Technological Advancement in Internet of Medical Things and Blockchain for Personalized Healthcare

✍ Scribed by A Prasanth (editor), Lakshmi D (editor), Rajesh Kumar Dhanaraj (editor), Balamurugan Balusamy (editor)

• Publisher: CRC Press
• Year: 2024
• Tongue: English
• Leaves: 219
• Edition: 1
• Category: Library

✦ Synopsis

Technological Advancement in Internet of Medical Things and Blockchain for Personalized Healthcare presents an overview of the innovative concepts, technologies, and various biomedical applications of the Internet of Medical Things (IoMT).

Features:

• Provides insights into smart contracts, healthcare monitoring equipment, and the next generation of Internet of Things sensors to improve adherence to chronic disease management programs and patient health.

• Discusses the IoMT for personalized healthcare, security, and privacy issues of the IoMT in the healthcare sector.

• Elaborates on the opportunities and challenges of blockchain technology in the healthcare system.

• Focuses on the convergence of the IoMT and blockchain for emerging personalized healthcare systems.

• Presents techniques and methods to secure IoMT devices to protect them from cyberattacks.

This book is primarily written for graduate students and academic researchers working in the fields of computer science and engineering, biomedical engineering, and electrical engineering.

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
Table of Contents
About the Editors
Contributors
1 Advanced Enabling Technologies of IoMT in Personalized Healthcare
1.1 Introduction
1.2 IoMT Communication Protocols
1.3 Fog-Based Architecture of IoMT
1.3.1 Perception Layer
1.3.2 Fog Layer
1.3.3 Cloud Layer
1.4 Classification of IoMT Devices
1.4.1 On-Body Segment Medical Devices
1.4.1.1 Consumer-Based Medical Devices
1.4.1.2 Clinical-Grade Wearables
1.4.1.3 Implantable
1.4.2 In-Home Medical Devices
1.4.3 Community Segment Medical Devices
1.4.4 In-Hospital Segment Medical Devices
1.5 Enabling Technologies
1.5.1 Fog Computing
1.5.2 Blockchain Technology
1.5.3 Artificial Intelligence
1.5.4 Wearable Technology
1.6 Advancements of IOMT
1.6.1 Health Monitors [B HEAD]
1.6.2 Seizure Management
1.6.3 Wearable
1.6.4 Personal Assistants
1.6.5 Implantable
1.6.6 Robots
1.6.7 Prosthetics
1.6.8 Hygiene Management
1.7 Conclusion
References
2 Deep Learning Interpretation of Biomedical Data in IoMT
2.1 Introduction
2.1.1 IoMT
2.1.2 IoMT Architecture
2.1.3 IoMT Technology
2.1.4 Advantages of IoMT
2.1.5 Challenges of Implementing IoMT
2.1.6 Applications of IoMT in Healthcare
2.2 Role of Machine Learning In IoMT
2.3 Deep Learning in IoMT
2.3.1 Deep Learning Overview
2.3.2 Deep Learning in IoMT
a. Data Collection From IoMT
b. Cloud Storage
c. Deep Learning Mechanism
2.4 Deep Learning Algorithms in IoMT
2.4.1 Deep Neural Network (DNN)
2.4.2 Restricted Boltzmann Networks (RBNs) Or Auto Encoders
2.4.3 Deep Belief Networks (DBNs)
2.4.4 Generative Adversarial Networks (GANs)
2.4.5 Recurrent Neural Networks (RNNs)
2.4.6 Long Short-Term Memory
2.4.7 Convolutional Deep Neural Networks – CNNs
2.4.8 Transfer Learning Models
2.4.8.1 ResNet-34
2.4.8.2 DenseNet-121
2.4.8.3 DenseNet-201
2.4.8.4 VGG16
2.4.8.5 InceptionResNetV2
2.4.8.6 U-Net
2.4.8.7 SqueezeNet
2.5 Conclusion
References
3 Machine Learning for Decision Support Systems in IoMT
3.1 Introduction
3.2 Working of IoMT
3.2.1 Perception Layer
3.2.2 Gateway Layer
3.2.3 Management Service Layer
3.2.4 Application/Service Layer
3.3 ML Algorithms and Their Classification
3.3.1 Data in ML
3.4 Machine Learning Applications
3.4.1 Medical Imaging
3.4.2 Diagnosis of Disease
3.4.3 Behavioral Treatment
3.4.4 Clinical Trials
3.4.5 Smart Electronic Health Records
3.4.6 Epidemic Outbreak
3.4.7 Heart Disease Prediction
3.4.8 Prediction Models for COVID-19
3.4.9 Personalized Care
3.5 Role of IoT In Cardiometabolic Diseases Treatment
3.5.1 Design Outline and Physiological Parameters
3.5.2 Analysis of Cardiometabolic Risk
3.5.3 Remote Healthcare System
3.6 Mobile IoMT Device For Eye Examination
3.6.1 Eye Examination Device
3.6.1.1 Design
3.6.1.2 Additive Manufacturing
3.6.2 IoT Platform for Medical Analysis
3.6.2.1 Device Incorporated for Eye Examination
3.6.2.2 Remote Monitoring of Eye
3.6.3 Cornea Detection Using IoMT
3.6.3.1 Regeneration of Corneal Surface
3.6.3.2 Anomalies in Cornea
3.6.3.3 Keratitis
3.6.3.4 Corneal Mechanical Injuries
3.6.3.5 Conjunctivitis
3.6.3.6 Disorders at the Eyelid
3.6.3.7 Tumors and Benign Growths
3.6.4 Preliminary Test Results Observed From the IoMT-Based Remote Device
3.7 Conclusion
References
4 Secure Healthcare Systems: Recent and Future Applications
4.1 Introduction
4.2 System For Recent Applications
4.2.1 Raspberry Pi Controller
4.2.2 Heart Rate Sensor
4.2.3 Pulse Oximeter
4.2.4 Blood Pressure Sensor
4.2.5 Temperature Sensor
4.2.6 ECG Sensor
4.2.7 Position Sensor
4.3 Encryption Algorithms
4.3.1 Types of Encryption Algorithms
4.3.1.1 Triple DES
4.3.1.2 Advanced Encryption Standard
4.3.1.3 RSA Security
4.3.1.4 Blowfish
4.3.1.5 Two Fish
4.4 Blowfish Algorithm
4.5 System For Future Applications: Inexpensive Cardiac Arrhythmia Management System (Icarma)
4.6 Advantages of Remote Healthcare
4.7 Conclusion
References
5 Transforming Healthcare Management: Combining Blockchain, P2P Networks, and Digital Platforms
5.1 Introduction
5.1.1 Introduction to Patient-Centric Healthcare
5.1.2 Patient-Centric Blockchains
5.1.3 Advantages and Disadvantages of Using Blockchain in Healthcare
5.2 Multilayer P2P Networks
5.3 Digital Platforms In Healthcare
5.3.1 Healthcare Data Management Platforms
5.3.2 EHR Platforms
5.3.3 Health Information Exchange Platforms
5.3.4 Patient Engagement Platforms
5.3.5 Blockchain Platforms
5.4 Connecting Patient-Centric Blockchains With Multilayer P2P Networks
5.4.1 Challenges and Considerations
5.4.2 Connecting Patient-Centric Blockchains With Digital Platforms
5.5 Future Directions
5.5.1 Advances in Blockchain Technology
5.5.2 Growth of Interoperability
5.5.3 Artificial Intelligence and Machine Learning
5.5.4 Expansion of Telehealth
5.5.5 Regulatory Challenges
5.6 Conclusion
References
6 Convergence of IoMT and Blockchain for Emerging Personalized Healthcare System: Challenges and Use Cases
6.1 Introduction
6.2 Challenges In The Adoption of IoMT In Healthcare
6.3 Challenges In The Adoption of Blockchain Technology In Healthcare
6.4 Use Cases For Converging Blockchain Technology With IoMT In Personalized Healthcare Systems
6.5 Challenges In The Implementation Of A Personalized Healthcare System Based On The Convergence of IoMT And Blockchain Technology
6.6 Conclusion
References
7 Role of Access Control Mechanism for Blockchain-Enabled IoMT in Personalized Healthcare
7.1 Introduction
7.1.1 What Is IoMT?
7.2 Personalized Healthcare
7.2.1 Key Components of Personalized Healthcare
7.3 Role of IoMT In Personalized Healthcare
7.3.1 IoMT-Based Healthcare Monitoring Systems
7.3.2 Advantages of Integrating IoMT With Personalized Healthcare
7.4 Access Control Systems
7.4.1 Existing ACS
7.4.2 Drawbacks of the Existing ACS
7.5 Blockchain Technology
7.5.1 Blockchain as a Considerable Solution
7.6 Blockchain Security Systems
7.6.1 Proposed Architectures
7.6.2 Hyperledger Fabric
7.6.2.1 Hyperledger-Based Architectures
7.6.3 Blockchain-Based Architectures
7.6.4 Use Cases: IoMT-Based Blockchain Access Control Mechanisms
7.7 Conclusion And Future Work
References
8 Protecting the Privacy of IoT-Based Health Records Using Blockchain Technology
8.1 Introduction
8.2 Overview of Blockchain Technology
8.2.1 Blockchain Working Process
8.3 Background
8.3.1 Challenges in Healthcare
8.4 IoMT-Based Health Record Using Blockchain
8.5 Proposed Methodology
8.5.1 Data Management in IoMT-Based Health Records
8.5.2 Protecting the IoMT
8.5.3 Blockchain: An Effective Solution
8.6 Conclusion
References
9 Securing IoMT Devices to Protect the Future of Healthcare From Rising Cyberattacks
9.1 Introduction
9.1.1 ADHD
9.1.2 IoMT Device for Monitoring ADHD Child
9.1.2.1 IoMT Device Challenges
9.1.3 Artificial Intelligence
9.1.3.1 Artificial Intelligence in Cybersecurity
9.1.4 Blockchain Technology
9.1.4.1 Block Architecture of Blockchain Technology
9.2 Related Works
9.3 Proposed Work
9.4 Result And Discussions
9.5 Conclusion
References
10 Smart Hand-Hygiene Compliance and Temperature Monitoring System to Tackle COVID-19-Like Pathogens in Healthcare Institutions
10.1 Introduction
10.2 Related Works
10.2.1 Hand-Wash Systems in Patent Documents
10.2.1.1 Proximity Sensing-Based Hand-Wash Systems
10.2.1.2 Vision-Based Hand-Wash Monitoring
10.2.2 Hand-Wash Systems in Research Articles
10.2.2.1 Multi-Sensor And/or IoT-Based Systems
10.2.2.2 Vision-Based Hand-Wash Monitoring Systems Using Machine Learning
10.2.3 Off-The-Shelf Hand-Hygiene Monitoring Systems
10.3 Relation Between Hand Hygiene And Hai – A Pilot Study
10.4 Conceptual Design of The System
10.4.1 Hand-Wash Unit
10.4.2 Temperature Sensing Unit
10.4.3 Patient Side Monitoring Unit
10.4.4 Administrative Management and Messaging Unit
10.5 Detailed Design of System
10.6 Conclusion
References
11 LDS–LVAT: Lie Detection System–Layered Voice Technology
11.1 Introduction
11.1.1 Cybercrime Tools
11.1.1.1 Kali Linux
11.1.1.2 Oph Crack
11.1.1.3 EnCase
11.1.1.4 SafeBack
11.1.1.5 Data Dumper
11.1.1.6 Md5sum
11.1.2 Necessity of Detection of Cybercrime
11.1.2.1 Techniques for Detecting Cybercrime
11.1.3 Layered Voice Technology
11.1.3.1 Working of Layered Voice Analysis Work
11.1.3.2 Accuracy of Voice Lie Detector Test
11.1.3.3 Voice Stress Analysis
11.1.3.4 LVA 6.50 – Modes of Operation
11.1.3.5 LVA 6.50 Features
11.1.3.6 LVA and “Lie Detection”
11.1.4 General Questioning and Testing Techniques
11.2 Related Works
11.3 Proposed Work
11.3.1 Overview
11.3.1.1 Voice Analysis
11.3.1.2 Research Methodology
11.3.1.3 Algorithm of Overall System of Lie Detection System
11.3.2 Signal Preprocessing
11.3.3 Feature Extraction
11.3.4 Mel-Frequency Cepstrum Coefficient
11.3.4.1 Pre-Emphasis
11.3.4.2 Framing
11.3.4.3 Hamming Window
11.3.4.4 Fast Fourier Transform
11.3.5 Neural Networks and Lie Detection
11.4 Discussions
11.5 Conclusion
Acknowledgment
References
Index