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Author: Bruce
Publisher: John Wiley & Sons
ISBN: 9788126511112
Category :
Languages : en
Pages : 540
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Book Description
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
Author: Bruce
Publisher: John Wiley & Sons
ISBN: 9788126511112
Category :
Languages : en
Pages : 540
Get Book Here
Book Description
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
Author: Suresh R. Devasahayam
Publisher: Springer Science & Business Media
ISBN: 1461453321
Category : Technology & Engineering
Languages : en
Pages : 395
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Book Description
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.
Author: Giuseppe Nardulli
Publisher: World Scientific
ISBN: 9814489441
Category : Technology & Engineering
Languages : en
Pages : 293
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Book Description
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)
Author: Kunal Pal
Publisher: Academic Press
ISBN: 0323859542
Category : Technology & Engineering
Languages : en
Pages : 434
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Book Description
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
Author: Abdulhamit Subasi
Publisher: Academic Press
ISBN: 0128176733
Category : Medical
Languages : en
Pages : 458
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Book Description
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
Author: Giuseppe Nardulli
Publisher: World Scientific
ISBN: 9789810248437
Category : Medical
Languages : en
Pages : 300
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Book Description
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)
Author: Rangaraj M. Rangayyan
Publisher: John Wiley & Sons
ISBN: 1119068010
Category : Science
Languages : en
Pages : 717
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Book Description
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
Author: Robert B. Northrop
Publisher: CRC Press
ISBN: 1439812535
Category : Medical
Languages : en
Pages : 656
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Book Description
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
Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 012816087X
Category : Science
Languages : en
Pages : 348
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Book Description
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
Author: Rangaraj M. Rangayyan
Publisher: Wiley-IEEE Press
ISBN:
Category : Medical
Languages : en
Pages : 560
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Book Description
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
