Medical Internet of Things: Techniques, Practices and Applications

Cover
Half Title
Title Page
Copyright Page
Contents
Preface
Editors
Contributors
1. IoT in the Healthcare Industry
	1.1 Introduction
	1.2 Need Analysis and Beneficiaries
		1.2.1 Monitoring In-House (i.e., within Hospital or Clinics)
		1.2.2 Patients\' Movement within Hospitals and Other Management
	1.3 Doctors\' Perspective
	1.4 Health Cost Reduction
	1.5 Data Management of Patients for Administrative Purposes
	1.6 IoT in the Healthcare Industry
		1.6.1 Topology
		1.6.2 Architecture
	1.7 Platforms
		1.7.1 Applications and Services
	1.8 Conclusion
	References
2. Asynchronous BCI (Brain–Computer Interface) Switch for an Alarm
	2.1 Introduction
	2.2 Review of Related Works
		2.2.1 Different Brain Waves in the Brain
		2.2.2 Electroencephalogram (EEG)
			2.2.2.1 Categories of EEG-Based BCIs
			2.2.2.2 Mechanism of the EEG
			2.2.2.3 Non-Invasive EEG Sensor Setup
			2.2.2.4 Circuit Components of a Non-Invasive EEG Transducer
	2.3 Proposed Work: EEG-Based Simple Spontaneous Asynchronous BCI Switch (SSABS)
		2.3.1 Logical Components of the EEG Device Used in the BCI Switch
		2.3.2 Workflow of the EEG-Based Simple Spontaneous Asynchronous BCI Switch (SSABS)
		2.3.3 Salient Features of the Proposed Model
	2.4 Conclusion
	References
3. Preprocessing and Discrimination of Cytopathological Images
	3.1 Introduction: Importance of Preprocessing
	3.2 Enhancement
	3.3 Different Categories of Cytopathological Images
	3.4 Choice of Preprocessing Methods for Different Images
	3.5 Conclusion, Future Directions and Remarks
	References
4. Applications of Internet of Vehicles in the Medical Sector
	4.1 Introduction
		4.1.1 Concept and Definition of IoV
	4.2 Architecture of IoV
	4.3 IoV Coordination Computing Based on Virtual Vehicle
	4.4 Related Works
	4.5 Benefits of IoV
		4.5.1 IoV over VANETs
	4.6 Challenges and Issues
		4.6.1 Localization Accuracy
		4.6.2 Location Privacy
		4.6.3 Location Verification
		4.6.4 Radio Propagation Model
		4.6.5 Operational Management
	4.7 Applications
	4.8 Conclusion
	References
5. CNN-Based Melanoma Detection with Denoising Autoencoder for Content-Based Image Classification
	5.1 Introduction
	5.2 Related Work
	5.3 Methodology
	5.4 Denoising Technique
		5.4.1 Autoencoders
		5.4.2 Denoising Autoencoder (DAE)
		5.4.3 Convolutional Neural Network (CNN)
		5.4.4 Convolution Autoencoder (CAE)
		5.4.5 Encoder
		5.4.6 Decoder
	5.5 Result and Discussion
	5.6 Conclusion
	References
6. IoT and Fog Computing-Based Smart Irrigation System for the Planting Medicinal Plants
	6.1 Introduction
	6.2 Literature Survey
	6.3 Proposed Work
		6.3.1 Benefits of Keeping Medicinal Plants
	6.4 Proposed Algorithm
	6.5 Results
	6.6 Conclusion and Future Scope
	References
7. IoT Networks for Healthcare
	7.1 Introduction
	7.2 Data Communication in IoT
		7.2.1 RFID
		7.2.2 Near-Field Communication (NFC)
		7.2.3 Bluetooth
		7.2.4 WiFi
		7.2.5 Global System for Mobile Communication (GSM)
	7.3 Power Conservation in IoT Devices
		7.3.1 MCU Design
		7.3.2 Sensor Operating Principles
		7.3.3 Radio Frequency Selection
		7.3.4 Bluetooth BLE
		7.3.5 WiFi
		7.3.6 Cellular
	7.4 Technology for IoT
		7.4.1 Infrastructure
		7.4.2 Identification
		7.4.3 Communication
		7.4.4 Discovery
		7.4.5 Data Protocols
		7.4.6 Device Management
	7.5 IoT Device Integration Protocol and Middleware
	7.6 Reliable and Secure Communication
		7.6.1 Authentication at Network Entry
		7.6.2 Secured Connection to a Distant Peer
	7.7 IoT in Healthcare
		7.7.1 Cancer Treatment
		7.7.2 CGM and InPen
		7.7.3 Artificial Pancreas and OpenAPS
		7.7.4 Connected Inhalers
		7.7.4 Ingestible Sensors
		7.7.5 Connected Contact Lenses
		7.7.6 The Apple Watch App that Monitors Depression
		7.7.7 Coagulation Testing
		7.7.8 Apple\'s Research Kit and Parkinson\'s Disease
		7.7.9 ADAMM Asthma Monitor
	7.8 Challenges in the IoT Healthcare Sector
		7.8.1 Most IoT Initiatives Are Incomplete or Unsuccessful
		7.8.2 Healthcare Will Generate a Tremendous Amount of Data
		7.8.3 IoT Devices Increase Available Attack Surfaces
		7.8.4 Outdated Infrastructure Hinders the Medical Industry
		7.8.5 IoT Poses Many Overlooked Obstacles
	7.9 Future Trends of IoT in Healthcare
	7.10 Conclusion
	References
8. Medical Internet of Things: Techniques, Practices and Applications
	8.1 Introduction: Importance of MIoT
	8.2 Challenges in MIoT
	8.3 Advances in MIoT
	8.4 Hardware and Software Challenges in MIoT
		8.4.1 Hardware Challenge
		8.4.2 Software Challenges
	8.5 Security and Privacy Issues in MIoT
		8.5.1 Data Integrity
		8.5.2 Authorization
		8.5.3 Cloud Storage
		8.5.4 Automation
	8.6 MIoT in Healthcare: Applications and Benefits
		8.6.1 Applications
		8.6.2 Benefits
	8.7 MIoT in Psychological Well-Being
	8.8 MIoT and Cloud Computing
		8.8.1 Cloud-Based Adherence Platforms Helping Patients Stay on Track
		8.8.2 Big Data and Predictive Technologies Enabling Preventive Action Ahead of Time
		8.8.3 Telemedicine Bringing Healthcare to Rural and Remote Areas
	8.9 MIoT and Big Data
	8.10 MIoT Innovations and Products
		8.10.1 Introduction
		8.10.2 Important Modules and Sensors
			8.10.2.1 MPU 6050 [26]
				8.10.2.1.1 Working Principle of MPU 6050
				8.10.2.1.2 Flowchart
				8.10.2.1.3 Pseudocode
				8.10.2.1.4 General Syntax of Notification SMS
				8.10.2.1.5 Benefits
	8.11 MIoT and 5G: The Future of Healthcare
	8.12 Conclusion
	References
9. Issues and Aspects of Medical IoT: A Case-Based Analysis
	9.1 Introduction
	9.2 IoT in Healthcare Networks
		9.2.1 The IoThNet Architecture
	9.3 IoT Healthcare Services and Applications
		9.3.1 Healthcare Services
		9.3.2 IoT Healthcare Applications
	9.4 Detection of an Ambulance on Toll Roads: A Case Study of MIoT Application
		9.4.1 Transportation Management System
			9.4.1.1 Importance of Having a TMS
			9.4.1.2 Who Uses a TMS?
			9.4.1.3 Plan, Execute and Optimize for Timely Delivery of Goods
			9.4.1.4 The Future of TMSs
		9.4.2 Radio-Frequency Identification (RFID)
			9.4.2.1 RFID Design
				9.4.2.1.1 Tags
				9.4.2.1.2 Readers
				9.4.2.1.3 Uses
		9.4.3 The Proposed Methodology
	9.5 Conclusion
	References
10. Diagnosis and Treatment of Cardiac Patients During the Pandemic Situation Due to COVID-19: Exploring Possible Application of MIoT
	10.1 Introduction
	10.2 Brief History of MIoT and Its Services
	10.3 Major Challenges in Cardiac Treatment in the Pandemic Period
	10.4 Role of MIoT in a Cardiac Patient\'s Diagnosis and Treatment
		10.4.1 Heart Disease Prediction System
	10.5 Requirement of Security Features
	10.6 Conclusion
	References
11. MIoT: Paralyzed Patient Healthcare
	11.1 Introduction
		11.1.1 Paralyzed Patient\'s Glove and Its Importance
		11.1.2 Important Modules and Sensors
		11.1.3 Working Principle
		11.1.4 Block Diagrams
		11.1.5 Hardware
		11.1.6 Software
		11.1.7 Pseudocode
		11.1.8 Benefits
		11.1.9 Possible Advancements
	11.2 Challenges in Development
		11.2.1 Hardware Challenges
		11.2.2 Software Challenges
		11.2.3 Network Challenges
	11.3 Security and Privacy
	11.4 Conclusion
	References
12. Vision-X: IoT-Based Smart Navigation System for People with Visual Challenges
	12.1 Introduction
	12.2 Literature Review
	12.3 Modeling of the Product
		12.3.1 Hardware Required
		12.3.2 Construct of Device
	12.4 Algorithms
		12.4.1 Ground and Obstacle Detection
		12.4.2 Modified K-Means Algorithm
		12.4.3 Human Detection
		12.4.4 Door Detection
			12.4.4.1 ROI Preprocessor
			12.4.4.2 Door Line and Feature Extraction
			12.4.4.3 Fuzzy Logic to Extract Doors
		12.4.5 Stair Detection
	12.5 Output
		12.5.1 Door Detection
		12.5.2 Human Detection
		12.5.3 Stair Detection
	12.6 Conclusion
	References
13. Analysis of Human Emotion-Based Data Using MIoT Technique
	13.1 Introduction
	13.2 IoT and the SIoT Concept
	13.3 SIoT in Healthcare
	13.4 What Is Galvanic Skin Response?
	13.5 Conclusion
	References
14. Understanding Explainable AI: Role in IoT-Based Disease Prediction and Diagnosis
	14.1 Introduction
	14.2 Limitations of Existing AI and IoT-Based Systems
	14.3 Need for Transformation of IoT by XAI
	14.4 What Is Explainable Artificial Intelligence (XAI) and How Does It Work?
	14.5 Overview of XAI Models
		14.5.1 Post-Hoc Systems
		14.5.2 Ante-Hoc Systems
	14.6 Examples of AI-Powered IoT-Based Disease Diagnosis and Prevention Platforms
	14.7 Explainable AI for Adverse Childhood Experiences
		14.7.1 Detecting Dementia
		14.7.2 Diagnosing Autism with an HIPAA-Compliant Platform
		14.7.3 Preventing Heart Diseases
		14.7.4 Preventing Pressure Injuries
		14.7.5 AI-Powered Pediatric Services
	14.8 Challenges of XAI in IoT-Based Platform and Future Prospects
	14.9 \"Omics\" Data, Bioinformatics and Future Scope of XAI in Disease Diagnostics
	14.10 Legal and Ethical Concerns
	14.11 Conclusion
	References
15. An Overview on Sleep, Sleep Stages and Sleep Behavior
	15.1 Introduction
	15.2 10-20 Electrode Placement System of EEG Recording
		15.2.1 Electrodes
		15.2.2 Montage
			15.2.2.1 Electroencephalogram (EEG) Electrodes
			15.2.2.2 Electrooculogram (EOG) Electrodes
			15.2.2.3 Electromyogram Electrodes (EMG)
			15.2.2.4 Electrocardiogram Electrodes (ECG)
			15.2.2.5 Respiratory Electrodes
	15.3 Human Sleep Staging Parameters
		15.3.1 Electroencephalographic Recording
		15.3.2 Electrooculogram Recording
		15.3.3 Electromyography Recording
	15.4 Behavior of EEG During Wakefulness and Sleep
		15.4.1 Alpha Activity
		15.4.2 Theta Activity
		15.4.3 Beta Activity
		15.4.4 Sleep Spindles
		15.4.5 K-Complexes
		15.4.6 Delta Activity
	15.5 Sleep Stages
		15.5.1 NREM Stage 1
		15.5.2 NREM Stage 2
		15.5.3 NREM Stage 3
		15.5.4 REM Sleep
	15.6 Summary and Conclusion
	References
Index