Automated Eeg Based Diagnosis Of Neurological Disorders
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Automated Eeg Based Diagnosis Of Neurological Disorders
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Author : Hojjat Adeli
language : en
Publisher: CRC Press
Release Date : 2010-02-09
Automated Eeg Based Diagnosis Of Neurological Disorders written by Hojjat Adeli and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-09 with Medical categories.
Based on the authors' groundbreaking research, Automated EEG-Based Diagnosis of Neurological Disorders: Inventing the Future of Neurology presents a research ideology, a novel multi-paradigm methodology, and advanced computational models for the automated EEG-based diagnosis of neurological disorders. It is based on the ingenious integration of thr
Eeg Based Diagnosis Of Alzheimer Disease
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Author : Nilesh Kulkarni
language : en
Publisher: Academic Press
Release Date : 2018-04-13
Eeg Based Diagnosis Of Alzheimer Disease written by Nilesh Kulkarni and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-13 with Technology & Engineering categories.
EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques provides a practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer's disease, and dementia diagnostics. The book examines different features of EEG signals used to properly diagnose Alzheimer's Disease early, presenting new and innovative results in the extraction and classification of Alzheimer's Disease using EEG signals. This book brings together the use of different EEG features, such as linear and nonlinear features, which play a significant role in diagnosing Alzheimer's Disease. - Includes the mathematical models and rigorous analysis of various classifiers and machine learning algorithms from a perspective of clinical deployment - Covers the history of EEG signals and their measurement and recording, along with their uses in clinical diagnostics - Analyzes spectral, wavelet, complexity and other features of early and efficient Alzheimer's Disease diagnostics - Explores support vector machine-based classification to increase accuracy
Deep Learning For Eeg Based Brain Computer Interfaces Representations Algorithms And Applications
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Author : Xiang Zhang
language : en
Publisher: World Scientific
Release Date : 2021-09-14
Deep Learning For Eeg Based Brain Computer Interfaces Representations Algorithms And Applications written by Xiang Zhang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-14 with Computers categories.
Deep Learning for EEG-Based Brain-Computer Interfaces is an exciting book that describes how emerging deep learning improves the future development of Brain-Computer Interfaces (BCI) in terms of representations, algorithms and applications. BCI bridges humanity's neural world and the physical world by decoding an individuals' brain signals into commands recognizable by computer devices.This book presents a highly comprehensive summary of commonly-used brain signals; a systematic introduction of around 12 subcategories of deep learning models; a mind-expanding summary of 200+ state-of-the-art studies adopting deep learning in BCI areas; an overview of a number of BCI applications and how deep learning contributes, along with 31 public BCI data sets. The authors also introduce a set of novel deep learning algorithms aimed at current BCI challenges such as robust representation learning, cross-scenario classification, and semi-supervised learning. Various real-world deep learning-based BCI applications are proposed and some prototypes are presented. The work contained within proposes effective and efficient models which will provide inspiration for people in academia and industry who work on BCI.Related Link(s)
Advanced Models Of Neural Networks
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Author : Gerasimos G. Rigatos
language : en
Publisher: Springer
Release Date : 2014-08-27
Advanced Models Of Neural Networks written by Gerasimos G. Rigatos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-27 with Technology & Engineering categories.
This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory. It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory.
Neural Information Processing
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Author : Sabri Arik
language : en
Publisher: Springer
Release Date : 2015-11-17
Neural Information Processing written by Sabri Arik and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-17 with Computers categories.
The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.
Issues In Neurology Research And Practice 2011 Edition
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Author :
language : en
Publisher: ScholarlyEditions
Release Date : 2012-01-09
Issues In Neurology Research And Practice 2011 Edition written by and has been published by ScholarlyEditions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-09 with Medical categories.
Issues in Neurology Research and Practice / 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Neurology Research and Practice. The editors have built Issues in Neurology Research and Practice: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Neurology Research and Practice in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Neurology Research and Practice: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Biomedical Signals Based Computer Aided Diagnosis For Neurological Disorders
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Author : M. Murugappan
language : en
Publisher: Springer Nature
Release Date : 2022-06-17
Biomedical Signals Based Computer Aided Diagnosis For Neurological Disorders written by M. Murugappan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-17 with Technology & Engineering categories.
Biomedical signals provide unprecedented insight into abnormal or anomalous neurological conditions. The computer-aided diagnosis (CAD) system plays a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced and analyzed, including electroencephalogram (EEG), electrocardiogram (ECG), heart rate (HR), magnetoencephalogram (MEG), and electromyogram (EMG). It explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders.
Artificial Intelligence For Neurological Disorders
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Author : Ajith Abraham
language : en
Publisher: Academic Press
Release Date : 2022-09-23
Artificial Intelligence For Neurological Disorders written by Ajith Abraham and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-23 with Medical categories.
Artificial Intelligence for Neurological Disorders provides a comprehensive resource of state-of-the-art approaches for AI, big data analytics and machine learning-based neurological research. The book discusses many machine learning techniques to detect neurological diseases at the cellular level, as well as other applications such as image segmentation, classification and image indexing, neural networks and image processing methods. Chapters include AI techniques for the early detection of neurological disease and deep learning applications using brain imaging methods like EEG, MEG, fMRI, fNIRS and PET for seizure prediction or neuromuscular rehabilitation. The goal of this book is to provide readers with broad coverage of these methods to encourage an even wider adoption of AI, Machine Learning and Big Data Analytics for problem-solving and stimulating neurological research and therapy advances. - Discusses various AI and ML methods to apply for neurological research - Explores Deep Learning techniques for brain MRI images - Covers AI techniques for the early detection of neurological diseases and seizure prediction - Examines cognitive therapies using AI and Deep Learning methods
Future Generation Information Technology
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Author : Jung-Hyun Lee
language : en
Publisher: Springer
Release Date : 2010-11-26
Future Generation Information Technology written by Jung-Hyun Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-26 with Computers categories.
As information technology (IT) becomes specialized and fragmented, it is easy to lose sight that many topics have common threads and because of this, advances in one s- discipline may transmit to another. The presentation of results between different s- disciplines encourages this interchange for the advancement of IT as a whole. This volume comprises the selection of papers presented at the Second International Mega-Conference on Future Generation Information Technology (FGIT 2010), composed of the following 11 international conferences: Advanced Software Engineering and Its Applications (ASEA 2010), Bio-Science and Bio- Technology (BSBT 2010), Control and Automation (CA 2010), Disaster Recovery and Business Continuity (DRBC 2010), Database Theory and Application (DTA 2010), Future Generation Communication and Networking (FGCN 2010), Grid and Distributed Computing (GDC 2010), Multimedia, Computer Graphics and Broadcasting (MulGraB 2010), Security Technology (SecTech 2010), Signal Processing, Image Processing and Pattern Recognition (SIP 2010), as well as u- and e-Service, Science and Technology (UNESST 2010). In total, 1,630 papers were submitted to FGIT 2010 from 30 countries. The submitted papers went through a rigorous reviewing process and 395 papers were accepted. Of these 395 papers, 60 were assigned to this volume. In addition, this volume contains 7 invited papers and abstracts. Of the remaining accepted papers, 269 were distributed among 8 volumes of proceedings published by Springer in the CCIS series. 66 papers were withdrawn due to technical reasons.
Eeg Based Experiment Design For Major Depressive Disorder
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Author : Aamir Saeed Malik
language : en
Publisher: Academic Press
Release Date : 2019-05-16
Eeg Based Experiment Design For Major Depressive Disorder written by Aamir Saeed Malik and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-16 with Medical categories.
EEG-Based Experiment Design for Major Depressive Disorder: Machine Learning and Psychiatric Diagnosis introduces EEG-based machine learning solutions for diagnosis and assessment of treatment efficacy for a variety of conditions. With a unique combination of background and practical perspectives for the use of automated EEG methods for mental illness, it details for readers how to design a successful experiment, providing experiment designs for both clinical and behavioral applications. This book details the EEG-based functional connectivity correlates for several conditions, including depression, anxiety, and epilepsy, along with pathophysiology of depression, underlying neural circuits and detailed options for diagnosis. It is a necessary read for those interested in developing EEG methods for addressing challenges for mental illness and researchers exploring automated methods for diagnosis and objective treatment assessment. - Written to assist in neuroscience experiment design using EEG - Provides a step-by-step approach for designing clinical experiments using EEG - Includes example datasets for affected individuals and healthy controls - Lists inclusion and exclusion criteria to help identify experiment subjects - Features appendices detailing subjective tests for screening patients - Examines applications for personalized treatment decisions