The Internet of Medical Things (IoMT)

For more information about Scrivener publications please visit www.scrivenerpublishing.com.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

Wiley Global Headquarters

111 River Street, Hoboken, NJ 07030, USA

For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.

Limit of Liability/Disclaimer of Warranty

While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials, or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read.

Library of Congress Cataloging-in-Publication Data

ISBN 978-1-119-76883-8

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

10 9 8 7 6 5 4 3 2 1

It is a pleasure for us to put forth this book, The Internet of Medical Things (IoMT): Healthcare Transformation . Digital technologies have come into effect in various sectors of our daily lives and it has been successful in influencing and conceptualizing our day-to-day activities. The Internet of Medical Things is one such discipline which seeks a lot of interest as it combines various medical devices and allows these devices to have a conversation among themselves over a network to form a connection of advanced smart devices. This book helps to know about IoMT in the health care sector that involves the latest technological implementation in diagnostic level as well as therapeutic level. The security and privacy of maintaining the health records is a major concern and several solutions for the same has been discussed in this book. It provides significant advantages for the wellbeing of people by increasing the quality of life and reducing medical expenses. IoMT plays a major role in maintaining smart healthcare system as the security and privacy of the health records further leads to help the health care sector to be more secure and reliable. Artificial Intelligence is the other enabling technology that helps IoMT in building smart defensive mechanisms for a variety of applications like providing assistance for doctors in almost every area of their proficiencies such as clinical decision-making. Through Machine Learning and Deep Learning techniques, the system can learn normal and abnormal decisions using the data generated by the health worker/professionals and the patient feedback. This book demonstrates the connectivity between medical devices and sensors is streamlining clinical workflow management and leading to an overall improvement in patient care, both inside care facility walls and in remote locations. This book would be a good collection of state-of-the-art approaches for applications of IoMT in various health care sectors. It will be very beneficial for the new researchers and practitioners working in the field to quickly know the best methods for IoMT.

• Chapter 1concentrates on the study of the three-dimensional (3-D) models of lung cancer cell line proteins (epidermal growth factor (EGFR), K-Ras oncogene protein and tumor suppressor (TP53)). The generation and their binding affinities with curcumins, ellagic acid and quercetin through local docking were assessed.

• Chapter 2focuses on cloud computing and electronic health record system service EHR used to protect the confidentiality of patient sensitive information and must be encrypted before outsourcing information. This chapter focuses on the effective use of cloud data such as search keywords and data sharing and the challenging problem associated with the concept of soft computing.

• Chapter 3elucidates the study of cloud computing concepts, security concerns in clouds and data centers, live migration and its importance for cloud computing, and the role of virtual machine (VM) migration in cloud computing. It provides a holistic approach towards the pre-copy migration technique thereby explore the way for reducing the downtime and migration time. This chapter compares different pre-copy algorithms and evaluates its parameters for providing a better solution.

• Chapter 4concentrates on Deep Learning that has gained more interest in various fields like image classification, self-driven cars, natural language processing and healthcare applications. The chapter focuses on solving the complex problems in a more effective and efficient manner. It elaborates for the reader how deep learning techniques are useful for predicting and classification of the brain tumor cells. Datasets are trained using pre-trained neural networks such as Alexnet, Googlenet and Resnet 101 and performance of these networks are analysed in detail. Resnet 101 networks have achieved highest accuracy.

• Chapter 5illustrates an intelligent healthcare monitoring system for coma patients that examines the coma patient's vital signs on a continuous basis, detects the movement happening in the patient, and updates the information to the doctor and central station through IoMT. Consistent tracking and observation of these health issues improves medical assurance and allows for tracking coma events.

• Chapter 6details the Deep Learning process that resembles the human functions in processing and defining patterns used for decision-making. Deep learning algorithms are mainly designed and developed using neural networks performing unsupervised data that are unstructured. Biomedical data possess time and frequency domain features for analysis and classification. Thus, deep learning algorithms are used for interpretation and classification of biomedical big data.

• Chapter 7discusses how the electronic health records automates and streamlines the clinician’s workflow and makes the process easy. It has the ability to generate the complete history of the patient and also help in assisting for the further treatment which helps in the recovery of the patient in a more effective way. The electronic health records are designed according to the convenience depending on the sector it is being implemented. The main aim of electronic health records was to make it available to the concerned person wherever they are, to reduce the work load to maintain clinical book records and use the details for research purposes with the concerned persons acknowledgement.