Smart Healthcare System Design

SMART HEALTHCARE SYSTEM DESIGN

This book deeply discusses the major challenges and issues for security and privacy aspects of smart health-care systems.

The Internet-of-Things (IoT) has emerged as a powerful and promising technology, and though it has significant technological, social, and economic impacts, it also poses new security and privacy challenges. Compared with the traditional internet, the IoT has various embedded devices, mobile devices, a server, and the cloud, with different capabilities to support multiple services. The pervasiveness of these devices represents a huge attack surface and, since the IoT connects cyberspace to physical space, known as a cyber-physical system, IoT attacks not only have an impact on information systems, but also affect physical infrastructure, the environment, and even human security.

The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies.

Smart Healthcare System Design covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus is on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations.

Audience: Researchers and industry engineers in information technology, artificial intelligence, cyber security, as well as designers of healthcare systems, will find this book very valuable.

Auteur

SK Hafizul Islam received his PhD degree in the Computer Science and Engineering in 2013 from the Indian Institute of Technology [IIT (ISM)] Dhanbad, Jharkhand, India. He is an assistant professor in the Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani (IIIT Kalyani), West Bengal, India. He has authored or coauthored 110 research papers in journals and conference proceedings.

Debabrata Samanta is an assistant professor in the Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India. He obtained his PhD in Computer Science and Engg. from the National Institute of Technology, Durgapur, India, in the area of SAR Image Processing. He is the owner of 17 Indian patents and has authored and coauthored more than 135 research papers in international journals.

Texte du rabat

The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions; which is why this book will prove invaluable to professionals who want to increase their understanding of recent challenges in the IoT-enabled healthcare domain. The 14 chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, and implementation issues, and also include several case studies.

Smart Healthcare System: Security and Privacy Aspects covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus will be on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations. More particularly, this volume consists of 14 chapters contributed by authors well-versed in the subject who are devoted to reporting the latest findings on smart healthcare system design.

Contenu

Preface xvii

Acknowledgments xxiii

1 Machine Learning Technologies in IoT EEG-Based Healthcare Prediction 1
*Karthikeyan M.P., Krishnaveni K. and Muthumani N.*

1.1 Introduction 2

1.1.1 Descriptive Analytics 3

1.1.2 Analytical Methods 3

1.1.3 Predictive Analysis 4

1.1.4 Behavioral Analysis 4

1.1.5 Data Interpretation 4

1.1.6 Classification 4

1.2 Related Works 7

1.3 Problem Definition 9

1.4 Research Methodology 9

1.4.1 Components Used 10

1.4.2 Specifications and Description About Components 10

1.4.2.1 Arduino 10

1.4.2.2 EEG SensorMindwave Mobile Headset 11

1.4.2.3 Raspberry pi 12

1.4.2.4 Working 13

1.4.3 Cloud Feature Extraction 13

1.4.4 Feature Optimization 14

1.4.5 Classification and Validation 15

1.5 Result and Discussion 16

1.5.1 Result 16

1.5.2 Discussion 23

1.6 Conclusion 27

1.6.1 Future Scope 27

References 28

2 Smart Health Application for Remote Tracking of Ambulatory Patients 33
*Shariq Aziz Butt, Muhammad Waqas Anjum, Syed Areeb Hassan, Arindam Garai and Edeh Michael Onyema*

2.1 Introduction 34

2.2 Literature Work 34

2.3 Smart Computing for Smart Health for Ambulatory Patients 35

2.4 Challenges With Smart Health 36

2.4.1 Emergency Support 36

2.4.2 The Issue With Chronic Disease Monitoring 38

2.4.3 An Issue With the Tele-Medication 38

2.4.4 Mobility of Doctor 40

2.4.5 Application User Interface Issue 40

2.5 Security Threats 41

2.5.1 Identity Privacy 41

2.5.2 Query Privacy 42

2.5.3 Location of Privacy 42

2.5.4 Footprint Privacy and Owner Privacy 43

2.6 Applications of Fuzzy Set Theory in Healthcare and Medical Problems 43

2.7 Conclusion 51

References 51

3 Data-Driven Decision Making in IoT Healthcare SystemsCOVID-19: A Case Study 57
*Saroja S., Haseena S. and Blessa Binolin Pepsi M.*

3.1 Introduction 58

3.1.1 Pre-Processing 59

3.1.2 Classification Algorithms 60

3.1.2.1 Dummy Classifier 60

3.1.2.2 Support Vector Machine (SVM) 60

3.1.2.3 Gradient Boosting 61

3.1.2.4 Random Forest 62

3.1.2.5 Ada Boost 63

3.2 Experimental Analysis 63

3.3 Multi-Criteria Decision Making (MCDM) Procedure 63

3.3.1 Simple Multi Attribute Rating Technique (SMART) 64

3.3.1.1 COVID-19 Disease Classification Using SMART 64

3.3.2 Weighted Product Model (WPM) 66

3.3.2.1 COVID-19 Disease Classification Using WPM 66

3.3.3 Method for Order Preference by Similarity to the Ideal Solution (TOPSIS) 67

3.3.3.1 COVID-19 Disease Classification Using TOPSIS 68

3.4 Conclusion 69

References 69

4 Touch and Voice-Assisted Multilingual Communication Prototype for ICU Patients Specific to COVID-19 71
*B. Rajesh Kanna and C.Vijayalakshmi*

4.1 Introduction and Motivation 72

4.1.1 Existing Interaction Approaches and Technology 73

4.1.2 Challenges and Gaps 74

4.2 Proposed Prototype of Touch and Voice-Assisted Multilingual Communication 75

4.3 A Sample Case Study 82

4.4 Conclusion 82

References 84

5 Cloud-Assisted IoT System for Epidemic Disease Detection and Spread Monitoring 87
*Himadri Nath Saha, Reek Roy and Sumanta Chakraborty*

5.1 Introduction 88

5.2 Background & Related Works 92

5.3 Proposed Model 98

5.3.1 ThinkSpeak 100

5.3.2 Blood Oxygen Saturation (SpO2) 100

5.3.3 Blood Pressure (BP) 101

5.3.4 Electrocardiogram (ECG) 101

5.3.5 Body Temperature (BT) 102 5.…