Smart Systems for E-Health: WBAN Technologies, Security and Applications (Advanced Information and Knowledge Processing)

✍ Scribed by Hanen Idoudi (editor), Thierry Val (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 239
• Category: Library

✦ Synopsis

The purpose of this book is to review the recent advances in E-health technologies and applications. In particular, the book investigates the recent advancements in physical design of medical devices, signal processing and emergent wireless technologies for E-health. In a second part, novel security and privacy solutions for IoT-based E-health applications are presented. The last part of the book is focused on applications, data mining and data analytics for E-health using artificial intelligence and cloud infrastructure.

E-health has been an evolving concept since its inception, due to the numerous technologies that can be adapted to offer new innovative and efficient E-health applications. Recently, with the tremendous advancement of wireless technologies, sensors and wearable devices and software technologies, new opportunities have arisen and transformed the E-health field. Moreover, with the expansion of the Internet of Things, and the huge amount of data that connected E-health devices and applications are generating, it is also mandatory to address new challenges related to the data management, applications management and their security. Through this book, readers will be introduced to all these concepts.

This book is intended for all practitioners (industrial and academic) interested in widening their knowledge in wireless communications and embedded technologies applied to E-health, cloud computing, artificial intelligence and big data for E-health applications and security issues in E-health.

✦ Table of Contents

Introduction
The Layout of this Book
Contents
Editors and Contributors
About the Editors
Contributors
Part I Physical Design of Medical Devices, Signal Processing and Emergent Wireless Technologies for E-Health
1 Design and Control of Multifunctional, Multiarticulate Prosthetic Hand
1.1 Introduction
1.2 EMG Signal Pre-processing and Envelope Detection
1.2.1 Different Category of EMG Noise
1.2.2 Denoising
1.2.3 Envelope Detection
1.2.4 Feature Extraction
1.2.5 Frequency Domain
1.2.6 Time–frequency Domain
1.3 Intelligent Control
1.3.1 Support Vector Machine (SVM) [30]
1.3.2 Artificial Neural Network (ANN) [30] and [31]
1.3.3 K-Nearest Neighbour (KNN) [24]
1.3.4 Linear Discriminant Analysis (LDA) [23, 31]
1.4 Software and Hardware Implementation
1.4.1 Mechanical Design
1.4.2 Electrical Requirement and Specification
1.5 Results and Discussion
1.6 Conclusion
References
2 A Mobile Computing Solution for Enhanced Living Environments and Healthcare Based on Internet of Things
2.1 Introduction
2.2 Internet of Things
2.3 Smart Homes
2.4 Indoor Air Quality
2.5 Materials and Methods
2.6 Results and Discussion
2.7 Conclusion
References
3 Rapid Medical Images Restoration Combining Parametric Wiener Filtering and Wave Atom Transform Based on Local Adaptive Shrinkage
3.1 Introduction
3.2 Image Degradation Process
3.2.1 Notion of Blur
3.2.2 Various Types of Image Blur
3.2.3 Mathematical Formulation of Image Degradation
3.3 Image Restoration Process
3.3.1 Deconvolution in the Spectral Domain
3.3.2 Denoising in the Wave Atom Domain
3.4 Experimental Results
3.4.1 Numerical Results Using Gaussian Blur
3.4.2 Numerical Results Using Motion Blur
3.5 Discussion
3.6 Conclusion
References
Part II Security and Privacy in IoT-Based E-Health Applications
4 BlockCare: SDN-Enabled Blockchain Framework for Securing Decentralized Healthcare and Precision Medicine Applications
4.1 Introduction
4.2 Background on Enabling Technologies
4.2.1 Overview of Blockchain and Its Use in Health Care
4.2.2 Overview of SDN and NFV
4.2.3 SDN-Enabled Blockchain
4.3 Key Technical Requirements for SDN-Enabled Blockchain
4.3.1 Requirement 1: Dealing with Fragmented Data
4.3.2 Requirement 2: System Interoperability
4.3.3 Requirement 3: Consistent and Secure Data Access, Storage, and Exchange
4.3.4 Requirement 4: Identity Verification and Participant Authentication
4.3.5 Requirement 5: Timely Access, Cost Effectiveness, and Maintaining Modularity
4.4 BlockCare: SDN-Enabled Blockchain for Scalable and Tamper-Resistant Healthcare Network
4.4.1 BlockCare System Design
4.4.2 Smart Contract
4.5 Use Cases
4.5.1 Blockchain Technology for Smart Healthcare Clinical Trials
4.5.2 Blockchain Technology for Improving Precision Medicine
4.5.3 Blockchain Technology in Pharmaceutical Supply Chain
4.6 Open Challenges and Ensuing Directions for Future Work
4.6.1 Scalability Issues
4.6.2 Power Consumption
4.6.3 Storage
4.6.4 Privacy Leakage
4.6.5 Smart Contract Risks and Governing Regulatory Status
4.7 Possible Future Directions
4.7.1 Off-Chain Computation
4.7.2 Big Data Analytics
4.7.3 Artificial Intelligence
4.7.4 Smart Contracts
4.8 Conclusion
References
5 IoT Performability for Medical Wearable Device by Data Privacy and Fault Tolerance
5.1 Introduction
5.2 IoT and Biomedical Wearable Devices—Evolution, Perspectives and Challenges
5.3 Security Risks and Safety Concerns for Using Wearable Devices
5.3.1 Safety and Privacy Aspects Related to Wearable Medical Devices
5.3.2 Information Privacy for Medical Records
5.4 Personal Data Management in Private Cloud Versus Public Cloud for Data Analytics
5.5 Methods for IoT Wearable Risks Reduction by Data Anonymization
5.5.1 Methods Used in Statistical Disclosure Control
5.5.2 Statistical Disclosure Control for Medical Data
5.6 Future Challenges for Wearable IoT Technologies for Healthcare
5.7 Conclusions
References
6 Toward Trustworthy Cognitive Radio-Based Internet of Medical Things
6.1 Introduction
6.2 Cognitive Radio Solution
6.2.1 Cognitive Radio
6.2.2 Cycle Cognition
6.2.3 Software-Defined Cognitive Radio (SDCR) Network
6.3 Motivations for Using CR in IoMT
6.3.1 Communication Range
6.3.2 Spectrum Scarcity
6.3.3 Interference
6.3.4 Connectivity Issues
6.3.5 Energetic Requirements
6.4 Challenges of the Integration of CR in the IoMT
6.4.1 Sensing Capabilities
6.4.2 Software Radio Issues
6.4.3 Hardware Issues
6.4.4 Security Issues
6.5 Backgrounds
6.6 Trustworthy Proposed Mechanism
6.6.1 Description and Principals
6.6.2 Hierarchical Architecture
6.6.3 Assumptions
6.6.4 Cooperative Trustworthy Spectrum Sensing
6.7 Dynamic Multi-winners’ Spectrum Access Games
6.7.1 Competitive Game Models
6.7.2 Second Proposed Game Model
6.7.3 Game Model Analysis
6.7.4 Nash Equilibrium Analysis
6.8 Opportunistic Spectrum Scheduling Scheme
6.8.1 Scheduling Principals and Mechanism
6.8.2 Scheduling Algorithm
6.9 Simulations and Results
6.9.1 Spectrum Sensing (SS)
6.9.2 Data Routing
6.10 Conclusion
References
7 E-Health Threat Intelligence Within Cyber-Defence Framework for E-Health Organizations
7.1 Smart E-Health Systems
7.1.1 E-Health System Architecture
7.1.2 The Current State of Cybersecurity in E-Health
7.2 Review of E-Health Cybersecurity Models
7.2.1 E-Healthcare Encryption Algorithms
7.2.2 Types of Attack
7.2.3 E-Health Threat Intelligence
7.2.4 Event Correlation
7.2.5 Smart E-Health Gateway
7.3 Conclusion
References
Part III Applications, Data Mining and Data Analytics for E-Health
8 DAS-Autism: A Rule-Based System to Diagnose Autism Within Multi-valued Logic
8.1 Introduction
8.2 Autism Diagnosis
8.2.1 Description of the Domain
8.2.2 Autism Diagnosis Tools
8.3 Symbolic Knowledge-Based System
8.3.1 Knowledge Representation
8.3.2 Approximate Reasoning Based on Linguistic Modifiers
8.3.3 Knowledge-Based System Shell
8.4 Construction of DAS-Autism
8.4.1 Design of the Knowledge Base
8.4.2 Development of DAS-Autism
8.5 Experimental Study
8.6 Conclusion
Appendix 1. Extract from the Diagnosis Algorithm of DSM-IV-TR
Appendix 2. Extract from the Knowledge Base of DAS-Autism
References
9 Smart E-Health Home Supervision Systems
9.1 Introduction
9.2 Historical Review of the Technology Currently proposed
9.2.1 Home Instrumentation
9.2.2 Mixed Equipment: Patient at home
9.2.3 Tomorrow: “Patient” Involvement
9.3 Further Analysis of Health Technological Needs
9.3.1 Prevention
9.3.2 Prescription Follow-up
9.4 Obstacles to Real-Life Implementation
9.4.1 Economic Component
9.4.2 Organizational Component
9.5 What Technological Offer for Tomorrow?
9.6 Conclusion
References
10 Literature Review: Overview of Cancer Treatment and Prediction Approaches Based on Machine Learning
10.1 Introduction
10.2 Machine Learning
10.3 An Overview of Studies of the Literature
10.4 Others Studies and Approach’s
10.5 Conclusion
References