Advances In Non Invasive Biomedical Signal Sensing And Processing With Machine Learning

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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 : 42,5 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.

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

Adel Al-Jumaily,Paolo Crippa,Ali Mansour,Claudio Turchetti
Non Invasive Health Systems based on Advanced Biomedical Signal and Image Processing Book PDF

Author : Adel Al-Jumaily,Paolo Crippa,Ali Mansour,Claudio Turchetti
Publisher : CRC Press
Page : 475 pages
File Size : 46,8 Mb
Release : 2024-02-29
Category : Technology & Engineering
ISBN : 9781003838104

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Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing by Adel Al-Jumaily,Paolo Crippa,Ali Mansour,Claudio Turchetti Pdf

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.

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 : 51,7 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

Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods

Kemal Polat,Saban Öztürk
Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods Book PDF

Author : Kemal Polat,Saban Öztürk
Publisher : Elsevier
Page : 303 pages
File Size : 52,9 Mb
Release : 2023-04-30
Category : Computers
ISBN : 9780323996815

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Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods by Kemal Polat,Saban Öztürk Pdf

Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases. Investigates novel concepts of deep learning for acquisition of non-invasive biomedical image and signal modalities for different disorders Explores the implementation of novel deep learning and CNN methodologies and their impact studies that have been tested on different medical case studies Presents end-to-end CNN architectures for automatic detection of situations where early diagnosis is important Includes novel methodologies, datasets, design and simulation examples

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 : 40,5 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

Biomedical Signal Processing

Ganesh Naik
Biomedical Signal Processing Book PDF

Author : Ganesh Naik
Publisher : Springer Nature
Page : 432 pages
File Size : 51,8 Mb
Release : 2019-11-12
Category : Technology & Engineering
ISBN : 9789811390975

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Biomedical Signal Processing by Ganesh Naik Pdf

This book reports on the latest advances in the study of biomedical signal processing, and discusses in detail a number of open problems concerning clinical, biomedical and neural signals. It methodically collects and presents in a unified form the research findings previously scattered throughout various scientific journals and conference proceedings. In addition, the chapters are self-contained and can be read independently. Accordingly, the book will be of interest to university researchers, R&D engineers and graduate students who wish to learn the core principles of biomedical signal analysis, algorithms, and applications, while also offering a valuable reference work for biomedical engineers and clinicians who wish to learn more about the theory and recent applications of neural engineering and biomedical signal processing.

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 : 47,5 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

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.

Classification and Clustering in Biomedical Signal Processing

Dey, Nilanjan
Classification and Clustering in Biomedical Signal Processing Book PDF

Author : Dey, Nilanjan
Publisher : IGI Global
Page : 463 pages
File Size : 41,7 Mb
Release : 2016-04-07
Category : Technology & Engineering
ISBN : 9781522501411

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Classification and Clustering in Biomedical Signal Processing by Dey, Nilanjan Pdf

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.

Recent Advances in Biomedical Signal Processing

Juan Manuel Górriz,Elmar W. Lang,Javier Ramírez
Recent Advances in Biomedical Signal Processing Book PDF

Author : Juan Manuel Górriz,Elmar W. Lang,Javier Ramírez
Publisher : Bentham Science Publishers
Page : 288 pages
File Size : 50,7 Mb
Release : 2011
Category : Technology & Engineering
ISBN : 9781608052189

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Recent Advances in Biomedical Signal Processing by Juan Manuel Górriz,Elmar W. Lang,Javier Ramírez Pdf

"Biomedical signal processing is a rapidly expanding field with a wide range of applications, from the construction of artificial limbs and aids for disabilities to the development of sophisticated medical imaging systems. Acquisition and processing of bio"

AI-Enabled Smart Healthcare Using Biomedical Signals

Chaurasiya, Rahul Kumar,Agrawal, Dheeraj,Pachori, Ram Bilas
AI Enabled Smart Healthcare Using Biomedical Signals Book PDF

Author : Chaurasiya, Rahul Kumar,Agrawal, Dheeraj,Pachori, Ram Bilas
Publisher : IGI Global
Page : 322 pages
File Size : 44,5 Mb
Release : 2022-05-27
Category : Technology & Engineering
ISBN : 9781668439487

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AI-Enabled Smart Healthcare Using Biomedical Signals by Chaurasiya, Rahul Kumar,Agrawal, Dheeraj,Pachori, Ram Bilas Pdf

Technological advancements have enhanced all functions of society and revolutionized the healthcare field. Smart healthcare applications and practices have grown within the past decade, strengthening overall care. Biomedical signals observe physiological activities, which provide essential information to healthcare professionals. Biomedical signal processing can be optimized through artificial intelligence (AI) and machine learning (ML), presenting the next step towards smart healthcare. AI-Enabled Smart Healthcare Using Biomedical Signals will not only cover the mathematical description of the AI- and ML-based methods, but also analyze and demonstrate the usability of different AI methods for a range of biomedical signals. The book covers all types of biomedical signals helpful for smart healthcare applications. Covering topics such as automated diagnosis, emotion identification, and frequency discrimination techniques, this premier reference source is an excellent resource for healthcare administration, biomedical engineers, medical laboratory technicians, medical technology assistants, computer scientists, libraries, students and faculty of higher education, researchers, and academicians.

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 : 41,8 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.

Computational Tools and Techniques for Biomedical Signal Processing

Singh, Butta
Computational Tools and Techniques for Biomedical Signal Processing Book PDF

Author : Singh, Butta
Publisher : IGI Global
Page : 415 pages
File Size : 54,6 Mb
Release : 2016-08-12
Category : Technology & Engineering
ISBN : 9781522506614

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Computational Tools and Techniques for Biomedical Signal Processing by Singh, Butta Pdf

Biomedical signal processing in the medical field has helped optimize patient care and diagnosis within medical facilities. As technology in this area continues to advance, it has become imperative to evaluate other ways these computation techniques could be implemented. Computational Tools and Techniques for Biomedical Signal Processing investigates high-performance computing techniques being utilized in hospital information systems. Featuring comprehensive coverage on various theoretical perspectives, best practices, and emergent research in the field, this book is ideally suited for computer scientists, information technologists, biomedical engineers, data-processing specialists, and medical physicists interested in signal processing within medical systems and facilities.

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

Adel Al-Jumaily,Paolo Crippa,Ali Mansour,Claudio Turchetti
Non Invasive Health Systems based on Advanced Biomedical Signal and Image Processing Book PDF

Author : Adel Al-Jumaily,Paolo Crippa,Ali Mansour,Claudio Turchetti
Publisher : CRC Press
Page : 502 pages
File Size : 43,5 Mb
Release : 2024-02-29
Category : Technology & Engineering
ISBN : 9781003838128

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Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing by Adel Al-Jumaily,Paolo Crippa,Ali Mansour,Claudio Turchetti Pdf

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.

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 : 49,9 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