Advanced Biosignal Processing and Diagnostic Methods

Advanced Biosignal Processing and Diagnostic Methods PDF

Author: Christoph Hintermüller

Publisher: BoD – Books on Demand

Published: 2016-07-21

Total Pages: 150

ISBN-13: 9535125192

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Personal health and well-being was and is important for all individuals. This includes the way people are living, what they do to stay healthy as well as a profound, well-informed diagnosis and appropriate treatment in case of disease. To achieve these goals, modern medicine is provided with a large variety of tools to assess a patient's health state and collect the information required for a proper diagnosis and treatment, which is tailored to the patient's needs. Many of these available tools use signals either generated by the human body, for example, electroencephalogram (EEG) and electrocardiogram (ECG), or by interacting with the human body while traversing it like microwaves or reflected visible light that is recorded by a video camera. The biosignals recorded by the available and newly developed methods have to be processed to extract the information about the patient's condition and, analyzed tissue and cells. This book presents a small selection of the recent developments in the field of biosignal processing. The covered diagnostic tools and methods include the assessment of respiratory state through gait analysis, the contactless monitoring of cardiovascular and respiratory parameters using microwaves, a non-linear approach to extract the fetal ECG from non-invasive abdominal recordings, identification of epileptic networks from pre-surgical neurophysiological recordings and an improved method to obtain and validate the copy number alterations parameter, which are considered an important marker in cancer classification.

Advanced Biosignal Processing

Advanced Biosignal Processing PDF

Author: Amine Nait-Ali

Publisher: Springer Science & Business Media

Published: 2009-04-21

Total Pages: 384

ISBN-13: 354089506X

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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.

Biosignal Processing

Biosignal Processing PDF

Author: Hualou Liang

Publisher: CRC Press

Published: 2012-10-17

Total Pages: 202

ISBN-13: 1439871442

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With the rise of advanced computerized data collection systems, monitoring devices, and instrumentation technologies, large and complex datasets accrue as an inevitable part of biomedical enterprise. The availability of these massive amounts of data offers unprecedented opportunities to advance our understanding of underlying biological and physiol

Advanced Methods of Biomedical Signal Processing

Advanced Methods of Biomedical Signal Processing PDF

Author: Sergio Cerutti

Publisher: John Wiley & Sons

Published: 2011-06-09

Total Pages: 612

ISBN-13: 1118007735

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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.

Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing

Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing PDF

Author: Adel Al-Jumaily

Publisher: CRC Press

Published: 2024-02-29

Total Pages: 502

ISBN-13: 100383812X

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This book contains up-to-date noninvasive monitoring and diagnosing systems closely developed by a set of scientists, engineers, and physicians. The chapters are the results of different biomedical projects and theoretical studies that were coupled by simulations and real-world data. Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing provides a multifaceted view of various biomedical and clinical approaches to health monitoring systems. The authors introduce advanced signal- and image-processing techniques as well as other noninvasive monitoring and diagnostic systems such as inertial sensors in wearable devices and novel algorithm-based hybrid learning systems for biosignal processing. The book includes a discussion of designing electronic circuits and systems for biomedical applications and analyzes several issues related to real-world data and how they relate to health technology including ECG signal monitoring and processing in the operating room. The authors also include detailed discussions of different systems for monitoring various conditions and diseases including sleep apnea, skin cancer, deep vein thrombosis, and prosthesis controls. This book is intended for a wide range of readers including scientists, researchers, physicians, and electronics and biomedical engineers. It will cover the gap between theory and real life applications.

Advanced Methods in Biomedical Signal Processing and Analysis

Advanced Methods in Biomedical Signal Processing and Analysis PDF

Author: Kunal Pal

Publisher: Academic Press

Published: 2022-09-07

Total Pages: 434

ISBN-13: 0323859542

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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

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging PDF

Author: Nilanjan Dey

Publisher: Academic Press

Published: 2018-11-30

Total Pages: 345

ISBN-13: 012816087X

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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

Biomedical Signal Analysis

Biomedical Signal Analysis PDF

Author: Rangaraj M. Rangayyan

Publisher: John Wiley & Sons

Published: 2024-02-19

Total Pages: 724

ISBN-13: 1119825873

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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.

Biomedical Signal Analysis

Biomedical Signal Analysis PDF

Author: Rangaraj M. Rangayyan

Publisher: John Wiley & Sons

Published: 2015-04-24

Total Pages: 722

ISBN-13: 1119067936

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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

Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing

Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing PDF

Author: Adel Al-Jumaily

Publisher: CRC Press

Published: 2024-02-29

Total Pages: 475

ISBN-13: 1003838103

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This book contains up-to-date noninvasive monitoring and diagnosing systems closely developed by a set of scientists, engineers, and physicians. The chapters are the results of different biomedical projects and theoretical studies that were coupled by simulations and real-world data. Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing provides a multifaceted view of various biomedical and clinical approaches to health monitoring systems. The authors introduce advanced signal- and image-processing techniques as well as other noninvasive monitoring and diagnostic systems such as inertial sensors in wearable devices and novel algorithm-based hybrid learning systems for biosignal processing. The book includes a discussion of designing electronic circuits and systems for biomedical applications and analyzes several issues related to real-world data and how they relate to health technology including ECG signal monitoring and processing in the operating room. The authors also include detailed discussions of different systems for monitoring various conditions and diseases including sleep apnea, skin cancer, deep vein thrombosis, and prosthesis controls. This book is intended for a wide range of readers including scientists, researchers, physicians, and electronics and biomedical engineers. It will cover the gap between theory and real life applications.