Circuits, Signals, and Systems for Bioengineers: A MATLAB-Based Introduction

Citation

Semmlow, J. (2024). Circuits, Signals, and Systems for Bioengineers: A MATLAB-Based Introduction (4th ed.). Academic Press.

Chapter Summary

The fourth edition runs to almost 790 pages in 15 chapters and seven appendices (derivations, transform tables, trigonometric formulae, conversion factors, complex numbers, the specifications of an operational amplifier, and determinants with Cramer's rule). It is by John Semmlow, for 32 years a professor of biomedical engineering at Rutgers and of surgery at Robert Wood Johnson Medical School, whose research covers cardiovascular diagnosis and human motor control. The book is in three parts, in an order that differs from many electrical engineering courses: signals first, then systems, then circuits. The publisher describes it as introducing the electrical engineering principles behind biomedical systems, medical devices, biocontrol and biomedical signal analysis, with computational methods that let students explore correlation, convolution, the Fourier transform and the transfer function in MATLAB. Support materials include solutions, lecture slides, and the MATLAB data and functions needed for the problems.

Part I: Signals (Chapters 1–4: The Big Picture: Bioengineering Signals and Systems; Signal Analysis in the Time Domain; Signal Analysis in the Frequency Domain: The Fourier Series and the Fourier Transformation; Signal Analysis in the Frequency Domain – Implications and Applications)

Chapter 1 sets out the overall view of signals and systems in bioengineering. Chapter 2, at about 65 pages the longest in the book, analyses signals in the time domain. Chapters 3 and 4 introduce the Fourier series and transform and then their implications and applications.

Part II: Systems (Chapters 5–11: Linear Systems Analysis in the Time Domain – Convolution; Linear Systems Analysis in the Frequency Domain: The Transfer Function; Linear Systems in the Complex Frequency Domain: The Laplace Transform; Analysis of Discrete Linear Systems – The z-Transform and Applications to Filters; System Modeling and Simulink; Stochastic, Nonstationary, and Nonlinear Systems and Signals; Two-Dimensional Signals – Basic Image Analysis)

The central and longest part. Linear systems are analysed three ways, by convolution in the time domain, by the transfer function in the frequency domain and by the Laplace transform, before Chapter 8 turns to discrete systems, the z-transform and digital filters. Chapter 9 introduces system modelling with Simulink; the publisher points to biocontrol applications with examples from physiological modelling such as the respiratory system. Chapter 10 moves beyond linear, deterministic signals to noise, stochastic, nonstationary and nonlinear signals, and Chapter 11 extends the methods to two-dimensional signals and basic image analysis. Chapters 10 and 11 were added in the third edition.

Part III: Circuits (Chapters 12–15: Circuit Elements and Circuit Variables; Analysis of Analog Circuits and Models; Circuit Reduction – Simplifications; Basic Analog Electronics – Operational Amplifiers)

The last part builds circuit analysis from the elements and variables up, analyses analog circuits and circuit models, covers circuit reduction and ends with operational amplifiers. An appendix gives the specifications of a specific op-amp, the LF356.

Key Concepts

Part I: Signals

• Time-domain signal analysis: describing and comparing signals directly as functions of time, including correlation.
• Fourier series and Fourier transform: representing a signal by its frequency components.
• Frequency-domain implications: what the spectrum of a signal shows and how it is used in practice.

Part II: Systems

• Convolution: the response of a linear system computed from its impulse response in the time domain.
• Transfer function: the description of a linear system by how it modifies each frequency.
• Laplace transform: the complex-frequency extension of the transfer function, used for transient behaviour.
• z-transform and digital filters: the corresponding tools for discrete, sampled systems.
• Simulink modelling: building and simulating system models, including physiological control systems.
• Stochastic and nonstationary signals: noise and signals whose properties change with time.
• Basic image analysis: applying signal processing to two-dimensional signals.

Part III: Circuits

• Circuit elements and variables: the components and quantities from which analog circuits are analysed.
• Circuit reduction: simplifying networks into equivalent forms.
• Operational amplifiers: the basic building block of analog electronics.

Critical Analysis

Strengths

• Computation at the centre. As the subtitle says, the book is MATLAB-based. The publisher stresses that operations such as correlation, convolution, the Fourier transform and the transfer function are developed through computation, and the support materials include the data and functions needed to solve the problems.
• Biomedical context throughout. The publisher's descriptions of both the third and the fourth edition emphasise biological, physiological and medical examples, and the biocontrol material draws on physiological systems modelling.
• Unified coverage of three subjects. One volume takes students from signal analysis through linear and discrete systems to circuits and op-amps, the electrical engineering background a bioengineering programme often has to squeeze into one or two courses.
• Matured over four editions. The third edition added chapters on image analysis and on noise and stochastic processes; the fourth, according to the publisher, revises the text throughout for clarity and adds new medical examples.

Limitations

• Large. At nearly 790 pages, the book holds more than one semester of material, and instructors must choose among the parts.
• Circuits come last. Programmes that need circuit analysis early, for instance before an instrumentation laboratory, will have to read Part III out of order; this departs from the book's sequence.
• Introductory treatment of advanced topics. Stochastic and nonlinear signals and image analysis get one chapter each, about 40 pages; students working seriously with biosignals or images need a dedicated text.
• Tied to MATLAB and Simulink. The examples and support materials assume access to these commercial tools.

Where It Fits in the Course

This is the foundation text for biomedical signal processing in the course list: it teaches the signals, systems and circuits background that the other books assume. Semmlow and Griffel's Biosignal and Medical Image Processing is the natural next step by the same author, working through filtering, spectral and time-frequency analysis of physiological signals and then medical images, also with MATLAB. Rangayyan's Biomedical Signal Analysis is a more advanced, case-study-driven treatment of ECG, EEG, EMG and other signals, motivated by clinical problems and applied to real recordings.

Smith's The Scientist and Engineer's Guide to Digital Signal Processing, freely available from its author, explains sampling, convolution, Fourier analysis and digital filters with minimal mathematics, and is a good companion for students who find Chapters 3–8 heavy going. Tompkins's Biomedical Digital Signal Processing is an older book built around C programs and laboratory experiments for the PC; its examples are of historical interest but still show how classic biosignal filters were implemented.

How to Use This Book

The book is for bioengineering and biomedical engineering students, meeting signals, systems and circuits for the first time, and for practising technicians and engineers from other fields. Calculus and introductory physics are the background; complex numbers and determinants are reviewed in appendices. Access to MATLAB, and to Simulink for Chapter 9, is needed to do the examples.

A practical plan:

• Signals course: Part I in full, then Chapters 5–8 of Part II (convolution, transfer function, Laplace transform, z-transform and filters).
• Systems or physiological modelling course: Chapters 5–7, then Chapter 9 on Simulink modelling; Chapter 10 if noise and variability matter for the course.
• Circuits or instrumentation preparation: Part III, which forms a separate block and can be read out of sequence.
• Optional: Chapter 11 on images, a bridge to medical image processing.

Run the MATLAB examples while reading and change their parameters; the book is designed so that operations like convolution and the Fourier transform are understood by computing them. Work end-of-chapter problems with the supplied data files rather than synthetic data.