Biomedical Signal Analysis For Connected Healthcare
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Biomedical Signal Analysis For Connected Healthcare
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Author : Sridhar Krishnan
language : en
Publisher: Elsevier
Release Date : 2021-06-25
Biomedical Signal Analysis For Connected Healthcare written by Sridhar Krishnan and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Medical categories.
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
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Author : Varun Bajaj
language : en
Publisher: CRC Press
Release Date : 2021-07-20
Biomedical Signal Processing For Healthcare Applications written by Varun Bajaj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-20 with Technology & Engineering categories.
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 Analysis
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Author : Rangaraj M. Rangayyan
language : en
Publisher: John Wiley & Sons
Release Date : 2024-02-19
Biomedical Signal Analysis written by Rangaraj M. Rangayyan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-19 with Science categories.
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.
Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques
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Author : Abdulhamit Subasi
language : en
Publisher: Academic Press
Release Date : 2019-03-16
Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-16 with Medical categories.
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
Iot For Elderly Aging And Ehealth
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Author : C.H. Wu
language : en
Publisher: Springer Nature
Release Date : 2022-01-17
Iot For Elderly Aging And Ehealth written by C.H. Wu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-17 with Technology & Engineering categories.
This book reflects the recent developments while providing a comprehensive introduction to the Internet of things (IoT) and cloud technologies in transforming aging. IoT has its origins in device connectivity, whereas the cloud grew out of computer science. They can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. This book is aimed at advanced undergraduates or first-year research students, as well as researchers and practitioners, and assumes no previous knowledge of IoT and cloud concepts. Basics of computer applications and concepts are required. Some familiarity with gerontechnology would be helpful, though not essential, as this book includes a self-contained introduction to how technology is transforming elderly care and eHealth management. This book aims to give references that offer more detail than is possible here and hopefully provide an entry point into a series of technologies that can improve the quality of life for the elderly. The book includes several case studies explaining how each piece of technology works and its benefits to the elderly. This book is also considered as a simple guide to the technologies for the elderly to use in the community.
Advances In 3d Bioprinting
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Author : Roger J. Narayan
language : en
Publisher: CRC Press
Release Date : 2023-08-11
Advances In 3d Bioprinting written by Roger J. Narayan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-11 with Medical categories.
"3D bioprinting" refers to processes in which an additive manufacturing approach is used to create devices for medical applications. This volume considers exciting applications for 3D bioprinting, including its use in manufacturing artificial tissues, surgical models, and orthopedic implants. The book includes chapters from leaders in the field on 3D bioprinting of tissues and organs, biomedical applications of digital light processing, biomedical applications of nozzle-free pyro-electrohydrodynamic jet printing of buffer-free bioinks, additive manufacturing of surgical models, dental crowns, and orthopedic implants, 3D bioprinting of dry electrodes, and 3D bioprinting for regenerative medicine and disease modeling of the ocular surface. This is an accessible reference for students and researchers on current 3D bioprinting technology, providing helpful information on the important applications of this technology. It will be a useful resource to students, researchers, and practitioners in the rapidly growing global 3D bioprinting community.
Machine Learning Models And Architectures For Biomedical Signal Processing
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Author : Suman Lata Tripathi
language : en
Publisher: Elsevier
Release Date : 2024-11-05
Machine Learning Models And Architectures For Biomedical Signal Processing written by Suman Lata Tripathi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-05 with Computers categories.
Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates how efficient machine and deep learning models can support high-speed processors with reconfigurable architectures like graphic processing units (GPUs), Field programmable gate arrays (FPGAs), or any hybrid system. This great resource will be of interest to researchers working to increase the efficiency of hardware and architecture design for biomedical signal processing and signal processing techniques. - Covers the hardware architecture implementation of machine learning algorithms - Discusses the software implementation approach and the efficient hardware of machine learning application with FPGA - Presents the major design challenges and research potential in machine learning techniques
Computational Health Informatics For Biomedical Applications
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Author : Aryan Chaudhary
language : en
Publisher: CRC Press
Release Date : 2023-06-30
Computational Health Informatics For Biomedical Applications written by Aryan Chaudhary and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Computers categories.
The recent explosion of technology in healthcare has rapidly changed the healthcare sector. Technologies such as artificial intelligence and machine learning along with the integration of the Internet of Medical Things have evolved to tackle the need for remote healthcare systems, augmenting them in a self-sustainable way. This new volume explores the many important smart technologies that can make healthcare delivery and monitoring faster, more efficient, and less invasive. It looks at computational tactics as applied to the development of biomedical applications using artificial intelligence, machine learning, signal analysis, computer-aided design, robotics and automation, biomedical imaging, telemedicine, and other technologies. The book provides a solid framework to give the modern class of medical gearheads information on the innovative applications of computational mechanisms for improving and expediting patient-friendly automation in healthcare.
Intelligent Human Computer Interaction
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Author : Hakimjon Zaynidinov
language : en
Publisher: Springer Nature
Release Date : 2023-04-10
Intelligent Human Computer Interaction written by Hakimjon Zaynidinov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-10 with Computers categories.
This book constitutes the refereed proceedings of the 14th International Conference on Intelligent Human Computer Interaction, IHCI 2022, held in Tashkent, Uzbekistan, during October 20–22, 2022. The 47 full papers and 13 short papers included in this book were carefully reviewed and selected from 148 submissions. They were organized in topical sections as follows: Bio-inspired Computing; Cognitive computing; Human Centered AI; Intelligent Technology for Post-Covid and Web Frameworks.
Machine Learning And The Internet Of Medical Things In Healthcare
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Author : Krishna Kant Singh
language : en
Publisher: Academic Press
Release Date : 2021-04-14
Machine Learning And The Internet Of Medical Things In Healthcare written by Krishna Kant Singh and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-14 with Science categories.
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