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Название: Intelligent Systems for Rehabilitation Engineering

Автор: Группа авторов

Издательство: John Wiley & Sons Limited

Жанр: Программы

Серия:

isbn: 9781119785637

isbn:

СКАЧАТЬ Kautish

      and

      Pradeep N

      This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA © 2022 Scrivener Publishing LLC

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       Library of Congress Cataloging-in-Publication Data

      ISBN 978-1-119-78566-8

      Cover image: Pixabay.Com

      Cover design by Russell Richardson

      Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines

      Printed in the USA

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      Preface

      Rehabilitation engineering uses engineering sciences to develop technological solutions and devices to assist individuals with disabilities and also supports the rehabilitation of those who have lost their physical and cognitive functions. Systems can be designed and built to meet a wide range of needs in order to help those with impaired mobility, communication, vision, hearing and cognition. And these tools and devices assist the disabled in their daily activities such as, for example, attending school or working.

      Intelligent systems have a wide range of technological developments which will enhance research in the field of rehabilitation engineering. The growing list of these developments, such as machine learning, deep learning, robotics, virtual intelligence, etc., plays an important role in rehabilitation engineering.

      The material collected in this book has been edited to provide information on current research achievements and challenges in the area of rehabilitation engineering and intelligent systems. The target audience of this book includes senior and junior engineers, undergraduate and postgraduate students, researchers, and anyone else interested in the trends, developments, and opportunities of rehabilitation engineering and intelligent system concepts. Research trends in the design and development of innovative technologies are highlighted along with the techniques involved. And even though it is impossible to include all current aspects of the research being conducted in targeted areas, the book is a useful resource in terms of presenting the various possible methodologies that can be applied to achieve results in the field. Presented below is a brief description of the topics covered in the 10 chapters of the book.

      – Chapter 2 reviews the use of neurorehabilitation robots for an automated process for the upper limb. This chapter illustrates and defines all areas of mechanical recovery technology for novices, and captures the recent robot advances being widely used by talented scientists and clinicians. Also, a few company devices for mechanical recovery are given for a better understanding of the complete picture. The use of productive robotic methodologies promotes the recovery of motor skills. This innovation combines the outcomes of social investigations on motor learning and neurological recovery in the creation and execution of automated processes, with the approval of robot specialists who operate as ideal instructors. Human-robot collaboration assumes a leading role in creating a beneficial relationship, where the human body and the robot can benefit from each other’s components.

      – Chapter 3 highlights an effective affordable rehabilitation robot for nervous system disorders powered by dynamic convolutional neural network (CNN) and hidden Markov model (HMM). Neurological disorders are a frequent health concern of billions of individuals around the world. This condition is caused by malfunctioning of the central and peripheral nervous systems. For example, Alzheimer’s and Parkinson’s diseases are not uncommon and wreck the lives of many people. In particular, those afflicted with Parkinson’s disease have impaired movement resulting in freezing of gait (FOG). The only accessible treatment option is the artificial creation of dopamine levels. Therefore, robotic rehabilitation devices have been proposed which apply vibrations to activate muscle performance. These bracelets, bands, and chains are part of the sensors which are fixed to the patient’s body. For processing sensor signals and decision-making, CNN and HMM are used.