Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Abdulhamit Subasi
Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques Book PDF

Author : Abdulhamit Subasi
Publisher : Academic Press
Page : 456 pages
File Size : 48,6 Mb
Release : 2019-03-16
Category : Business & Economics
ISBN : 9780128176733

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques by Abdulhamit Subasi Pdf

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

Practical Machine Learning for Data Analysis Using Python

Abdulhamit Subasi
Practical Machine Learning for Data Analysis Using Python Book PDF

Author : Abdulhamit Subasi
Publisher : Academic Press
Page : 534 pages
File Size : 44,9 Mb
Release : 2020-06-05
Category : Computers
ISBN : 9780128213803

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Practical Machine Learning for Data Analysis Using Python by Abdulhamit Subasi Pdf

Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data Explores important classification and regression algorithms as well as other machine learning techniques Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features

Practical Biomedical Signal Analysis Using MATLAB®

Katarzyna J. Blinowska,Jarosław Żygierewicz
Practical Biomedical Signal Analysis Using MATLAB Book PDF

Author : Katarzyna J. Blinowska,Jarosław Żygierewicz
Publisher : CRC Press
Page : 370 pages
File Size : 42,7 Mb
Release : 2021-10-18
Category : Medical
ISBN : 9780429775734

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Practical Biomedical Signal Analysis Using MATLAB® by Katarzyna J. Blinowska,Jarosław Żygierewicz Pdf

Covering the latest cutting-edge techniques in biomedical signal processing while presenting a coherent treatment of various signal processing methods and applications, this second edition of Practical Biomedical Signal Analysis Using MATLAB® also offers practical guidance on which procedures are appropriate for a given task and different types of data. It begins by describing signal analysis techniques—including the newest and most advanced methods in the field—in an easy and accessible way, illustrating them with Live Script demos. MATLAB® routines are listed when available, and freely available software is discussed where appropriate. The book concludes by exploring the applications of the methods to a broad range of biomedical signals while highlighting common problems encountered in practice. These chapters have been updated throughout and include new sections on multiple channel analysis and connectivity measures, phase-amplitude analysis, functional near-infrared spectroscopy, fMRI (BOLD) signals, wearable devices, multimodal signal analysis, and brain-computer interfaces. By providing a unified overview of the field, this book explains how to integrate signal processing techniques in biomedical applications properly and explores how to avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods. It will be an excellent guide for graduate students studying biomedical engineering and practicing researchers in the field of biomedical signal analysis. Features: Fully updated throughout with new achievements, technologies, and methods and is supported with over 40 original MATLAB Live Scripts illustrating the discussed techniques, suitable for self-learning or as a supplement to college courses Provides a practical comparison of the advantages and disadvantages of different approaches in the context of various applications Applies the methods to a variety of signals, including electric, magnetic, acoustic, and optical Katarzyna J. Blinowska is a Professor emeritus at the University of Warsaw, Poland, where she was director of Graduate Studies in Biomedical Physics and head of the Department of Biomedical Physics. Currently, she is employed at the Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. She has been at the forefront in developing new advanced time-series methods for research and clinical applications. Jarosław Żygierewicz is a Professor at the University of Warsaw, Poland. His research focuses on developing methods for analyzing EEG and MEG signals, brain-computer interfaces, and applications of machine learning in signal processing and classification.

Practical Biomedical Signal Analysis Using MATLAB

Katarzyna J. Blinowska-Cieślak,Jaroslaw Zygierewicz
Practical Biomedical Signal Analysis Using MATLAB Book PDF

Author : Katarzyna J. Blinowska-Cieślak,Jaroslaw Zygierewicz
Publisher : Unknown
Page : 128 pages
File Size : 54,5 Mb
Release : 2021-09
Category : Electrophysiology
ISBN : 1032105526

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Practical Biomedical Signal Analysis Using MATLAB by Katarzyna J. Blinowska-Cieślak,Jaroslaw Zygierewicz Pdf

"Fully updated and with exclusive new content, this second edition 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"--

Practical Biomedical Signal Analysis Using MATLAB®

Katarzyn J. Blinowska,Jaroslaw Zygierewicz
Practical Biomedical Signal Analysis Using MATLAB Book PDF

Author : Katarzyn J. Blinowska,Jaroslaw Zygierewicz
Publisher : CRC Press
Page : 326 pages
File Size : 50,8 Mb
Release : 2011-09-12
Category : Medical
ISBN : 9781439812020

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Practical Biomedical Signal Analysis Using MATLAB® by Katarzyn J. Blinowska,Jaroslaw Zygierewicz Pdf

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 Intelligence and Signal Analysis

M. Tanveer,Ram Bilas Pachori
Machine Intelligence and Signal Analysis Book PDF

Author : M. Tanveer,Ram Bilas Pachori
Publisher : Springer
Page : 767 pages
File Size : 44,6 Mb
Release : 2018-08-07
Category : Technology & Engineering
ISBN : 9789811309236

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Machine Intelligence and Signal Analysis by M. Tanveer,Ram Bilas Pachori Pdf

The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.

Advances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning

Saeed Mian Qaisar,Humaira Nisar,Abdulhamit Subasi
Advances in Non Invasive Biomedical Signal Sensing and Processing with Machine Learning Book PDF

Author : Saeed Mian Qaisar,Humaira Nisar,Abdulhamit Subasi
Publisher : Springer Nature
Page : 385 pages
File Size : 51,6 Mb
Release : 2023-03-01
Category : Computers
ISBN : 9783031232398

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Advances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning by Saeed Mian Qaisar,Humaira Nisar,Abdulhamit Subasi Pdf

This book presents the modern technological advancements and revolutions in the biomedical sector. Progress in the contemporary sensing, Internet of Things (IoT) and machine learning algorithms and architectures have introduced new approaches in the mobile healthcare. A continuous observation of patients with critical health situation is required. It allows monitoring of their health status during daily life activities such as during sports, walking and sleeping. It is realizable by intelligently hybridizing the modern IoT framework, wireless biomedical implants and cloud computing. Such solutions are currently under development and in testing phases by healthcare and governmental institutions, research laboratories and biomedical companies. The biomedical signals such as electrocardiogram (ECG), electroencephalogram (EEG), Electromyography (EMG), phonocardiogram (PCG), Chronic Obstructive Pulmonary (COP), Electrooculography (EoG), photoplethysmography (PPG), and image modalities such as positron emission tomography (PET), magnetic resonance imaging (MRI) and computerized tomography (CT) are non-invasively acquired, measured, and processed via the biomedical sensors and gadgets. These signals and images represent the activities and conditions of human cardiovascular, neural, vision and cerebral systems. Multi-channel sensing of these signals and images with an appropriate granularity is required for an effective monitoring and diagnosis. It renders a big volume of data and its analysis is not feasible manually. Therefore, automated healthcare systems are in the process of evolution. These systems are mainly based on biomedical signal and image acquisition and sensing, preconditioning, features extraction and classification stages. The contemporary biomedical signal sensing, preconditioning, features extraction and intelligent machine and deep learning-based classification algorithms are described. Each chapter starts with the importance, problem statement and motivation. A self-sufficient description is provided. Therefore, each chapter can be read independently. To the best of the editors’ knowledge, this book is a comprehensive compilation on advances in non-invasive biomedical signal sensing and processing with machine and deep learning. We believe that theories, algorithms, realizations, applications, approaches, and challenges, which are presented in this book will have their impact and contribution in the design and development of modern and effective healthcare systems.

Biomedical Signal Processing

Ganesh R. Naik,Wellington Pinheiro dos Santos
Biomedical Signal Processing Book PDF

Author : Ganesh R. Naik,Wellington Pinheiro dos Santos
Publisher : CRC Press
Page : 313 pages
File Size : 43,6 Mb
Release : 2023-09-27
Category : Technology & Engineering
ISBN : 9781000906486

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Biomedical Signal Processing by Ganesh R. Naik,Wellington Pinheiro dos Santos Pdf

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.

Signal Processing and Machine Learning for Biomedical Big Data

Ervin Sejdic,Tiago H. Falk
Signal Processing and Machine Learning for Biomedical Big Data Book PDF

Author : Ervin Sejdic,Tiago H. Falk
Publisher : CRC Press
Page : 624 pages
File Size : 54,5 Mb
Release : 2018-07-04
Category : Medical
ISBN : 9781498773461

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Signal Processing and Machine Learning for Biomedical Big Data by Ervin Sejdic,Tiago H. Falk Pdf

Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.

Advanced Methods in Biomedical Signal Processing and Analysis

Kunal Pal,Samit Ari,Arindam Bit,Saugat Bhattacharyya
Advanced Methods in Biomedical Signal Processing and Analysis Book PDF

Author : Kunal Pal,Samit Ari,Arindam Bit,Saugat Bhattacharyya
Publisher : Academic Press
Page : 434 pages
File Size : 45,7 Mb
Release : 2022-09-07
Category : Technology & Engineering
ISBN : 9780323859547

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Advanced Methods in Biomedical Signal Processing and Analysis by Kunal Pal,Samit Ari,Arindam Bit,Saugat Bhattacharyya Pdf

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

Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
Machine Learning in Bio Signal Analysis and Diagnostic Imaging Book PDF

Author : Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
Publisher : Academic Press
Page : 345 pages
File Size : 40,9 Mb
Release : 2018-11-30
Category : Science
ISBN : 9780128160879

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging by Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi Pdf

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 Processing for Healthcare Applications

Varun Bajaj,G. R. Sinha,Chinmay Chakraborty
Biomedical Signal Processing for Healthcare Applications Book PDF

Author : Varun Bajaj,G. R. Sinha,Chinmay Chakraborty
Publisher : CRC Press
Page : 336 pages
File Size : 42,7 Mb
Release : 2021-07-21
Category : Technology & Engineering
ISBN : 9781000413304

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Biomedical Signal Processing for Healthcare Applications by Varun Bajaj,G. R. Sinha,Chinmay Chakraborty Pdf

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

Walid A. Zgallai
Biomedical Signal Processing and Artificial Intelligence in Healthcare Book PDF

Author : Walid A. Zgallai
Publisher : Academic Press
Page : 270 pages
File Size : 54,5 Mb
Release : 2020-07-29
Category : Technology & Engineering
ISBN : 9780128189474

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Biomedical Signal Processing and Artificial Intelligence in Healthcare by Walid A. Zgallai Pdf

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

Sub-Terahertz Sensing Technology for Biomedical Applications

Shiban Kishen Koul,Priyansha Kaurav
Sub Terahertz Sensing Technology for Biomedical Applications Book PDF

Author : Shiban Kishen Koul,Priyansha Kaurav
Publisher : Springer Nature
Page : 289 pages
File Size : 43,5 Mb
Release : 2022-08-20
Category : Science
ISBN : 9789811931406

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Sub-Terahertz Sensing Technology for Biomedical Applications by Shiban Kishen Koul,Priyansha Kaurav Pdf

This book offers the readers an opportunity to acquire the concepts of artificial intelligence (AI) enabled sub-THz systems for novel applications in the biomedical field. The readers will also be inspired to contextualize these applications for solving real life problems such as non-invasive glucose monitoring systems, cancer detection and dental imaging. The introductory section of this book focuses on existing technologies for radio frequency and infrared sensing in biomedical applications, and their limited use in sensing applications, as well as the advantages of using THz technology in this context. This is followed by a detailed comparative analysis of THz electronics technology and other conventional electro optic THz setups highlighting the superior efficiency, affordability and portability of electronics-based THz systems. The book also discusses electronic sub-THz measurement systems for different biomedical applications. The chapters elucidate two major applications where sub-THz provides an edge over existing state of the art techniques used for non-invasive measurement of blood glucose levels and intraoperative assessment of tumor margins. There is a detailed articulation of an application of leveraging machine learning for measurement systems for non-invasive glucose concentration measurement. This helps the reader relate to the output in a more user-friendly format and understand the possible use cases in a more lucid manner. The book is intended to help the reader learn how to build tissue phantoms and characterize them at sub-THz frequencies in order to test the measurement systems. Towards the end of the book, a brief introduction to system automation for biomedical imaging is provided as well for quick analysis of the data. The book will empower the reader to understand and appreciate the immense possibilities of using electronic THz systems in the biomedical field, creating gateways for fueling further research in this area.​

Enhanced Telemedicine and e-Health

Gonçalo Marques,Akash Kumar Bhoi,Isabel de la Torre Díez,Begonya Garcia-Zapirain
Enhanced Telemedicine and e Health Book PDF

Author : Gonçalo Marques,Akash Kumar Bhoi,Isabel de la Torre Díez,Begonya Garcia-Zapirain
Publisher : Springer Nature
Page : 359 pages
File Size : 43,9 Mb
Release : 2021-05-09
Category : Technology & Engineering
ISBN : 9783030701116

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Enhanced Telemedicine and e-Health by Gonçalo Marques,Akash Kumar Bhoi,Isabel de la Torre Díez,Begonya Garcia-Zapirain Pdf

In recent years, new applications on computer-aided technologies for telemedicine have emerged. Therefore, it is essential to capture this growing research area concerning the requirements of telemedicine. This book presents the latest findings on soft computing, artificial intelligence, Internet of Things and related computer-aided technologies for enhanced telemedicine and e-health. Furthermore, this volume includes comprehensive reviews describing procedures and techniques, which are crucial to support researchers in the field who want to replicate these methodologies in solving their related research problems. On the other hand, the included case studies present novel approaches using computer-aided methods for enhanced telemedicine and e-health. This volume aims to support future research activities in this domain. Consequently, the content has been selected to support not only academics or engineers but also to be used by healthcare professionals.