Structures for MATLAB | p. 39 |
Number representation | p. 39 |
Number representation in MATLAB | p. 40 |
Complex numbers | p. 40 |
Arrays | p. 41 |
Indexing arrays in MATLAB | p. 41 |
Characters and strings | p. 43 |
Character strings as arrays | p. 43 |
Logical or Boolean data types | p. 44 |
Logical indexing in MATLAB | p. 44 |
Cells and cell arrays | p. 46 |
Cell arrays and mixed data types | p. 46 |
Structure arrays and mixed data types | p. 48 |
Data structures not explicitly found in MATLAB | p. 48 |
Data structures in MATLAB: implementing a stack | p. 49 |
Data type conversion | p. 50 |
Data type conversion | p. 51 |
An Introduction to Object-Oriented Systems | p. 52 |
Simple object-oriented programs that are sequences of statements | p. 55 |
Analyzing Algorithms and Programs | p. 57 |
Polynomial complexity | p. 57 |
Operation counting | p. 57 |
Measuring execution time as a function of the amount of data | p. 59 |
Lessons Learned in this Chapter | p. 61 |
Problems | p. 62 |
Concepts of Numerical Analysis | p. 65 |
Scientific Computing | p. 65 |
Numerical Algorithms and Errors | p. 66 |
Taylor Series | p. 67 |
How truncation errors and roundoff errors arise | p. 68 |
Keeping Errors Small | p. 72 |
An ill-posed problem | p. 72 |
Floating-Point Representation in MATLAB | p. 74 |
The IEEE 754 standard for floating-point representation | p. 75 |
IEEE 754 floating-point representation | p. 75 |
Floating-point arithmetic, truncation, and rounding | p. 76 |
Propagation of floating-point errors | p. 77 |
Machine precision in MATLAB | p. 77 |
Roundoff error accumulation and cancellation error | p. 78 |
Avoiding overflow | p. 78 |
Avoiding cancellation errors | p. 79 |
Using Taylor series expansions to avoid cancellation errors | p. 79 |
Lessons Learned in this Chapter | p. 80 |
Problems | p. 81 |
References | p. 83 |
Steady-State Behavior | |
Linear Models of Biological Systems | p. 85 |
Introduction | p. 85 |
Examples of Linear Biological Systems | p. 86 |
Force balance in biomechanics | p. 86 |
Biomedical imaging and image processing | p. 88 |
Metabolic engineering and cellular biotechnology | p. 89 |
Simultaneous Linear Algebraic Equations | p. 90 |
Illustration of simple Gauss elimination for a 3 x 3 matrix | p. 90 |
Matrix notation of Gaussian elimination | p. 91 |
Application of the Gauss elimination method | p. 98 |
The Gauss-Jordan Reduction Method | p. 100 |
Application of the Gauss-Jordan reduction method | p. 102 |
Iterative Approach for Solution of Linear Systems | p. 105 |
The Jacobi method | p. 105 |
Application of the iterative Jacobi method | p. 107 |
The Gauss-Seidel method | p. 110 |
Application of the iterative Gauss-Seidel method | p. 111 |
Lessons Learned in this Chapter | p. 114 |
Problems | p. 114 |
References | p. 116 |
Nonlinear Equations in Biomedical Engineering | p. 117 |
Introduction | p. 117 |
General Form of Nonlinear Equations | p. 118 |
Examples of Nonlinear Equations in Biomedical Engineering | p. 120 |
Molecular bioengineering | p. 120 |
Cellular and tissue engineering | p. 121 |
Bioheat transport: photothermal therapy | p. 122 |
Biomedical flow transport dynamics | p. 123 |
The Method of Successive Substitution | p. 124 |
The Method of False Position (Linear Interpolation) | p. 125 |
The Newton-Raphson Method | p. 127 |
Cardiovascular physiology | p. 130 |
Solution of the Colebrook equation using Newton-Raphson | p. 136 |
Successive substitution method for solution of nonlinear equation | p. 141 |
Solution of the Colebrook equation using linear interpolation | p. 145 |
Solution of a Michaelis-Menten kinetics equation using the Newton-Raphson method | p. 150 |
Newton's Method for Simultaneous Nonlinear Equations | p. 151 |
Determination of receptor occupancy during receptorligand dynamics | p. 153 |
Lessons Learned in this Chapter | p. 157 |
Problems | p. 157 |
References | p. 161 |
Dynamic Behavior | |
Finite Difference Methods, Interpolation and Integration | p. 163 |
Introduction | p. 163 |
Symbolic Operators | p. 164 |
Backward Finite Differences | p. 167 |
Express the first-order derivative in terms of backward finite differences with error of order h | p. 169 |
Express the first-order derivative in terms of backward finite differences with error of order h[superscript 2] | p. 170 |
Forward Finite Differences | p. 172 |
Express the first-order derivative in terms of forward finite differences with error of order h | p. 173 |
Express the second-order derivative in terms of forward finite differences with error of order h | p. 173 |
Central Finite Differences | p. 176 |
Express the first-order derivative in terms of central finite differences with error of order h[superscript 2] | p. 176 |
Express the second-order derivative in terms of central finite differences with error of order h[superscript 2] | p. 177 |
Interpolating Polynomials | p. 178 |
Interpolation of Equally Spaced Points | p. 182 |
Gregory-Newton interpolation | p. 182 |
Gregory-Newton method for interpolation of equally spaced data | p. 186 |
Interpolation of Unequally Spaced Points | p. 191 |
Lagrange polynomials | p. 191 |
Spline interpolation | p. 192 |
Integration Formulas | p. 193 |
The Newton-Cotes Formulas of Integration | p. 194 |
The trapezoidal rule | p. 195 |
Simpson's 1/3 rule | p. 197 |
Simpson's 3/8 rule | p. 198 |
Summary of Newton-Cotes integration | p. 200 |
Integration formulas-Trapezoidal and Simpson's 1/3 rules | p. 201 |
Lessons Learned in this Chapter | p. 205 |
Problems | p. 206 |
References | p. 208 |
Dynamic Systems: Ordinary Differential Equations | p. 209 |
Introduction | p. 209 |
Pharmacokinetics: the dynamics of drug absorption | p. 210 |
Tissue engineering: cell differentiation, cell adhesion and migration dynamics | p. 211 |
Metabolic Engineering: Glycolysis pathways of living cells | p. 212 |
Transport of molecules across biological membranes | p. 213 |
Classification of Ordinary Differential Equations | p. 214 |
Transformation to Canonical Form | p. 216 |
Transformation of ordinary differential equations into their canonical form | p. 218 |
Nonlinear Ordinary Differential Equations | p. 221 |
The Euler and modified Euler methods | p. 221 |
The Runge-Kutta methods | p. 224 |
Simultaneous differential equations | p. 227 |
MATLAB functions for nonlinear equations | p. 227 |
Solution of enzyme catalysis reactions | p. 229 |
Linear Ordinary Differential Equations | p. 233 |
Method using eigenvalues and eigenvectors | p. 233 |
MATLAB functions for linear equations | p. 235 |
The dynamics of drug absorption | p. 236 |
Steady-State Solutions and Stability Analysis | p. 241 |
Numerical Stability and Error Propagation | p. 246 |
Advanced Examples | p. 248 |
Metabolic engineering: Modeling the glycolysis pathways of living cells | p. 248 |
The dynamics of membrane and nerve cell potentials | p. 255 |
The dynamics of stem cell differentiation | p. 264 |
Tissue engineering: models of epidermal cell migration | p. 271 |
Lessons Learned in this Chapter | p. 279 |
Problems | p. 279 |
References | p. 286 |
Dynamic Systems: Partial Differential Equations | p. 289 |
Introduction | p. 289 |
Examples of PDEs in Biomedical Engineering | p. 290 |
Diffusion across biological membranes | p. 290 |
Diffusion of macromolecules and controlled release of drugs | p. 292 |
Cell migration on vascular prosthetic materials | p. 293 |
Fluid flow in physiological and extracorporeal vessels | p. 293 |
Classification of Partial Differential Equations | p. 294 |
Initial and Boundary Conditions | p. 296 |
Solution of Partial Differential Equations | p. 299 |
Elliptic partial differential equations | p. 305 |
Solution of the Laplace and Poisson equations | p. 310 |
Parabolic partial differential equations | p. 317 |
Migration of human leukocytes on prosthetic materials | p. 321 |
Hyperbolic partial differential equations | p. 327 |
Polar Coordinate Systems | p. 329 |
Stability Analysis | p. 331 |
PDE Toolbox in MATLAB | p. 331 |
Solution of Fick's second law of diffusion using the PDE toolbox | p. 332 |
Lessons Learned in this Chapter | p. 338 |
Problems | p. 338 |
References | p. 343 |
Modeling Tools and Applications | |
Measurements, Models and Statistics | p. 345 |
The Role of Numerical Methods | p. 345 |
Measurements, Errors and Uncertainty | p. 346 |
Descriptive Statistics | p. 349 |
Computing statistics of MRI and CT image intensities | p. 351 |
Inferential Statistics | p. 356 |
Estimating the mean value of a population from a sample | p. 357 |
Hypothesis testing in DNA microarray analysis | p. 383 |
Least Squares Modeling | p. 363 |
Least square fit of a first-order polynomial (straight line) | p. 365 |
Least squares fit of a cubic polynomial | p. 367 |
Least squares fit of a nonlinear model | p. 367 |
Least squares fit of a multivariate model | p. 368 |
Curve Fitting | p. 369 |
Lagrange interpolating polynomials | p. 369 |
Newton divided difference interpolating polynomials | p. 370 |
Splines | p. 372 |
Resampling and baseline correction of MALDI-TOF mass spectra data | p. 374 |
Fourier Transforms | p. 379 |
Separating EEG frequency components | p. 382 |
Lessons Learned in the Chapter | p. 386 |
Problems | p. 387 |
References | p. 388 |
Modeling Biosystems: Applications | p. 389 |
Numerical Modeling of Bioengineering Systems | p. 389 |
PhysioNet, PhysioBank, and PhysioToolkit | p. 391 |
ECG simulation | p. 391 |
Using the MATLAB script ECGwaveGen to synthesize ECG data | p. 391 |
Reading PhysioBank data | p. 395 |
Read and visualize PhysioBank signals and annotations | p. 395 |
Signal Processing: EEG Data | p. 397 |
Differential brain activity in the left and right hemispheres | p. 400 |
Diabetes and Insulin Regulation | p. 403 |
Simulink model of glucose regulation | p. 405 |
Renal Clearance | p. 411 |
Renal clearance | p. 412 |
Correspondence Problems and Motion Estimation | p. 414 |
Estimating motion from features on a rigid body | p. 415 |
Physbe Simulations | p. 419 |
Normal PHYSBE operation | p. 420 |
Coarctation of the aorta | p. 422 |
Simulink model of coarctation of the aorta | p. 423 |
Aortic stenosis | p. 426 |
Simulink model of aortic valve stenosis | p. 427 |
Ventricular septal defect | p. 430 |
Ventricular septal defect | p. 430 |
Left ventricular hypertrophy | p. 434 |
Left ventricular hypertrophy | p. 436 |
Pressure-volume loops | p. 438 |
References | p. 440 |
Appendices | |
Introduction to MATLAB | p. 443 |
Introduction to Simulink | p. 487 |
Review of Linear Algebra and Related MATLAB Commands | p. 517 |
Analytical Solutions of Differential Equations | p. 527 |
Numerical Stability and Other Topics | p. 575 |
Index | p. 593 |
Table of Contents provided by Ingram. All Rights Reserved. |
ISBN: 9780121860318
ISBN-10: 0121860310
Series: Biomedical Engineering
Published: 7th November 2005
Format: Hardcover
Language: English
Number of Pages: 640
Audience: Professional and Scholarly
Publisher: Academic Press
Country of Publication: US
Dimensions (cm): 24.4 x 17.5 x 4.45
Weight (kg): 1.45
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