-PDF Download- Applied Software Development With Python Machine Learning By Wearable Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation EBOOK

Applied Software Development With Python & Machine Learning By Wearable & Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation

Author: Robert Lemoyne

Publisher: World Scientific

Published: 2021-08-26

Total Pages: 249

ISBN-13: 981123597X

The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to Cloud computing resources.Imperative to the realization of these objectives is the organization of the software development process. Requirements and pseudo code are derived, and software automation using Python for post-processing the inertial sensor signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provided. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system.Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity.Related Link(s)

Applied Software Development With Python & Machine Learning By Wearable & Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation

Author: Robert Charles LeMoyne

Publisher:

Published: 2021

Total Pages: 249

ISBN-13: 9789811235962

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"The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to Cloud computing resources. Imperative to the realization of these objectives is the organization of the software development process. Requirements and pseudo code are derived, and software automation using Python for post-processing the inertial sensor signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provided. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system. Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity"--

Wearable and Wireless Systems for Healthcare

Author: Robert LeMoyne

Publisher: Springer Nature

Published: 2018

Total Pages: 206

ISBN-13: 9819724392

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Wearable and Wireless Systems for Healthcare II

Author: Robert LeMoyne

Publisher: Springer

Published: 2019-02-20

Total Pages: 128

ISBN-13: 9811358087

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This book provides a far-sighted perspective on the role of wearable and wireless systems for movement disorder evaluation, such as Parkinson’s disease and Essential tremor. These observations are brought together in the application of quantified feedback for deep brain stimulation systems using the wireless accelerometer and gyroscope of a smartphone to determine tuning efficacy. The perspective of the book ranges from the pioneering application of these devices, such as the smartphone, for quantifying Parkinson’s disease and Essential tremor characteristics, to the current state of the art. Dr. LeMoyne has published multiple first-of-their-kind applications using smartphones to quantify movement disorder, with associated extrapolation to portable media devices.

Wearable and Wireless Systems for Healthcare

Author: Robert Charles LeMoyne

Publisher:

Published: 2019

Total Pages: 128

ISBN-13: 9789811358098

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Machine Learning - A Journey To Deep Learning: With Exercises And Answers

Author: Andreas Miroslaus Wichert

Publisher: World Scientific

Published: 2021-01-26

Total Pages: 641

ISBN-13: 9811234078

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This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.Related Link(s)

Deep Learning in Smart eHealth Systems

Author: Asma Channa

Publisher: Springer Nature

Published: 2023-12-07

Total Pages: 102

ISBN-13: 3031450035

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One of the main benefits of this book is that it presents a comprehensive and innovative eHealth framework that leverages deep learning and IoT wearable devices for the evaluation of Parkinson's disease patients. This framework offers a new way to assess and monitor patients' motor deficits in a personalized and automated way, improving the efficiency and accuracy of diagnosis and treatment. Compared to other books on eHealth and Parkinson's disease, this book offers a unique perspective and solution to the challenges facing patients and healthcare providers. It combines state-of-the-art technology, such as wearable devices and deep learning algorithms, with clinical expertise to develop a personalized and efficient evaluation framework for Parkinson's disease patients. This book provides a roadmap for the integration of cutting-edge technology into clinical practice, paving the way for more effective and patient-centered healthcare. To understand this book, readers should have a basic knowledge of eHealth, IoT, deep learning, and Parkinson's disease. However, the book provides clear explanations and examples to make the content accessible to a wider audience, including researchers, practitioners, and students interested in the intersection of technology and healthcare.

Digital Technologies in Movement Disorders

Author:

Publisher: Elsevier

Published: 2023-07-24

Total Pages: 314

ISBN-13: 0323992382

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Digital Technologies in Movement Disorders, Volume Five updates on the latest advances in new technologies for the care of common conditions, including Parkinson’s disease and other diseases. The book has been organized in four differentiated sections with chapters that cover an Introduction, key concepts, and overview of digital solutions, Applications of AI in MD, Digital Biomarkers in MD, Sensors basic concepts for the MD specialist, Wearable systems in MD, Quantitative gait analysis, The challenges and opportunities of remote evaluation in MD, Telemedicine in MD, ePROs, eCOA and other digital health solutions, HIFU, Telerrehabilition and other therapeutical applications of technology, and more. Includes a multidisciplinary review of topics such as the input of care providers and engineers Reviews new technological advances Includes practice oriented technologies and innovations that have direct applications in the clinic

Handbook of Digital Technologies in Movement Disorders

Author: Roongroj Bhidayasiri

Publisher: Elsevier

Published: 2024-01-20

Total Pages: 366

ISBN-13: 0323994954

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Over the past few years, there have been fundamental changes in the diagnosing and treating patients with chronic diseases, significantly affecting management of neurological movement disorders. In addition, the health and fitness sector developed several devices to better classify, track, and potentially treat chronic diseases. Both handling and interpreting these large datasets has been revolutionized, by machine and deep learning approaches, leading to new and more effective therapies, resulting in longer survival rates. Handbook of Digital Technologies in Movement Disorders aims to unite these factors to provide a comprehensive guide to patient focused treatments for movement disorders. This book is divided into five distinct sections, starting with an introduction to digital technologies, concepts, and terminologies. The following section reviews various perspectives on technology in movement disorders, including patient and medical professionals. The third section presents technologies used in detecting, measuring progression, and determining response to treatments. This is followed by reviewing the technology used in various treatments of movement disorders including assistive and robotic technologies. Finally, the last section examines the challenges with technology including privacy and other ethical issues. Reviews different stakeholders' perspectives on technology in movement disorders Presents technological advancements for diagnosing, monitoring, and managing Parkinson’s disease Discusses challenges with implementing technology into treatment

Granular Video Computing

Author: Debarati B Chakraborty

Publisher: World Scientific Publishing Company

Published: 2021

Total Pages: 0

ISBN-13: 9789811227110

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This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training.This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing.