Download Biosignal Processing and Classification Using Computational Learning and Intelligence Ebook PDF

Biosignal Processing and Classification Using Computational Learning and Intelligence

Biosignal Processing and Classification Using Computational Learning and Intelligence
Principles, Algorithms and Applications

by Alejandro Antonio Torres Garcia,Carlos Alberto Reyes Garcia,Luis Villasenor-Pineda,Omar Mendoza Montoya

  • Publisher : Academic Press
  • Release : 2021-09-15
  • Pages : 432
  • ISBN : 9780128201251
  • Language : En, Es, Fr & De
GET BOOK

Biosignal Processing and Classification Using Computational Learning and Intelligence: Principles, Algorithms and Applications posits an approach for biosignal processing and classification using computational learning and intelligence, highlighting that the term biosignal refers to all kinds of signals that can be continuously measured and monitored in living beings. The book is composed of four relevant parts. Part One is an introduction to biosignals and their processing. Part Two presents the fundamentals of computational learning (machine learning). Then, the main techniques of computational intelligence are described along with the hybrid systems, which are the resulting combinations of these techniques. The authors focus primarily on the explanation of the most used methods in the last part of this book, which is the most extensive portion of the book. This part consists of a recapitulation of the newest applications in which these techniques have been successfully applied to the biosignals' domain, including EEG-based Brain-Computer Interfaces (BCI), emotion recognition from voice, leukemia recognition, infant cry recognition, epilepsy diagnosis from EEG, and automatic smell recognition. Provides coverage of the fundamentals of signal processing, including sensing the heart, sending the brain, sensing human acoustic, and sensing other organs Includes coverage biosignal pre-processing techniques such as filtering, artifiact removal, and feature extraction techniques such as Fourier transform, wavelet transform, and MFCC Covers the latest techniques in machine learning and computational intelligence, including Supervised Learning, common classifiers, feature selection, dimensionality reduction, fuzzy logic, neural networks, Deep Learning, bio-inspired algorithms, and Hybrid Systems Written by engineers to help engineers, computer scientists, researchers, and clinicians understand the technology and applications of computational learning to biosignal processing

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging
A Book

by Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi

  • Publisher : Academic Press
  • Release : 2018-11-30
  • Pages : 345
  • ISBN : 012816087X
  • Language : En, Es, Fr & De
GET BOOK

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 and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare
A Book

by Walid A. Zgallai

  • Publisher : Academic Press
  • Release : 2020-07-29
  • Pages : 268
  • ISBN : 0128189479
  • Language : En, Es, Fr & De
GET BOOK

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.

Machine Intelligence and Signal Processing

Machine Intelligence and Signal Processing
Proceedings of International Conference, MISP 2019

by Sonali Agarwal,Shekhar Verma,Dharma P. Agrawal

  • Publisher : Springer Nature
  • Release : 2020-02-25
  • Pages : 466
  • ISBN : 981151366X
  • Language : En, Es, Fr & De
GET BOOK

This book features selected high-quality research papers presented at the International Conference on Machine Intelligence and Signal Processing (MISP 2019), held at the Indian Institute of Technology, Allahabad, India, on September 7–10, 2019. The book covers the latest advances in the fields of machine learning, big data analytics, signal processing, computational learning theory, and their real-time applications. The topics covered include support vector machines (SVM) and variants like least-squares SVM (LS-SVM) and twin SVM (TWSVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. Further, it discusses the real-time challenges involved in processing big data and adapting the algorithms dynamically to improve the computational efficiency. Lastly, it describes recent developments in processing signals, for instance, signals generated from IoT devices, smart systems, speech, and videos and addresses biomedical signal processing: electrocardiogram (ECG) and electroencephalogram (EEG).

Machine Intelligence and Signal Analysis

Machine Intelligence and Signal Analysis
A Book

by M. Tanveer,Ram Bilas Pachori

  • Publisher : Springer
  • Release : 2018-08-07
  • Pages : 767
  • ISBN : 981130923X
  • Language : En, Es, Fr & De
GET BOOK

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.

Practical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python
A Book

by Abdulhamit Subasi

  • Publisher : Academic Press
  • Release : 2020-06-05
  • Pages : 534
  • ISBN : 0128213809
  • Language : En, Es, Fr & De
GET BOOK

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 Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques
A MATLAB Based Approach

by Abdulhamit Subasi

  • Publisher : Academic Press
  • Release : 2019-03-16
  • Pages : 456
  • ISBN : 0128176733
  • Language : En, Es, Fr & De
GET BOOK

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

Classification and Clustering in Biomedical Signal Processing

Classification and Clustering in Biomedical Signal Processing
A Book

by Dey, Nilanjan

  • Publisher : IGI Global
  • Release : 2016-04-07
  • Pages : 463
  • ISBN : 152250141X
  • Language : En, Es, Fr & De
GET BOOK

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.

Introduction to Computational Health Informatics

Introduction to Computational Health Informatics
A Book

by Arvind Kumar Bansal,Javed Iqbal Khan,S. Kaisar Alam

  • Publisher : CRC Press
  • Release : 2020-01-08
  • Pages : 576
  • ISBN : 1000761592
  • Language : En, Es, Fr & De
GET BOOK

This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis. Features Integrates computer science and clinical perspectives Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development

Signal Processing and Machine Learning for Biomedical Big Data

Signal Processing and Machine Learning for Biomedical Big Data
A Book

by Ervin Sejdic,Tiago H. Falk

  • Publisher : CRC Press
  • Release : 2018-07-04
  • Pages : 606
  • ISBN : 1351061216
  • Language : En, Es, Fr & De
GET BOOK

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.

Bio-inspired Neurocomputing

Bio-inspired Neurocomputing
A Book

by Akash Kumar Bhoi,Pradeep Kumar Mallick,Chuan-Ming Liu,Valentina E. Balas

  • Publisher : Springer Nature
  • Release : 2020-07-21
  • Pages : 427
  • ISBN : 9811554951
  • Language : En, Es, Fr & De
GET BOOK

This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchers as well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.

Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques

Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
Algorithms, Methods, and Techniques

by Olivas, Emilio Soria,Guerrero, Jos‚ David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos‚

  • Publisher : IGI Global
  • Release : 2009-08-31
  • Pages : 852
  • ISBN : 1605667676
  • Language : En, Es, Fr & De
GET BOOK

"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.

ECG Signal Processing, Classification and Interpretation

ECG Signal Processing, Classification and Interpretation
A Comprehensive Framework of Computational Intelligence

by Adam Gacek,Witold Pedrycz

  • Publisher : Springer Science & Business Media
  • Release : 2011-09-18
  • Pages : 278
  • ISBN : 9780857298683
  • Language : En, Es, Fr & De
GET BOOK

The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. The text is self-contained, addressing concepts, methodology, algorithms, and case studies and applications, providing the reader with the necessary background augmented with step-by-step explanation of the more advanced concepts. It is structured in three parts: Part I covers the fundamental ideas of computational intelligence together with the relevant principles of data acquisition, morphology and use in diagnosis; Part II deals with techniques and models of computational intelligence that are suitable for signal processing; and Part III details ECG system-diagnostic interpretation and knowledge acquisition architectures. Illustrative material includes: brief numerical experiments; detailed schemes, exercises and more advanced problems.

Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition

Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition
A Book

by Serkan Kiranyaz,Turker Ince,Moncef Gabbouj

  • Publisher : Springer Science & Business Media
  • Release : 2013-07-16
  • Pages : 321
  • ISBN : 3642378463
  • Language : En, Es, Fr & De
GET BOOK

For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach. After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its advantages in challenging application domains, focusing on the state of the art of multidimensional extensions such as global convergence in particle swarm optimization, dynamic data clustering, evolutionary neural networks, biomedical applications and personalized ECG classification, content-based image classification and retrieval, and evolutionary feature synthesis. The content is characterized by strong practical considerations, and the book is supported with fully documented source code for all applications presented, as well as many sample datasets. The book will be of benefit to researchers and practitioners working in the areas of machine intelligence, signal processing, pattern recognition, and data mining, or using principles from these areas in their application domains. It may also be used as a reference text for graduate courses on swarm optimization, data clustering and classification, content-based multimedia search, and biomedical signal processing applications.

Machine Intelligence and Signal Processing

Machine Intelligence and Signal Processing
A Book

by Richa Singh,Mayank Vatsa,Angshul Majumdar,Ajay Kumar

  • Publisher : Springer
  • Release : 2015-10-01
  • Pages : 163
  • ISBN : 8132226259
  • Language : En, Es, Fr & De
GET BOOK

This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning – instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning). And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intelligence and Signal Processing was one of the few unique events that are focused on the convergence of the two fields. The book is comprised of chapters based on the top presentations at the workshop. This book has three chapters on various topics of biometrics – two are on face detection and one on iris recognition; all from top researchers in their field. There are four chapters on different biomedical signal / image processing problems. Two of these are on retinal vessel classification and extraction; one on biomedical signal acquisition and the fourth one on region detection. There are three chapters on data analysis – a topic gaining immense popularity in industry and academia. One of these shows a novel use of compressed sensing in missing sales data interpolation. Another chapter is on spam detection and the third one is on simple one-shot movie rating prediction. Four other chapters cover various cutting edge miscellaneous topics on character recognition, software effort prediction, speech recognition and non-linear sparse recovery. The contents of this book will prove useful to researchers, professionals and students in the domains of machine learning and signal processing.

Pattern Recognition and Machine Intelligence

Pattern Recognition and Machine Intelligence
8th International Conference, PReMI 2019, Tezpur, India, December 17-20, 2019, Proceedings

by Bhabesh Deka,Pradipta Maji,Sushmita Mitra,Dhruba Kumar Bhattacharyya,Prabin Kumar Bora,Sankar Kumar Pal

  • Publisher : Springer Nature
  • Release : 2020-01-09
  • Pages : 637
  • ISBN : 3030348695
  • Language : En, Es, Fr & De
GET BOOK

The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning; Soft and Evolutionary Computing; Image Processing; Medical Image Processing; Bioinformatics and Biomedical Signal Processing; Information Retrieval; Remote Sensing; Signal and Video Processing; and Smart and Intelligent Sensors.

Cognitive Informatics and Soft Computing

Cognitive Informatics and Soft Computing
Proceeding of CISC 2019

by Pradeep Kumar Mallick,Valentina Emilia Balas,Akash Kumar Bhoi,Gyoo-Soo Chae

  • Publisher : Springer Nature
  • Release : 2020-01-14
  • Pages : 705
  • ISBN : 9811514518
  • Language : En, Es, Fr & De
GET BOOK

The book presents new approaches and methods for solving real-world problems. It highlights, in particular, innovative research in the fields of Cognitive Informatics, Cognitive Computing, Computational Intelligence, Advanced Computing, and Hybrid Intelligent Models and Applications. New algorithms and methods in a variety of fields are presented, together with solution-based approaches. The topics addressed include various theoretical aspects and applications of Computer Science, Artificial Intelligence, Cybernetics, Automation Control Theory, and Software Engineering.

Advances in Electronics, Communication and Computing

Advances in Electronics, Communication and Computing
Select Proceedings of ETAEERE 2020

by Pradeep Kumar Mallick,Akash Kumar Bhoi,Gyoo-Soo Chae,Kanak Kalita

  • Publisher : Springer Nature
  • Release : 2021-03-01
  • Pages : 675
  • ISBN : 9811587523
  • Language : En, Es, Fr & De
GET BOOK

This book comprises select proceedings of the international conference ETAEERE 2020, and covers latest research in the areas of electronics, communication and computing. The book includes different approaches and techniques for specific applications using particle swarm optimization, Otsu’s function and harmony search optimization algorithm, DNA-NAND gate, triple gate SOI MOSFET, micro-Raman and FTIR analysis, high-k dielectric gate oxide, spectrum sensing in cognitive radio, microstrip antenna, GPR with conducting surfaces, energy efficient packet routing, iBGP route reflectors, circularly polarized antenna, double fork shaped patch radiator, implementation of Doppler radar at 24 GHz, iris image classification using SVM, digital image forgery detection, secure communication, spoken dialog system, and DFT-DCT spreading strategies. Given the range of topics covered, this book can be useful for both students and researchers working in electronics and communication.

Advances in Computational Intelligence Techniques

Advances in Computational Intelligence Techniques
A Book

by Shruti Jain,Meenakshi Sood,Sudip Paul

  • Publisher : Springer Nature
  • Release : 2020-02-20
  • Pages : 266
  • ISBN : 9811526206
  • Language : En, Es, Fr & De
GET BOOK

This book highlights recent advances in computational intelligence for signal processing, computing, imaging, artificial intelligence, and their applications. It offers support for researchers involved in designing decision support systems to promote the societal acceptance of ambient intelligence, and presents the latest research on diverse topics in intelligence technologies with the goal of advancing knowledge and applications in this rapidly evolving field. As such, it offers a valuable resource for researchers, developers and educators whose work involves recent advances and emerging technologies in computational intelligence.

Signal Processing Techniques for Computational Health Informatics

Signal Processing Techniques for Computational Health Informatics
A Book

by Md Atiqur Rahman Ahad

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 329
  • ISBN : 3030549321
  • Language : En, Es, Fr & De
GET BOOK