Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare
Author: Sridhar Krishnan
Publsiher: Academic Press
Total Pages: 334
Release: 2021-06-23
ISBN 10: 012813173X
ISBN 13: 9780128131732
Language: EN, FR, DE, ES & NL

Biomedical Signal Analysis for Connected Healthcare Book Review:

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare. Provides comprehensive coverage of biomedical engineering, technologies, and healthcare applications of various physiological signals Covers vital signals, including ECG, EEG, EMG and body sounds Includes case studies and MATLAB code for selected applications

Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare
Author: Sridhar Krishnan
Publsiher: Elsevier
Total Pages: 334
Release: 2021-07-09
ISBN 10: 0128130865
ISBN 13: 9780128130865
Language: EN, FR, DE, ES & NL

Biomedical Signal Analysis for Connected Healthcare Book Review:

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare. Provides comprehensive coverage of biomedical engineering, technologies, and healthcare applications of various physiological signals Covers vital signals, including ECG, EEG, EMG and body sounds Includes case studies and MATLAB code for selected applications

Biomedical Signal Processing for Healthcare Applications

Biomedical Signal Processing for Healthcare Applications
Author: Varun Bajaj,G. R. Sinha,Chinmay Chakraborty
Publsiher: CRC Press
Total Pages: 336
Release: 2021-07-21
ISBN 10: 1000413306
ISBN 13: 9781000413304
Language: EN, FR, DE, ES & NL

Biomedical Signal Processing for Healthcare Applications Book Review:

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.

Biomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare
Author: Walid A. Zgallai
Publsiher: Academic Press
Total Pages: 268
Release: 2020-07-29
ISBN 10: 0128189479
ISBN 13: 9780128189474
Language: EN, FR, DE, ES & NL

Biomedical Signal Processing and Artificial Intelligence in Healthcare Book Review:

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.

Digital Health Approach for Predictive Preventive Personalised and Participatory Medicine

Digital Health Approach for Predictive  Preventive  Personalised and Participatory Medicine
Author: Lotfi Chaari
Publsiher: Springer
Total Pages: 88
Release: 2019-07-10
ISBN 10: 3030118002
ISBN 13: 9783030118006
Language: EN, FR, DE, ES & NL

Digital Health Approach for Predictive Preventive Personalised and Participatory Medicine Book Review:

This collection, entitled Digital Health for Predictive, Preventive, Personalized and Participatory Medicine contains the proceedings of the first International conference on digital healthtechnologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools can be used for healthcare. For instance, the use of connected objects to monitor physiological parameters is discussed. Moreover, even if compressed sensing is nowadays a common acquisition technique, its use for IoT is presented in this collection through one of the pioneer works in the field. In addition, the use of AI for epileptic seizure detection is also discussed as being one of the major concerns of predictive medicine both in industrialized and low-income countries. This work is edited by Prof. Lotfi Chaari, professor at the University of Sfax, and previously at the University of Toulouse. This work comes after more than ten years of expertise in the biomedical signal and image processing field.

Biomedical Signal Analysis

Biomedical Signal Analysis
Author: Rangaraj M. Rangayyan
Publsiher: John Wiley & Sons
Total Pages: 720
Release: 2015-04-24
ISBN 10: 1119067936
ISBN 13: 9781119067931
Language: EN, FR, DE, ES & NL

Biomedical Signal Analysis Book Review:

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

Practical Biomedical Signal Analysis Using MATLAB

Practical Biomedical Signal Analysis Using MATLAB
Author: Katarzyn J. Blinowska,Jaroslaw Zygierewicz
Publsiher: CRC Press
Total Pages: 324
Release: 2011-09-12
ISBN 10: 1439812020
ISBN 13: 9781439812020
Language: EN, FR, DE, ES & NL

Practical Biomedical Signal Analysis Using MATLAB Book Review:

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.

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare
Author: Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar
Publsiher: Academic Press
Total Pages: 290
Release: 2021-04-26
ISBN 10: 012823217X
ISBN 13: 9780128232170
Language: EN, FR, DE, ES & NL

Machine Learning and the Internet of Medical Things in Healthcare Book Review:

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies

Health Monitoring Systems

Health Monitoring Systems
Author: Rajarshi Gupta,Dwaipayan Biswas
Publsiher: CRC Press
Total Pages: 320
Release: 2019-11-21
ISBN 10: 0429532555
ISBN 13: 9780429532559
Language: EN, FR, DE, ES & NL

Health Monitoring Systems Book Review:

Remote health monitoring using wearable sensors is an important research area involving several key steps: physiological parameter sensing and data acquisition, data analysis, data security, data transmission to caregivers, and clinical intervention, all of which play a significant role to form a closed loop system. Subject-specific behavioral and clinical traits, coupled with individual physiological differences, necessitate a personalized healthcare delivery model for around-the-clock monitoring within the home environment. Cardiovascular disease monitoring is an illustrative application domain where research has been instrumental in enabling a personalized closed-loop monitoring system, which has been showcased in this book. Health Monitoring Systems: An Enabling Technology for Patient Care provides a holistic overview of state-of-the-art monitoring systems facilitated by Internet of Things (IoT) technology. The book lists out the details on biomedical signal acquisition, processing, and data security, the fundamental building blocks towards an ambulatory health monitoring infrastructure. The fundamentals have been complimented with other relevant topics including applications which provide an in-depth view on remote health monitoring systems. Key Features: Presents examples of state-of-the-art health monitoring systems using IoT infrastructure Covers the full spectrum of physiological sensing, data acquisition, processing, and data security Provides relevant example applications demonstrating the benefits of technological advancements aiding disease prognosis This book serves as a beginner’s guide for engineering students of electrical and computer science, practicing engineers, researchers, and scientists who are interested in having an overview of pervasive health monitoring systems using body-worn sensors operating outside the hospital environment. It could also be recommended as a reference for a graduate or master’s level course on biomedical instrumentation and signal processing.

Signal Processing and Machine Learning for Biomedical Big Data

Signal Processing and Machine Learning for Biomedical Big Data
Author: Ervin Sejdic,Tiago H. Falk
Publsiher: CRC Press
Total Pages: 606
Release: 2018-07-04
ISBN 10: 1351061216
ISBN 13: 9781351061216
Language: EN, FR, DE, ES & NL

Signal Processing and Machine Learning for Biomedical Big Data Book Review:

This will be a comprehensive, multi-contributed reference work that will detail the latest research and developments in biomedical signal processing related to big data medical analysis. It will describe signal processing, machine learning, and parallel computing strategies to revolutionize the world of medical analytics and diagnosis as presented by world class researchers and experts in this important field. The chapters will desribe tools that can be used by biomedical and clinical practitioners as well as industry professionals. It will give signal processing researchers a glimpse into the issues faced with Big Medical Data.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques
Author: Abdulhamit Subasi
Publsiher: Academic Press
Total Pages: 456
Release: 2019-03-16
ISBN 10: 0128176733
ISBN 13: 9780128176733
Language: EN, FR, DE, ES & NL

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques Book Review:

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

Precision Medicine Powered by pHealth and Connected Health

Precision Medicine Powered by pHealth and Connected Health
Author: Nicos Maglaveras,Ioanna Chouvarda,Paulo de Carvalho
Publsiher: Springer
Total Pages: 269
Release: 2017-11-16
ISBN 10: 9811074194
ISBN 13: 9789811074196
Language: EN, FR, DE, ES & NL

Precision Medicine Powered by pHealth and Connected Health Book Review:

This volume presents the proceedings of the 3rd ICBHI which took place in Thessaloniki on 18-21 November, 2017.The area of biomedical and health informatics is exploding at all scales. The developments in the areas of medical devices, eHealth and personalized health as enabling factors for the evolution of precision medicine are quickly developing and demand the development of new scaling tools, integration frameworks and methodologies.

Issues in Biomedical Engineering Research and Application 2013 Edition

Issues in Biomedical Engineering Research and Application  2013 Edition
Author: Anonim
Publsiher: ScholarlyEditions
Total Pages: 1193
Release: 2013-05-01
ISBN 10: 1490108718
ISBN 13: 9781490108711
Language: EN, FR, DE, ES & NL

Issues in Biomedical Engineering Research and Application 2013 Edition Book Review:

Issues in Biomedical Engineering Research and Application: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Reproductive Biomedicine. The editors have built Issues in Biomedical Engineering Research and Application: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Reproductive Biomedicine in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Biomedical Engineering Research and Application: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

IoT and ICT for Healthcare Applications

IoT and ICT for Healthcare Applications
Author: Nishu Gupta,Sara Paiva
Publsiher: Springer Nature
Total Pages: 298
Release: 2020-08-12
ISBN 10: 3030429342
ISBN 13: 9783030429348
Language: EN, FR, DE, ES & NL

IoT and ICT for Healthcare Applications Book Review:

This book provides an insight on the importance that Internet of Things (IoT) and Information and Communication Technology (ICT) solutions can have in taking care of people's health. Key features of this book present the recent and emerging developments in various specializations in curing health problems and finding their solutions by incorporating IoT and ICT. This book presents useful IoT and ICT applications and architectures that cater to their improved healthcare requirements. Topics include in-home healthcare services based on the Internet-of-Things; RFID technology for IoT based personal healthcare; Real-time reporting and monitoring; Interfacing devices to IoT; Smart medical services; Embedded gateway configuration (EGC); Health monitoring infrastructure; and more. Features a number of practical solutions and applications of IoT and ICT on healthcare; Includes application domains such as communication technology and electronic materials and devices; Applies to researchers, academics, students, and practitioners around the world.

Biomedical Engineering and its Applications in Healthcare

Biomedical Engineering and its Applications in Healthcare
Author: Sudip Paul
Publsiher: Springer Nature
Total Pages: 738
Release: 2019-11-08
ISBN 10: 9811337055
ISBN 13: 9789811337055
Language: EN, FR, DE, ES & NL

Biomedical Engineering and its Applications in Healthcare Book Review:

This book illustrates the significance of biomedical engineering in modern healthcare systems. Biomedical engineering plays an important role in a range of areas, from diagnosis and analysis to treatment and recovery and has entered the public consciousness through the proliferation of implantable medical devices, such as pacemakers and artificial hips, as well as the more futuristic technologies such as stem cell engineering and 3-D printing of biological organs. Starting with an introduction to biomedical engineering, the book then discusses various tools and techniques for medical diagnostics and treatment and recent advances. It also provides comprehensive and integrated information on rehabilitation engineering, including the design of artificial body parts, and the underlying principles, and standards. It also presents a conceptual framework to clarify the relationship between ethical policies in medical practice and philosophical moral reasoning. Lastly, the book highlights a number of challenges associated with modern healthcare technologies.

Biomedical Signal and Image Processing in Patient Care

Biomedical Signal and Image Processing in Patient Care
Author: Kolekar, Maheshkumar H.,Kumar, Vinod
Publsiher: IGI Global
Total Pages: 312
Release: 2017-08-11
ISBN 10: 152252830X
ISBN 13: 9781522528302
Language: EN, FR, DE, ES & NL

Biomedical Signal and Image Processing in Patient Care Book Review:

In healthcare systems, medical devices help physicians and specialists in diagnosis, prognosis, and therapeutics. As research shows, validation of medical devices is significantly optimized by accurate signal processing. Biomedical Signal and Image Processing in Patient Care is a pivotal reference source for progressive research on the latest development of applications and tools for healthcare systems. Featuring extensive coverage on a broad range of topics and perspectives such as telemedicine, human machine interfaces, and multimodal data fusion, this publication is ideally designed for academicians, researchers, students, and practitioners seeking current scholarly research on real-life technological inventions.

Machine Learning in Bio Signal Analysis and Diagnostic Imaging

Machine Learning in Bio Signal Analysis and Diagnostic Imaging
Author: Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
Publsiher: Academic Press
Total Pages: 345
Release: 2018-11-30
ISBN 10: 012816087X
ISBN 13: 9780128160879
Language: EN, FR, DE, ES & NL

Machine Learning in Bio Signal Analysis and Diagnostic Imaging Book Review:

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

Internet of Things for Healthcare Technologies

Internet of Things for Healthcare Technologies
Author: Chinmay Chakraborty,Amit Banerjee,Maheshkumar H. Kolekar,Lalit Garg,Basabi Chakraborty
Publsiher: Springer Nature
Total Pages: 324
Release: 2020-06-08
ISBN 10: 9811541124
ISBN 13: 9789811541124
Language: EN, FR, DE, ES & NL

Internet of Things for Healthcare Technologies Book Review:

This book focuses on recent advances in the Internet of Things (IoT) in biomedical and healthcare technologies, presenting theoretical, methodological, well-established, and validated empirical work in these fields. Artificial intelligence and IoT are set to revolutionize all industries, but perhaps none so much as health care. Both biomedicine and machine learning applications are capable of analyzing data stored in national health databases in order to identify potential health problems, complications and effective protocols, and a range of wearable devices for biomedical and healthcare applications far beyond tracking individuals’ steps each day has emerged. These prosthetic technologies have made significant strides in recent decades with the advances in materials and development. As a result, more flexible, more mobile chip-enabled prosthetics or other robotic devices are on the horizon. For example, IoT-enabled wireless ECG sensors that reduce healthcare cost, and lead to better quality of life for cardiac patients. This book focuses on three current trends that are likely to have a significant impact on future healthcare: Advanced Medical Imaging and Signal Processing; Biomedical Sensors; and Biotechnological and Healthcare Advances. It also presents new methods of evaluating medical data, and diagnosing diseases in order to improve general quality of life.

Classification and Clustering in Biomedical Signal Processing

Classification and Clustering in Biomedical Signal Processing
Author: Dey, Nilanjan
Publsiher: IGI Global
Total Pages: 463
Release: 2016-04-07
ISBN 10: 152250141X
ISBN 13: 9781522501411
Language: EN, FR, DE, ES & NL

Classification and Clustering in Biomedical Signal Processing Book Review:

Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research findings in the areas of signal processing for biomedical applications with an emphasis on classification and clustering techniques, this essential publication is designed for use by medical professionals, IT developers, and advanced-level graduate students.

Biomedical Signal and Image Processing

Biomedical Signal and Image Processing
Author: Kayvan Najarian,Robert Splinter
Publsiher: CRC Press
Total Pages: 411
Release: 2016-04-19
ISBN 10: 1439870349
ISBN 13: 9781439870341
Language: EN, FR, DE, ES & NL

Biomedical Signal and Image Processing Book Review:

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.