Download or read book Modelling Biomedical Signals written by Giuseppe Nardulli and published by World Scientific. This book was released on 2002-05-24 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years, concepts and methodologies initially developed in physics have found high applicability in many different areas. This book, a result of cross-disciplinary interaction among physicists, biologists and physicians, covers several topics where methods and approaches rooted in physics are successfully applied to analyze and to model biomedical data. Included are papers on physiological rhythms and synchronization phenomena, gene expression patterns, the immune system, decision support systems in medical science, protein folding and protein crystallography. The volume can be used as a valuable reference for graduate students and researchers at the interface of physics, biology and medicine.The proceedings have been selected for coverage in:• Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)
Download or read book Biomedical Signal Processing And Signal Modeling written by Bruce and published by John Wiley & Sons. This book was released on 2007-01-20 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unique framework for understanding signal processing of biomedical signals and what it tells us about signal sources and their behavior in response to perturbation. Using a modeling-based approach, the author shows how to perform signal processing by developing and manipulating a model of the signal source, providing a logical, coherent basis for recognizing signal types and for tackling the special challenges posed by biomedical signals-including the effects of noise on the signal, changes in basic properties, or the fact that these signals contain large stochastic components and may even be fractal or chaotic. Each chapter begins with a detailed biomedical example, illustrating the methods under discussion and highlighting the interconnection between the theoretical concepts and applications. · The Nature of Biomedical Signals· Memory and Correlation· The Impulse Response· Frequency Response· Modeling Continuous-Time Signals as Sums of Sine Waves· Responses of Linear Continuous-Time Filters to Arbitrary Inputs· Modeling Signals as Sums of Discrete-Time Sine Waves· Noise Removal and Signal Compensation· Modeling Stochastic Signals as Filtered White Noise· Scaling and Long-Term Memory· Nonlinear Models of Signals· Assessing Stationarity and Reproducibility
Download or read book Signals and Systems in Biomedical Engineering written by Suresh R. Devasahayam and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past few years Biomedical Engineering has received a great deal of attention as one of the emerging technologies in the last decade and for years to come, as witnessed by the many books, conferences, and their proceedings. Media attention, due to the applications-oriented advances in Biomedical Engineering, has also increased. Much of the excitement comes from the fact that technology is rapidly changing and new technological adventures become available and feasible every day. For many years the physical sciences contributed to medicine in the form of expertise in radiology and slow but steady contributions to other more diverse fields, such as computers in surgery and diagnosis, neurology, cardiology, vision and visual prosthesis, audition and hearing aids, artificial limbs, biomechanics, and biomaterials. The list goes on. It is therefore hard for a person unfamiliar with a subject to separate the substance from the hype. Many of the applications of Biomedical Engineering are rather complex and difficult to understand even by the not so novice in the field. Much of the hardware and software tools available are either too simplistic to be useful or too complicated to be understood and applied. In addition, the lack of a common language between engineers and computer scientists and their counterparts in the medical profession, sometimes becomes a barrier to progress.
Download or read book Biomedical Signal Analysis written by Rangaraj M. Rangayyan and published by John Wiley & Sons. This book was released on 2015-04-24 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a pedagogical examination of basic and advanced topics accompanied by over 350 figures and illustrations. Wide range of filtering techniques presented to address various applications 800 mathematical expressions and equations Practical questions, problems and laboratory exercises Includes fractals and chaos theory with biomedical applications
Download or read book Modelling Biomedical Signals written by Giuseppe Nardulli and published by World Scientific. This book was released on 2002 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years, concepts and methodologies initially developed in physics have found high applicability in many different areas. This book, a result of cross-disciplinary interaction among physicists, biologists and physicians, covers several topics where methods and approaches rooted in physics are successfully applied to analyze and to model biomedical data. Included are papers on physiological rhythms and synchronization phenomena, gene expression patterns, the immune system, decision support systems in medical science, protein folding and protein crystallography. The volume can be used as a valuable reference for graduate students and researchers at the interface of physics, biology and medicine.The proceedings have been selected for coverage in: ? Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)
Download or read book Modelling and Analysis of Active Biopotential Signals in Healthcare Volume 1 written by Sinha BAJAJ and published by IOP Publishing Limited. This book was released on 2020-08-25 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on analysis and modelling of active bio potential signals addressing the real time challenges in biomedical signal processing used in a variety of applications such as analysis, classification and identification of different disorders in healthcare systems.
Download or read book Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and published by Academic Press. This book was released on 2019-03-16 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction Explains how to apply machine learning techniques to EEG, ECG and EMG signals Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series
Download or read book Advanced Methods of Biomedical Signal Processing written by Sergio Cerutti and published by John Wiley & Sons. This book was released on 2011-06-09 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Machine Learning in Bio Signal Analysis and Diagnostic Imaging written by Nilanjan Dey and published by Academic Press. This book was released on 2018-11-30 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains
Download or read book Biomedical Signal Analysis written by Rangaraj M. Rangayyan and published by Wiley-IEEE Press. This book was released on 2002 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of techniques to analyze biomedical signals, such as electro-cardiograms, has dramatically affected countless lives by making possible improved noninvasive diagnosis, online monitoring of critically ill patients, and rehabilitation and sensory aids for the handicapped. Rangaraj Rangayyan supplies a practical, hands-on field guide to this constantly evolving technology in Biomedical Signal Analysis, focusing on the diagnostic challenges that medical professionals continue to face. Dr. Rangayyan applies a problem-solving approach to his study. Each chapter begins with the statement of a different biomedical signal problem, followed by a selection of real-life case studies and the associated signals. Signal processing, modeling, or analysis techniques are then presented, starting with relatively simple "textbook" methods, followed by more sophisticated research approaches. The chapter concludes with one or more application solutions; illustrations of real-life biomedical signals and their derivatives are included throughout. Among the topics addressed are: Concurrent, coupled, and correlated processes Filtering for removal of artifacts Event detection and characterization Frequency-domain characterization Modeling biomedical systems Analysis of nonstationary signals Pattern classification and diagnostic decision The chapters also present a number of laboratory exercises, study questions, and problems to facilitate preparation for class examinations and practical applications. Biomedical Signal Analysis provides a definitive resource for upper-level under-graduate and graduate engineering students, as well as for practicing engineers, computer scientists, information technologists, medical physicists, and data processing specialists. An authoritative assessment of the problems and applications of biomedical signals, rooted in practical case studies
Download or read book Advanced Methods in Biomedical Signal Processing and Analysis written by Kunal Pal and published by Academic Press. This book was released on 2022-09-07 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques. Gives advanced methods in signal processing Includes machine and deep learning methods Presents experimental case studies
Download or read book Practical Biomedical Signal Analysis Using MATLAB written by Katarzyn J. Blinowska and published by CRC Press. This book was released on 2011-09-12 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Biomedical Signal Analysis Using MATLAB® presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and different types of data. The first several chapters of the text describe signal analysis techniques—including the newest and most advanced methods—in an easy and accessible way. MATLAB routines are listed when available and freely available software is discussed where appropriate. The final chapter explores the application of the methods to a broad range of biomedical signals, highlighting problems encountered in practice. A unified overview of the field, this book explains how to properly use signal processing techniques for biomedical applications and avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods.
Download or read book Signals and Systems Analysis In Biomedical Engineering written by Robert B. Northrop and published by CRC Press. This book was released on 2016-04-19 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first edition of this text, based on the author's 30 years of teaching and research on neurosensory systems, helped biomedical engineering students and professionals strengthen their skills in the common network of applied mathematics that ties together the diverse disciplines that comprise this field. Updated and revised to include new materia
Download or read book Biomedical Signal Analysis written by Rangaraj M. Rangayyan and published by John Wiley & Sons. This book was released on 2024-02-19 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Signals and Systems in Biomedical Engineering written by Suresh R. Devasahayam and published by Springer Science & Business Media. This book was released on 2012-11-08 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of digital signal processing is ubiquitous in the field of physiology and biomedical engineering. The application of such mathematical and computational tools requires a formal or explicit understanding of physiology. Formal models and analytical techniques are interlinked in physiology as in any other field. This book takes a unitary approach to physiological systems, beginning with signal measurement and acquisition, followed by signal processing, linear systems modelling, and computer simulations. The signal processing techniques range across filtering, spectral analysis and wavelet analysis. Emphasis is placed on fundamental understanding of the concepts as well as solving numerical problems. Graphs and analogies are used extensively to supplement the mathematics. Detailed models of nerve and muscle at the cellular and systemic levels provide examples for the mathematical methods and computer simulations. Several of the models are sufficiently sophisticated to be of value in understanding real world issues like neuromuscular disease. This second edition features expanded problem sets and a link to extra downloadable material.
Download or read book Practical Biomedical Signal Analysis Using MATLAB written by Katarzyna J. Blinowska and published by CRC Press. This book was released on 2021-10-18 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the latest cutting-edge techniques in biomedical signal processing while presenting a coherent treatment of various signal processing methods and applications, this second edition of Practical Biomedical Signal Analysis Using MATLAB® also offers practical guidance on which procedures are appropriate for a given task and different types of data. It begins by describing signal analysis techniques—including the newest and most advanced methods in the field—in an easy and accessible way, illustrating them with Live Script demos. MATLAB® routines are listed when available, and freely available software is discussed where appropriate. The book concludes by exploring the applications of the methods to a broad range of biomedical signals while highlighting common problems encountered in practice. These chapters have been updated throughout and include new sections on multiple channel analysis and connectivity measures, phase-amplitude analysis, functional near-infrared spectroscopy, fMRI (BOLD) signals, wearable devices, multimodal signal analysis, and brain-computer interfaces. By providing a unified overview of the field, this book explains how to integrate signal processing techniques in biomedical applications properly and explores how to avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods. It will be an excellent guide for graduate students studying biomedical engineering and practicing researchers in the field of biomedical signal analysis. Features: Fully updated throughout with new achievements, technologies, and methods and is supported with over 40 original MATLAB Live Scripts illustrating the discussed techniques, suitable for self-learning or as a supplement to college courses Provides a practical comparison of the advantages and disadvantages of different approaches in the context of various applications Applies the methods to a variety of signals, including electric, magnetic, acoustic, and optical Katarzyna J. Blinowska is a Professor emeritus at the University of Warsaw, Poland, where she was director of Graduate Studies in Biomedical Physics and head of the Department of Biomedical Physics. Currently, she is employed at the Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. She has been at the forefront in developing new advanced time-series methods for research and clinical applications. Jarosław Żygierewicz is a Professor at the University of Warsaw, Poland. His research focuses on developing methods for analyzing EEG and MEG signals, brain-computer interfaces, and applications of machine learning in signal processing and classification.
Download or read book Nonlinear Biomedical Signal Processing Volume 2 written by Metin Akay and published by Wiley-IEEE Press. This book was released on 2000-09-20 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher description: Biomedical / Electrical Engineering Nonlinear Biomedical Signal Processing Volume I: Fuzzy Logic, Neural Networks, and New Algorithms A volume in the IEEE Press Series on Biomedical Engineering Metin Akay, Series Editor For the first time, eleven experts in the fields of signal processing and biomedical engineering have contributed to an edition on the newest theories and applications of fuzzy logic, neural networks, and algorithms in biomedicine. Nonlinear Biomedical Signal Processing, Volume I provides comprehensive coverage of nonlinear signal processing techniques. In the last decade, theoretical developments in the concept of fuzzy logic have led to several new approaches to neural networks. This compilation delivers plenty of real-world examples for a variety of implementations and applications of nonlinear signal processing technologies to biomedical problems. Included here are discussions that combine the various structures of Kohenen, Hopfield, and multiple-layer "designer" networks with other approaches to produce hybrid systems. Comparative analysis is made of methods of genetic, back-propagation, Bayesian, and other learning algorithms. Topics covered include: * Uncertainty management * Analysis of biomedical signals * A guided tour of neural networks * Application of algorithms to EEG and heart rate variability signals * Event detection and sample stratification in genomic sequences * Applications of multivariate analysis methods to measure glucose concentration Nonlinear Biomedical Signal Processing, Volume I is a valuable reference tool for medical researchers, medical faculty and advanced graduate student, s as well as for practicing biomedical engineers. Nonlinear Biomedical Signal Processing, Volume I is an excellent companion to Nonlinear Biomedical Signal Processing, Volume II: Dynamic Analysis and Modeling.
