Computational Intelligence and Deep Learning Methods for Neuro-rehabilitation Applications
Computational Intelligence and Deep Learning Methods for Neuro-rehabilitation Applications

Author: D. Jude Hemanth

Publisher: Elsevier

Published: 2023-11-17

Total Pages: 304

ISBN-13: 0443137730

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Computational Intelligence and Deep Learning Methods for Neuro-rehabilitation Applications explores the different possibilities of providing AI based neuro-rehabilitation methods to treat neurological disorders. This book provides in-depth knowledge on the challenges and solutions associated with the different varieties of neuro-rehabilitation through the inclusion of case studies and real-time scenarios in different geographical locations. Beginning with an overview of neuro-rehabilitation applications, the book discusses the role of machine learning methods in brain function grading for adults with Mild Cognitive Impairment, Brain Computer Interface for post-stroke patients, developing assistive devices for paralytic patients, and cognitive treatment for spinal cord injuries. Topics also include AI-based video games to improve the brain performances in children with autism and ADHD, deep learning approaches and magnetoencephalography data for limb movement, EEG signal analysis, smart sensors, and the application of robotic concepts for gait control. Incorporates artificial intelligence techniques into neuro-rehabilitation and presents novel ideas for this process Provides in-depth case studies and state-of-the-art methods, along with the experimental study Presents a block diagram based complete set-up in each chapter to help in real-time implementation

Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence
Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence

Author: Anitha S. Pillai

Publisher: Academic Press

Published: 2022-02-23

Total Pages: 356

ISBN-13: 0323886264

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Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence focuses on how the neurosciences can benefit from advances in AI, especially in areas such as medical image analysis for the improved diagnosis of Alzheimer's disease, early detection of acute neurologic events, prediction of stroke, medical image segmentation for quantitative evaluation of neuroanatomy and vasculature, diagnosis of Alzheimer's Disease, autism spectrum disorder, and other key neurological disorders. Chapters also focus on how AI can help in predicting stroke recovery, and the use of Machine Learning and AI in personalizing stroke rehabilitation therapy. Other sections delve into Epilepsy and the use of Machine Learning techniques to detect epileptogenic lesions on MRIs and how to understand neural networks. - Provides readers with an understanding on the key applications of artificial intelligence and machine learning in the diagnosis and treatment of the most important neurological disorders - Integrates recent advancements of artificial intelligence and machine learning to the evaluation of large amounts of clinical data for the early detection of disorders such as Alzheimer's Disease, autism spectrum disorder, Multiple Sclerosis, headache disorder, Epilepsy, and stroke - Provides readers with illustrative examples of how artificial intelligence can be applied to outcome prediction, neurorehabilitation and clinical exams, including a wide range of case studies in predicting and classifying neurological disorders

Intelligent Interactive Multimedia Systems for e-Healthcare Applications
Intelligent Interactive Multimedia Systems for e-Healthcare Applications

Author: Amit Kumar Tyagi

Publisher: Springer Nature

Published: 2021-11-15

Total Pages: 451

ISBN-13: 9811665427

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This book includes high-quality research on various aspects of intelligent interactive multimedia technologies in healthcare services. The topics covered in the book focus on state-of-the-art approaches, methodologies, and systems in the design, development, deployment, and innovative use of multimedia systems, tools, and technologies in healthcare. The volume provides insights into smart healthcare service demands. It presents all information about multimedia uses in e-healthcare applications. The book also includes case studies and self-assessment problems for readers and future researchers. This book proves to be a valuable resource to know how AI can be an alternative tool for automated and intelligent analytics for e-healthcare applications.

Artificial Intelligence for Neurological Disorders
Artificial Intelligence for Neurological Disorders

Author: Ajith Abraham

Publisher: Academic Press

Published: 2022-09-23

Total Pages: 434

ISBN-13: 0323902782

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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

Time-Series Prediction and Applications
Time-Series Prediction and Applications

Author: Amit Konar

Publisher: Springer

Published: 2017-03-25

Total Pages: 255

ISBN-13: 3319545973

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This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at the end of each chapter to the readers’ ability and understanding of the topics covered.

Applications of Computational Intelligence
Applications of Computational Intelligence

Author: Alvaro David Orjuela-Cañón

Publisher: Springer Nature

Published: 2021-02-25

Total Pages: 175

ISBN-13: 3030697746

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This book constitutes revised and extended selected papers of the Third IEEE Colombian Conference, ColCACI 2020, held in Cali, Colombia, August 2020. Due to the COVID-19 pandemic the conference was held online. The12 full papers presented were carefully reviewed and selected from 65 submissions. The papers are organized in topical sections on ​earth sciences applications; biomedical and power applications; alternative proposals and its applications.

Brain and Behavior Computing
Brain and Behavior Computing

Author: Mridu Sahu

Publisher: CRC Press

Published: 2021-06-23

Total Pages: 429

ISBN-13: 1000387151

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Brain and Behavior Computing offers insights into the functions of the human brain. This book provides an emphasis on brain and behavior computing with different modalities available such as signal processing, image processing, data sciences, statistics further it includes fundamental, mathematical model, algorithms, case studies, and future research scopes. It further illustrates brain signal sources and how the brain signal can process, manipulate, and transform in different domains allowing researchers and professionals to extract information about the physiological condition of the brain. Emphasizes real challenges in brain signal processing for a variety of applications for analysis, classification, and clustering. Discusses data sciences and its applications in brain computing visualization. Covers all the most recent tools for analysing the brain and it’s working. Describes brain modeling and all possible machine learning methods and their uses. Augments the use of data mining and machine learning to brain computer interface (BCI) devices. Includes case studies and actual simulation examples. This book is aimed at researchers, professionals, and graduate students in image processing and computer vision, biomedical engineering, signal processing, and brain and behavior computing.