IEEE Press Series on Biomedical Engineering

This book grew out of the “IEEE-EMBS Summer Schools on Biomedical Signal Processing”, which have been held annually since 2002 to provide the participants state-of-the-art knowledge on emerging areas in biomedical engineering. Prominent experts in the areas of biomedical signal processing, biomedical data treatment, medicine, signal processing, system biology, and applied physiology introduce novel techniques and algorithms as well as their clinical or physiological applications. The book provides an overview of a compelling group of advanced biomedical signal processing techniques, such as multisource and multiscale integration of information for physiology and clinical decision; the impact of advanced methods of signal processing in cardiology and neurology; the integration of signal processing methods with a modelling approach; complexity measurement from biomedical signals; higher order analysis in biomedical signals; advanced methods of signal and data processing in genomics and proteomics; and classification and parameter enhancement.

The expanded and revised edition will split Chapter 4 to include more details and examples in FMRI, DTI, and DWI for MR. image modalities. The book will also expand ultrasound imaging to 3-D dynamic contrast ultrasound imaging in a separate chapter. A new chapter on Optical Imaging Modalities elaborating microscopy, confocal microscopy, endoscopy, optical coherent tomography, fluorescence and molecular imaging will be added. Another new chapter on Simultaneous Multi-Modality Medical Imaging including CT-SPECT and CT-PET will also be added. In the image analysis part, chapters on image reconstructions and visualizations will be significantly enhanced to include, respectively, 3-D fast statistical estimation based reconstruction methods, and 3-D image fusion and visualization overlaying multi-modality imaging and information. A new chapter on Computer-Aided Diagnosis and image guided surgery, and surgical and therapeutic intervention will also be added.

A cutting-edge look at the application of micro and nanotechnologies in regenerative medicine The area at the interface of micro/nanotechnology and stem cells/tissue engineering has seen an explosion of activity in recent years. This book provides a much-needed overview of these exciting developments, covering all aspects of micro and nanotechnologies, from the fundamental principles to the latest research to applications in regenerative medicine. Written and edited by the top researchers in the field, “Micro and Nanotechnologies in Engineering Stem Cells and Tissues” describes advances in material systems along with current techniques available for cell, tissue, and organ studies. Readers will gain tremendous insight into the state of the art of stem cells and tissue engineering and learn how to use the technology in their own research or clinical trials. Coverage includes: • Technologies for controlling or regulating stem cell and tissue growth • Various engineering approaches for stem cell, vascular tissue, and bone regeneration • The design and processing of biocompatible polymers and other biomaterials • Characterization of the interactions between cells and biomaterials Unrivaled among books of this kind, “Micro and Nanotechnologies in Engineering Stem Cells and Tissues” is the ultimate forward-looking reference for researchers in numerous disciplines, from engineering and materials science to biomedicine, and for anyone wishing to understand the trends in this transformative field.

Neural engineering is a discipline that uses engineering techniques to understand, repair, replace, enhance, or treat diseases of neural systems. Currently, no book other than this one covers this broad range of topics within motor rehabilitation technology. With a focus on cutting edge technology, it describes state-of-the-art methods within this field, from brain-computer interfaces to spinal and cortical plasticity. Touching on electrode design, signal processing, the neurophysiology of movement, robotics, and much more, this innovative volume collects the latest information for a wide range of readers working in biomedical engineering.

Discover how multiscale modeling can enhance patient treatment and outcomes. In “Multiscale Modelling in Biomedical Engineering”, an accomplished team of biomedical professionals delivers a robust treatment of the foundation and background of a general computational methodology for multi-scale modeling. The authors demonstrate how this methodology can be applied to various fields of biomedicine, with a particular focus on orthopedics and cardiovascular medicine. The book begins with a description of the relationship between multiscale modeling and systems biology before moving on to proceed systematically upwards in hierarchical levels from the molecular to the cellular, tissue, and organ level. It then examines multiscale modeling applications in specific functional areas, like mechanotransduction, musculoskeletal, and cardiovascular systems. “Multiscale Modelling in Biomedical Engineering” offers readers experiments and exercises to illustrate and implement the concepts contained within. Readers will also benefit from the inclusion of: • A thorough introduction to systems biology and multi-scale modeling, including a survey of various multi-scale methods and approaches and analyses of their application in systems biology • Comprehensive explorations of biomedical imaging and nanoscale modeling at the molecular, cell, tissue, and organ levels • Practical discussions of the mechanotransduction perspective, including recent progress and likely future challenges • In-depth examinations of risk prediction in patients using big data analytics and data mining Perfect for undergraduate and graduate students of bioengineering, biomechanics, biomedical engineering, and medicine, “Multiscale Modelling in Biomedical Engineering” will also earn a place in the libraries of industry professional and researchers seeking a one-stop reference to the basic engineering principles of biological systems.

Addresses recent advances from both the clinical and technological perspectives to provide a comprehensive presentation of m-Health This book introduces the concept of m-Health, first coined by Robert S. H. Istepanian in 2003. The evolution of m-Health since then-how it was transformed from an academic concept to a global healthcare technology phenomenon-is discussed. Afterwards the authors describe in detail the basics of the three enabling scientific technological elements of m-Health (sensors, computing, and communications), and how each of these key ingredients has evolved and matured over the last decade. The book concludes with detailed discussion of the future of m-Health and presents future directions to potentially shape and transform healthcare services in the coming decades. In addition, this book: • Discusses the rapid evolution of m-Health in parallel with the maturing process of its enabling technologies, from bio-wearable sensors to the wireless and mobile communication technologies from IOT to 5G systems and beyond • Includes clinical examples and current studies, particularly in acute and chronic disease management, to illustrate some of the relevant medical aspects and clinical applications of m-Health • Describes current m-Health ecosystems and business models • Covers successful applications and deployment examples of m-Health in various global health settings, particularly in developing countries.

A systematic overview of the quickly developing field of bioengineering-with state-of-the-art modeling software! Computational Modeling and Simulation Examples in Bioengineering provides a comprehensive introduction to the emerging field of bioengineering. It provides the theoretical background necessary to simulating pathological conditions in the bones, muscles, cardiovascular tissue, and cancers, as well as lung and vertigo disease. The methodological approaches used for simulations include the finite element, dissipative particle dynamics, and lattice Boltzman. The text includes access to a state-of-the-art software package for simulating the theoretical problems. In this way, the book enhances the reader's learning capabilities in the field of biomedical engineering. The aim of this book is to provide concrete examples of applied modeling in biomedical engineering. Examples in a wide range of areas equip the reader with a foundation of knowledge regarding which problems can be modeled with which numerical methods. With more practical examples and more online software support than any competing text, this book organizes the field of computational bioengineering into an accessible and thorough introduction. Computational Modeling and Simulation Examples in Bioengineering: • Includes a state-of-the-art software package enabling readers to engage in hands-on modeling of the examples in the book • Provides a background on continuum and discrete modeling, along with equations and derivations for three key numerical methods • Considers examples in the modeling of bones, skeletal muscles, cartilage, tissue engineering, blood flow, plaque, and more • Explores stent deployment modeling as well as stent design and optimization techniques • Generates different examples of fracture fixation with respect to the advantages in medical practice applications Computational Modeling and Simulation Examples in Bioengineering is an excellent textbook for students of bioengineering, as well as a support for basic and clinical research. Medical doctors and other clinical professionals will also benefit from this resource and guide to the latest modeling techniques.

Reflects on developments in noninvasive electromyography, and includes advances and applications in signal detection, processing and interpretation. • Addresses EMG imaging technology together with the issue of decomposition of surface EMG • Includes advanced single and multi-channel techniques for information extraction from surface EMG signals • Presents the analysis and information extraction of surface EMG at various scales, from motor units to the concept of muscle synergies.

By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. • Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms • Sampling techniques for estimating evolutionary rates and generating molecular structures • Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations • End-of-chapter exercises.

Biomedical Signal Analysis Comprehensive resource covering recent developments, applications of current interest, and advanced techniques for biomedical signal analysis Biomedical Signal Analysis provides extensive insight into digital signal processing techniques for filtering, identification, characterization, classification, and analysis of biomedical signals with the aim of computer-aided diagnosis, taking a unique approach by presenting case studies encountered in the authors' research work. Each chapter begins with the statement of a biomedical signal problem, followed by a selection of real-life case studies and illustrations with the associated signals. Signal processing, modeling, or analysis techniques are then presented, starting with relatively simple "textbook" methods, followed by more sophisticated research-informed approaches. Each chapter concludes with solutions to practical applications. Illustrations of real-life biomedical signals and their derivatives are included throughout. The third edition expands on essential background material and advanced topics without altering the underlying pedagogical approach and philosophy of the successful first and second editions. The book is enhanced by a large number of study questions and laboratory exercises as well as an online repository with solutions to problems and data files for laboratory work and projects. Biomedical Signal Analysis provides theoretical and practical information on: • The origin and characteristics of several biomedical signals • Analysis of concurrent, coupled, and correlated processes, with applications in monitoring of sleep apnea • Filtering for removal of artifacts, random noise, structured noise, and physiological interference in signals generated by stationary, nonstationary, and cyclostationary processes • Detection and characterization of events, covering methods for QRS detection, identification of heart sounds, and detection of the dicrotic notch • Analysis of waveshape and waveform complexity • Interpretation and analysis of biomedical signals in the frequency domain • Mathematical, electrical, mechanical, and physiological modeling of biomedical signals and systems • Sophisticated analysis of nonstationary, multicomponent, and multisource signals using wavelets, time-frequency representations, signal decomposition, and dictionary-learning methods • Pattern classification and computer-aided diagnosis Biomedical Signal Analysis is an ideal learning resource for senior undergraduate and graduate engineering students. Introductory sections on signals, systems, and transforms make this book accessible to students in disciplines other than electrical engineering.

This book is the first of its kind to discuss error estimation with a model-based approach. From the basics of classifiers and error estimators to distributional and Bayesian theory, it covers important topics and essential issues pertaining to the scientific validity of pattern classification. “Error Estimation for Pattern Recognition” focuses on error estimation, which is a broad and poorly understood topic that reaches all research areas using pattern classification. It includes model-based approaches and discussions of newer error estimators such as bolstered and Bayesian estimators. This book was motivated by the application of pattern recognition to high-throughput data with limited replicates, which is a basic problem now appearing in many areas. The first two chapters cover basic issues in classification error estimation, such as definitions, test-set error estimation, and training-set error estimation. The remaining chapters in this book cover results on the performance and representation of training-set error estimators for various pattern classifiers. Additional features of the book include: • The latest results on the accuracy of error estimation • Performance analysis of re-substitution, cross-validation, and bootstrap error estimators using analytical and simulation approaches • Highly interactive computer-based exercises and end-of-chapter problems This is the first book exclusively about error estimation for pattern recognition.

A must-have compendium on biomedical telemetry for all biomedical professional engineers, researchers, and graduate students in the field. “Handbook of Biomedical Telemetry” describes the main components of a typical biomedical telemetry system, as well as its technical challenges. Written by a diverse group of experts in the field, it is filled with overviews, highly-detailed scientific analyses, and example applications of biomedical telemetry. The book also addresses technologies for biomedical sensing and design of biomedical telemetry devices with special emphasis on powering/integration issues and materials for biomedical telemetry applications. “Handbook of Biomedical Telemetry”: • Describes the main components of a typical biomedical telemetry system, along with the technical challenges • Discusses issues of spectrum regulations, standards, and interoperability-while major technical challenges related to advanced materials, miniaturization, and biocompatibility issues are also included • Covers body area electromagnetics, inductive coupling, antennas for biomedical telemetry, intra-body communications, non-RF communication links for biomedical telemetry (optical biotelemetry), as well as safety issues, human phantoms, and exposure assessment to high-frequency biotelemetry fields • Presents biosensor network topologies and standards; context-aware sensing and multi-sensor fusion; security and privacy issues in biomedical telemetry; and the connection between biomedical telemetry and telemedicine • Introduces clinical applications of Body Sensor Networks (BSNs) in addition to selected examples of wearable, implantable, ingestible devices, stimulator and integrated mobile healthcare system paradigms for monitoring and therapeutic intervention Covering biomedical telemetry devices, biosensor network topologies and standards, clinical applications, wearable and implantable devices, and the effects on the mobile healthcare system, this compendium is a must-have for professional engineers, researchers, and graduate students.