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Table of Contents
1 Cover
5 Preface
7 1 Machine Learning Technologies in IoT EEG-Based Healthcare Prediction 1.1 Introduction 1.2 Related Works 1.3 Problem Definition 1.4 Research Methodology 1.5 Result and Discussion 1.6 Conclusion
8 2 Smart Health Application for Remote Tracking of Ambulatory Patients 2.1 Introduction 2.2 Literature Work 2.3 Smart Computing for Smart Health for Ambulatory Patients 2.4 Challenges With Smart Health 2.5 Security Threats 2.6 Applications of Fuzzy Set Theory in Healthcare and Medical Problems 2.7 Conclusion
9 3 Data-Driven Decision Making in IoT Healthcare Systems—COVID-19: A Case Study 3.1 Introduction 3.2 Experimental Analysis 3.3 Multi-Criteria Decision Making (MCDM) Procedure 3.4 Conclusion
10 4 Touch and Voice-Assisted Multilingual Communication Prototype for ICU Patients Specific to COVID-19 4.1 Introduction and Motivation 4.2 Proposed Prototype of Touch and Voice-Assisted Multilingual Communication 4.3 A Sample Case Study 4.4 Conclusion
11 5 Cloud-Assisted IoT System for Epidemic Disease Detection and Spread Monitoring 5.1 Introduction 5.2 Background & Related Works 5.3 Proposed Model 5.4 Methodology 5.5 Performance Analysis 5.6 Future Research Direction 5.7 Conclusion
12 6 Impact of Healthcare 4.0 Technologies for Future Capacity Building to Control Epidemic Diseases 6.1 Introduction 6.2 Background and Related Works 6.3 System Design and Architecture 6.4 Methodology 6.5 Performance Analysis 6.6 Future Research Direction 6.7 Conclusion
13 7 Security and Privacy of IoT Devices in Healthcare Systems 7.1 Introduction 7.2 Background and Related Works 7.3 Proposed System Design and Architecture 7.4 Methodology 7.5 Performance Analysis 7.6 Future Research Direction 7.7 Conclusion
14 8 An IoT-Based Diet Monitoring Healthcare System for Women 8.1 Introduction 8.2 Background 8.3 Necessity of Wearable Approach? 8.4 Different Approaches for Wearable Sensing 8.5 Description of the Methodology 8.6 Description of Various Components Used 8.7 Strategy of Communication for Wearable Systems 8.8 Conclusion
15 9 A Secure Framework for Protecting Clinical Data in Medical IoT Environment
