Computational Intelligence And Deep Learning Methods For Neuro Rehabilitation Applications
Download Computational Intelligence And Deep Learning Methods For Neuro Rehabilitation Applications full books in PDF, epub, and Kindle. Read online free Computational Intelligence And Deep Learning Methods For Neuro Rehabilitation Applications ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : D. Jude Hemanth |
| Publisher | : Elsevier |
| Total Pages | : 304 |
| Release | : 2023-11-14 |
| Genre | : Science |
| ISBN | : 0443137730 |
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
| Author | : Anitha S. Pillai |
| Publisher | : Academic Press |
| Total Pages | : 356 |
| Release | : 2022-02-23 |
| Genre | : Science |
| ISBN | : 0323886264 |
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
| Author | : Amit Kumar Tyagi |
| Publisher | : Springer Nature |
| Total Pages | : 451 |
| Release | : 2021-11-15 |
| Genre | : Technology & Engineering |
| ISBN | : 9811665427 |
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.
| Author | : Witold Pedrycz |
| Publisher | : Springer |
| Total Pages | : 431 |
| Release | : 2018-04-30 |
| Genre | : Technology & Engineering |
| ISBN | : 3319896296 |
The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.
| Author | : Alonso, Eduardo |
| Publisher | : IGI Global |
| Total Pages | : 394 |
| Release | : 2010-11-30 |
| Genre | : Computers |
| ISBN | : 1609600231 |
"This book argues that computational models in behavioral neuroscience must be taken with caution, and advocates for the study of mathematical models of existing theories as complementary to neuro-psychological models and computational models"--
| Author | : Fangzhou Xu |
| Publisher | : Frontiers Media SA |
| Total Pages | : 232 |
| Release | : 2023-11-15 |
| Genre | : Science |
| ISBN | : 2832539025 |
| Author | : Ajith Abraham |
| Publisher | : Academic Press |
| Total Pages | : 434 |
| Release | : 2022-09-23 |
| Genre | : Medical |
| ISBN | : 0323902782 |
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
| Author | : Rocco Salvatore Calabrò |
| Publisher | : Springer Nature |
| Total Pages | : 228 |
| Release | : |
| Genre | : |
| ISBN | : 303163604X |
| Author | : Boris Kryzhanovsky |
| Publisher | : Springer |
| Total Pages | : 441 |
| Release | : 2021-10-03 |
| Genre | : Technology & Engineering |
| ISBN | : 9783030605797 |
This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large scale neural models, brain computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXII International Conference on Neuroinformatics, held on October 12-16, 2020, Moscow, Russia.
| Author | : Amit Konar |
| Publisher | : Springer |
| Total Pages | : 255 |
| Release | : 2017-03-25 |
| Genre | : Technology & Engineering |
| ISBN | : 3319545973 |
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.
