Biomedical Signal and Image Processing

Biomedical Signal and Image Processing
Author: Kayvan Najarian
Publisher: CRC Press
Total Pages: 411
Release: 2016-04-19
Genre: Medical
ISBN: 1439870349

Written for senior-level and first year graduate students in biomedical signal and image processing, this book describes fundamental signal and image processing techniques that are used to process biomedical information. The book also discusses application of these techniques in the processing of some of the main biomedical signals and images, such as EEG, ECG, MRI, and CT. New features of this edition include the technical updating of each chapter along with the addition of many more examples, the majority of which are MATLAB based.

Biomedical Signal Processing for Healthcare Applications

Biomedical Signal Processing for Healthcare Applications
Author: Varun Bajaj
Publisher: CRC Press
Total Pages: 336
Release: 2021-07-21
Genre: Technology & Engineering
ISBN: 1000413306

This book examines the use of biomedical signal processing—EEG, EMG, and ECG—in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights of Biomedical Signal Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications. FEATURES Examines modeling and acquisition of biomedical signals of different disorders Discusses CAD-based analysis of diagnosis useful for healthcare Includes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCG Includes case studies and research directions, including novel approaches used in advanced healthcare systems This book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

Singular Spectrum Analysis of Biomedical Signals

Singular Spectrum Analysis of Biomedical Signals
Author: Saeid Sanei
Publisher: CRC Press
Total Pages: 270
Release: 2015-12-23
Genre: Medical
ISBN: 1466589280

Recent advancements in signal processing and computerised methods are expected to underpin the future progress of biomedical research and technology, particularly in measuring and assessing signals and images from the human body. This book focuses on singular spectrum analysis (SSA), an effective approach for single channel signal analysis, and its

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques
Author: Abdulhamit Subasi
Publisher: Academic Press
Total Pages: 458
Release: 2019-03-16
Genre: Medical
ISBN: 0128176733

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

Signal Processing for Neuroscientists

Signal Processing for Neuroscientists
Author: Wim van Drongelen
Publisher: Elsevier
Total Pages: 319
Release: 2006-12-18
Genre: Science
ISBN: 008046775X

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the 'golden trio' in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. - Multiple color illustrations are integrated in the text - Includes an introduction to biomedical signals, noise characteristics, and recording techniques - Basics and background for more advanced topics can be found in extensive notes and appendices - A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Advanced Biosignal Processing

Advanced Biosignal Processing
Author: Amine Nait-Ali
Publisher: Springer Science & Business Media
Total Pages: 384
Release: 2009-04-21
Genre: Technology & Engineering
ISBN: 354089506X

Generally speaking, Biosignals refer to signals recorded from the human body. They can be either electrical (e. g. Electrocardiogram (ECG), Electroencephalogram (EEG), Electromyogram (EMG), etc. ) or non-electrical (e. g. breathing, movements, etc. ). The acquisition and processing of such signals play an important role in clinical routines. They are usually considered as major indicators which provide clinicians and physicians with useful information during diagnostic and monitoring processes. In some applications, the purpose is not necessarily medical. It may also be industrial. For instance, a real-time EEG system analysis can be used to control and analyze the vigilance of a car driver. In this case, the purpose of such a system basically consists of preventing crash risks. Furthermore, in certain other appli- tions,asetof biosignals (e. g. ECG,respiratorysignal,EEG,etc. ) can be used toc- trol or analyze human emotions. This is the case of the famous polygraph system, also known as the “lie detector”, the ef ciency of which remains open to debate! Thus when one is dealing with biosignals, special attention must be given to their acquisition, their analysis and their processing capabilities which constitute the nal stage preceding the clinical diagnosis. Naturally, the diagnosis is based on the information provided by the processing system.

Biomedical Signal Processing And Signal Modeling

Biomedical Signal Processing And Signal Modeling
Author: Bruce
Publisher: John Wiley & Sons
Total Pages: 540
Release: 2007-01-20
Genre:
ISBN: 9788126511112

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

Emerging Trends of Biomedical Circuits and Systems

Emerging Trends of Biomedical Circuits and Systems
Author: Mohamad Sawan
Publisher:
Total Pages: 210
Release: 2021-12-09
Genre: Technology & Engineering
ISBN: 9781680839067

Science and engineering disciplines are provoking fundamental and applied discoveries in numerous applications, such as to deeply understand brain functions, precisely diagnose diseases, and to then properly address these. The later advances call upon biomedical integrated circuits and systems (BioCAS) to provide needed research tools. In fact, with the increase of the personalized healthcare market and BioCAS featuring wearability, implantability and intelligence, it has become significantly more important to address these emerging trends. These circuits and systems deal with various signals and images such as electrophysiological, electrochemical, optical, and magnetic, which require various front-end circuits to acquire signals and usually cancel out the noise. With the booming artificial intelligence methods, these biosignals became mandatory for the monitoring, detection, diagnosis and even prediction of diseases for example.This monograph focusses on the current research activities and emerging trends that relate to the above-mentioned functionalities, and it should be of interest to students, researchers and engineers active in the fields related to Circuits and Systems for Biomedical Engineering.Section I is a summary of the main BioCAS research interests, and in Section II various biosignal acquisition circuits techniques are discussed. In Section III the authors cover circuits for biosignal processing, with emphasis on the newly emerging artificial intelligence. Sections IV and V contain a review of wireless power harvesting and communication circuits. Sections VI and VII represent circuits that help miniaturizing biomedical imaging systems, and other systems intended for the detection of chemical and molecular assays. Section VIII describes one of the main neural prostheses intended to address vision disorders, whilst the last section reviews electrode-tissue interfaces that essentially bridge the circuits and systems with the human body.

Practical Biomedical Signal Analysis Using MATLAB®

Practical Biomedical Signal Analysis Using MATLAB®
Author: Katarzyn J. Blinowska
Publisher: CRC Press
Total Pages: 326
Release: 2011-09-12
Genre: Medical
ISBN: 1439812020

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.