Medical Internet of Things: Techniques, Practices and Applications
- Length: 244 pages
- Edition: 1
- Language: English
- Publisher: Chapman and Hall/CRC
- Publication Date: 2021-10-29
- ISBN-10: 0367331233
- ISBN-13: 9780367331238
- Sales Rank: #0 (See Top 100 Books)
In recent years, the Medical Internet of Things (MIoT) has emerged as one of the most helpful technological gifts to mankind. With the incredible development in data science, big data technologies, IoT and embedded systems, it is now possible to collect a huge amount of sensitive and personal data, compile it and store it through cloud or edge computing techniques. However, important concerns remain about security and privacy, the preservation of sensitive and personal data, and the efficient transfer, storage and processing of MIoT-based data.
Medical Internet of Things: Techniques, Practices and Applications is an attempt to explore new ideas and novel techniques in the area of MIoT. The book is composed of fifteen chapters discussing basic concepts, issues, challenges, case studies and applications in MIoT.
This book offers novel advances and applications of MIoT in a precise and clear manner to the research community to achieve in-depth knowledge in the field. This book will help those interested in the field as well as researchers to gain insight into different concepts and their importance in multifaceted applications of real life. This has been done to make the book more flexible and to stimulate further interest in the topic.
Features:
- A systematic overview of concepts in Medical Internet of Things (MIoT) is included.
- Recent research and some pointers on future advancements in MIoT are discussed.
- Examples and case studies are included.
- It is written in an easy-to-understand style with the help of numerous figures and datasets.
This book serves as a reference book for scientific investigators who are interested in working on MIoT, as well as researchers developing methodology in this field. It may also be used as a textbook for postgraduate-level courses in computer science or information technology.
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 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 15.5.2 NREM Stage 15.5.3 NREM Stage 15.5.4 REM Sleep 15.6 Summary and Conclusion References Index
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