Biomedical signals and systems
 Responsibility
 Joseph V. Tranquillo.
 Language
 English.
 Publication
 San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2014.
 Physical description
 1 PDF (xxi, 211 pages).
 Series
 Synthesis digital library of engineering and computer science.
 Synthesis lectures on biomedical engineering ; #52.
Access
Available online
More options
Creators/Contributors
 Author/Creator
 Tranquillo, Joseph Vincent, 1975 author.
Contents/Summary
 Contents

 1. Introduction
 1.1 What is a system?
 1.1.1 Cause and effect
 1.1.2 The systems of engineering
 1.2 What is a signal?
 1.2.1 Signals in engineering
 1.2.2 Sensors
 1.3 System boundaries
 1.4 Design using signals and systems
 2. System types
 2.1 Introduction
 2.2 conservative and nonconservative systems
 2.3 Open and closed systems
 2.4 Static and dynamic systems
 2.5 Continuous and discrete signals and systems
 2.6 Stable and unstable systems
 2.7 Time varying and time invariant systems
 2.8 Deterministic and nondeterministic systems
 2.9 Finite and infinite systems
 2.10 Linear and nonlinear systems
 2.11 Stationary and nonstationary
 2.12 Memory and memoriless systems
 2.13 Time constants
 2.14 Conclusion
 2.15 Exercises
 3. System models
 3.1 What is a model
 3.2 Models using conservation
 3.2.1 Conservation of momentum
 3.2.2 Conservation of charge
 3.2.3 Conservation of mass
 3.2.4 Fluid mass and volume
 3.2.5 Conservation of energy
 3.2.6 Other models
 3.3 State and compartment models
 3.3.1 Volume balance
 3.3.2 Models of ion channels
 3.4 Reduction of a higher order equation
 3.5 Exercises
 4. Laplace transform
 4.1 Introduction
 4.2 Formal definitions
 4.2.1 Laplace transform
 4.2.2 Inverse Laplace transform
 4.3 Transform tables
 4.4 Four useful Laplace transforms
 4.4.1 The impulse
 4.4.The unit step
 4.4.3 The sinusoid
 4.4.4 The derivative
 4.5 From differential to algebraic equations
 4.6 From algebraic equations to a solution
 4.7 Other interesting applications
 4.7.1 The Fourier transform
 4.7.2 Nontime mapping
 4.8 The ztransform
 4.9 Exercises
 5. Block diagrams
 5.1 Block diagram of a pacemakerdefibrilator
 5.2 Parallel, series and junctions
 5.3 Transfer functions
 5.3.1 Reducing block diagrams
 5.3.2 Series connection reduction
 5.3.3 Parallel connection reduction
 5.3.4 Combining series and parallel
 5.4 Matlab, signals and systems
 5.5 Exercises
 6. Stability
 6.1 Introduction
 6.2 Stability and transfer function poles
 6.2.1 Finding poles and zeros
 6.2.2 Visualizing poles and zeros
 6.2.3 Relationship to stability in time
 6.3 The role of zeros
 6.4 Designing systems
 6.5 Matlab and stability
 6.6 Exercises
 7. Feedback
 7.1 Open and closed loop systems
 7.2 Feedback transfer functions
 7.3 Block diagram reductions
 7.4 Stability and feedback
 7.5 Feedforward
 7.6 Opening the loop
 7.7 Matlab and feedback
 7.8 Exercises
 8. System response
 8.1 Zero input and zero state response
 8.2 The impulse response
 8.2.1 A first order example
 8.2.2 A different first order example
 8.2.3 A second order example
 8.3 The step response
 8.3.1 The importance of the step response
 8.3.2 Comparing the step and impulse responses
 8.4 Quantifying a response
 8.4.1 Estimating a transfer function
 8.4.2 A generic second order system
 8.5 The sine response
 8.5.1 decibels
 8.5.2 The Bode plot
 8.5.3 The 3dB point
 8.6 Response to an arbitrary input
 8.6.1 Convolution
 8.6.2 Deconvolution
 8.7 Other applications
 8.7.1 Other useful test signals
 8.8 Matlab and system responses
 8.9 Exercises
 9. Control
 9.1 The generic control model
 9.2 Evaluating a controlled response
 9.2.1 Time domain evaluation
 9.2.2 Frequency domain evaluation
 9.3 Onoff controllers
 9.4 PID controllers
 9.4.1 Proportional (P) control
 9.4.2 Proportional derivative (PD) controller
 9.4.3 Proportional integral (PI) controller
 9.4.4 Proportional integral derivative (PID) controller
 9.4.5 Choosing constants
 9.4.6 Alternative formulation
 9.5 Example of a PID controlled system
 9.6 The problem of system delays
 9.7 Other controllers
 9.7.1 Laglead controllers
 9.8 Reverse engineering biological systems
 9.9 Matlab
 9.10 Exercises
 10. Time domain analysis
 10.1 Basic signal processing
 10.1.1 Average
 10.1.2 Signal power
 10.1.3 Variance and standard deviation
 10.1.4 Signal to noise ratio
 10.2 Correlations
 10.2.1 Crosscorrelation
 10.2.2 Cross covariance
 10.2.3 Auto correlation
 10.3 Matlab
 10.4 Exercises
 11. Frequency domain analysis
 11.1 Comparing a signal to sinusoids
 11.1.1 Properties of sinusoids
 11.1.2 A problem with the crosscorrelation
 11.2 The Fourier series
 11.3 The Fourier transform
 11.3.1 Power at a frequency
 11.3.2 Fourier transform properties
 11.3.3 The rectangle function
 11.3.4 Inverse Fourier transform
 11.4 The discrete Fourier transform
 11.4.1 Aliasing and the Nyquist rate
 11.4.2 The Nyquist rate and aliasing
 11.5 Matlab
 11.6 Exercises
 12. Filters
 12.1 Ideal filters
 12.1.1 Ideal filter phase shift
 12.1.2 The chirp signal
 12.2 Filters in reality
 12.2.1 Rolloff
 12.2.2 Ripples
 12.2.3 Phase shifts
 12.3 First and second order filters
 12.3.1 A first order filter
 12.3.2 A second order filter
 12.4 Higher order filters
 12.4.1 Butterworth
 12.4.2 Chebyshev
 12.4.3 Elliptical
 12.4.4 Bessel
 12.4.5 Filter evaluation
 12.4.6 High, bandpass and notch filter
 12.4.7 Electrical implementation
 12.5 Windowing in the time domain
 12.6 Matlab
 12.7 Exercises
 A. Complex numbers
 A.1 Introduction
 A.2 The complex plane
 A.3 Euler's identity
 A.4 Mathematical operations
 A.4.1 Addition and subtraction
 A.4.2 Multiplication
 A.4.3 Conjugation
 B. Partial fraction expansion
 C. Laplace transform table
 D. Fourier transform table
 Author's biography.
 Summary
 Biomedical Signals and Systems is meant to accompany a onesemester undergraduate signals and systems course. It may also serve as a quickstart for graduate students or faculty interested in how signals and systems techniques can be applied to living systems. The biological nature of the examples allows for systems thinking to be applied to electrical, mechanical, fluid, chemical, thermal and even optical systems. Each chapter focuses on a topic from classic signals and systems theory: System block diagrams, mathematical models, transforms, stability, feedback, system response, control, time and frequency analysis and filters. Embedded within each chapter are examples from the biological world, ranging from medical devices to cell and molecular biology. While the focus of the book is on the theory of analog signals and systems, many chapters also introduce the corresponding topics in the digital realm. Although some derivations appear, the focus is on the concepts and how to apply them. Throughout the text, systems vocabulary is introduced which will allow the reader to read more advanced literature and communicate with scientist and engineers. Homework and Matlab simulation exercises are presented at the end of each chapter and challenge readers to not only perform calculations and simulations but also to recognize the realworld signals and systems around them.
Subjects
Bibliographic information
 Publication date
 2014
 Series
 Synthesis lectures on biomedical engineering, 19300336 ; #52
 Note
 Part of: Synthesis digital library of engineering and computer science.
 Series from website.
 Access
 Abstract freely available; fulltext restricted to subscribers or individual document purchasers.
 Citation
 Compendex
 INSPEC
 Google scholar
 Google book search
 Note
 Also available in print.
 Format
 Mode of access: World Wide Web.
 System requirements: Adobe Acrobat Reader.
 Available in another form
 Print version: ( 9781627053310 )
 ISBN
 9781627053327 (ebook)
 9781627053310 (paperback)
 1627053328 (electronic bk.)
 162705331X (print)