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Currents In Biomedical Signals Processing Methods And Applications
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Book Synopsis Currents in Biomedical Signals Processing - Methods and Applications by : Aleksandra Dagmara Kawala-Sterniuk
Download or read book Currents in Biomedical Signals Processing - Methods and Applications written by Aleksandra Dagmara Kawala-Sterniuk and published by Frontiers Media SA. This book was released on 2022-09-05 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Biomedical Signal and Image Processing by : Kayvan Najarian
Download or read book Biomedical Signal and Image Processing written by Kayvan Najarian and published by CRC Press. This book was released on 2016-04-19 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Biomedical Signal Processing for Healthcare Applications by : Varun Bajaj
Download or read book Biomedical Signal Processing for Healthcare Applications written by Varun Bajaj and published by CRC Press. This book was released on 2021-07-21 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Singular Spectrum Analysis of Biomedical Signals by : Saeid Sanei
Download or read book Singular Spectrum Analysis of Biomedical Signals written by Saeid Sanei and published by CRC Press. This book was released on 2015-12-23 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques by : Abdulhamit Subasi
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 458 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
Book Synopsis Signal Processing for Neuroscientists by : Wim van Drongelen
Download or read book Signal Processing for Neuroscientists written by Wim van Drongelen and published by Elsevier. This book was released on 2006-12-18 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Biomedical Signal Processing And Signal Modeling by : Bruce
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
Book Synopsis Practical Biomedical Signal Analysis Using MATLAB® by : Katarzyn J. Blinowska
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.
Book Synopsis Emerging Trends of Biomedical Circuits and Systems by : Mohamad Sawan
Download or read book Emerging Trends of Biomedical Circuits and Systems written by Mohamad Sawan and published by . This book was released on 2021-12-09 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Signals and Systems Analysis In Biomedical Engineering by : Robert B. Northrop
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
Book Synopsis Advances in Neural Signal Processing by : Ramana Vinjamuri
Download or read book Advances in Neural Signal Processing written by Ramana Vinjamuri and published by BoD – Books on Demand. This book was released on 2020-09-09 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural signal processing is a specialized area of signal processing aimed at extracting information or decoding intent from neural signals recorded from the central or peripheral nervous system. This has significant applications in the areas of neuroscience and neural engineering. These applications are famously known in the area of brain–machine interfaces. This book presents recent advances in this flourishing field of neural signal processing with demonstrative applications.
Book Synopsis Biomedical Signal Processing and Artificial Intelligence in Healthcare by : Walid A. Zgallai
Download or read book Biomedical Signal Processing and Artificial Intelligence in Healthcare written by Walid A. Zgallai and published by Academic Press. This book was released on 2020-07-29 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biomedical Signal Processing and Artificial Intelligence in Healthcare is a new volume in the Developments in Biomedical Engineering and Bioelectronics series. This volume covers the basics of biomedical signal processing and artificial intelligence. It explains the role of machine learning in relation to processing biomedical signals and the applications in medicine and healthcare. The book provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of Deep Learning, Neural Networks, and the implications of the expansion of artificial intelligence is covered. Biomedical Images are also introduced and processed, including segmentation, classification, and detection. This book covers different aspects of signals, from the use of hardware and software, and making use of artificial intelligence in problem solving.Dr Zgallai's book has up to date coverage where readers can find the latest information, easily explained, with clear examples and illustrations. The book includes examples on the application of signal and image processing employing artificial intelligence to Alzheimer, Parkinson, ADHD, autism, and sleep disorders, as well as ECG and EEG signals. Developments in Biomedical Engineering and Bioelectronics is a 10-volume series which covers recent developments, trends and advances in this field. Edited by leading academics in the field, and taking a multidisciplinary approach, this series is a forum for cutting-edge, contemporary review articles and contributions from key 'up-and-coming' academics across the full subject area. The series serves a wide audience of university faculty, researchers and students, as well as industry practitioners. - Coverage of the subject area and the latest advances and applications in biomedical signal processing and Artificial Intelligence - Contributions by recognized researchers and field leaders - On-line presentations, tutorials, application and algorithm examples
Book Synopsis Analog IC Design Techniques for Nanopower Biomedical Signal Processing by : Chutham Sawigun
Download or read book Analog IC Design Techniques for Nanopower Biomedical Signal Processing written by Chutham Sawigun and published by CRC Press. This book was released on 2022-09-01 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the requirements for low power consumption and very small physical dimensions in portable, wearable and implantable medical devices are calling for integrated circuit design techniques using MOSFETs operating in the subthreshold regime, this book first revisits some well-known circuit techniques that use CMOS devices biased in subthreshold in order to establish nanopower integrated circuit designs. Based on the these findings, this book shows the development of a class-AB current-mode sample-and-hold circuit with an order of magnitude improvement in its figure of merit compared to other state-of-the-art designs. Also, the concepts and design procedures of 1) single-branch filters 2) follower-integrator-based lowpass filters and 3) modular transconductance reduction techniques for very low frequency filters are presented. Finally, to serve the requirement of a very large signal swing in an energy-based action potential detector, a nanopower class-AB current-mode analog multiplier is designed to handle input current amplitudes of more than 10 times the bias current of the multiplier circuit. The invented filter circuits have been fabricated in a standard 0.18 μ CMOS process in order to verify our circuit concepts and design procedures. Their experimental results are reported.
Book Synopsis ECG Signal Processing, Classification and Interpretation by : Adam Gacek
Download or read book ECG Signal Processing, Classification and Interpretation written by Adam Gacek and published by Springer Science & Business Media. This book was released on 2011-09-18 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. The text is self-contained, addressing concepts, methodology, algorithms, and case studies and applications, providing the reader with the necessary background augmented with step-by-step explanation of the more advanced concepts. It is structured in three parts: Part I covers the fundamental ideas of computational intelligence together with the relevant principles of data acquisition, morphology and use in diagnosis; Part II deals with techniques and models of computational intelligence that are suitable for signal processing; and Part III details ECG system-diagnostic interpretation and knowledge acquisition architectures. Illustrative material includes: brief numerical experiments; detailed schemes, exercises and more advanced problems.
Book Synopsis Biomedical Signal Processing by : Ganesh R. Naik
Download or read book Biomedical Signal Processing written by Ganesh R. Naik and published by CRC Press. This book was released on 2023-09-27 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the theoretical basis and applications of biomedical signal analysis and processing. Initially, the nature of the most common biomedical signals, such as electroencephalography, electromyography, electrocardiography and others, is described. The theoretical basis of linear signal processing is summarized, with continuous and discrete representation, linear filters and convolutions, Fourier and Wavelets transforms. Machine learning concepts are also presented, from classic methods to deep neural networks. Finally, several applications in neuroscience are presented and discussed, involving diagnosis and therapy, in addition to other applications. Features: Explains signal processing of neuroscience applications using modern data science techniques. Provides comprehensible review on biomedical signals nature and acquisition aspects. Focusses on selected applications of neurosciences, cardiovascular and muscle-related biomedical areas. Includes computational intelligence, machine learning and biomedical signal processing and analysis. Reviews theoretical basis of deep learning and state-of-the-art biomedical signal processing and analysis. This book is aimed at researchers, graduate students in biomedical signal processing, signal processing, electrical engineering, neuroscience and computer science.
Book Synopsis Advances in Biomedical Engineering by : Pascal Verdonck
Download or read book Advances in Biomedical Engineering written by Pascal Verdonck and published by Elsevier. This book was released on 2008-09-11 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this essential reference is to bring together the interdisciplinary areas of biomedical engineering education. Contributors review the latest advances in biomedical engineering research through an educational perspective, making the book useful for students and professionals alike. Topics range from biosignal analysis and nanotechnology to biophotonics and cardiovascular medical devices. - Provides an educational review of recent advances - Focuses on biomedical high technology - Features contributions from leaders in the field
Book Synopsis Leveraging Data Science for Global Health by : Leo Anthony Celi
Download or read book Leveraging Data Science for Global Health written by Leo Anthony Celi and published by Springer Nature. This book was released on 2020-07-31 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
