Integrating Artificial Intelligence and IoT for Advanced Health Informatics: AI in the Healthcare Sector

Preface
	References
Contents
Authors and Contributors
	About the Authors
	Contributors
Lower-Gait Tracking Application Using Smartphones and Tablets
	1 Introduction
	2 Materials and Methods
		2.1 Mobility Analysis Workflow
		2.2 Mobile Application and Devices
		2.3 Vicon Motion Capture System
	3 Results and Discussion
		3.1 Main Features of the LGait Mobile App
		3.2 Measurements Verification
		3.3 Discussion
	4 Conclusion
	References
One-Class Classification Approach in Accelerometer-Based Remote Monitoring of Physical Activities for Healthcare Applications
	1 Use Cases of HAR in Healthcare
	2 System Architecture of HAR with IoT Integration
	3 Components of HAR System
		3.1 Data Acquisition with Sensors
		3.2 Data Communication
		3.3 Knowledge Discovery
			3.3.1 Feature Extraction
			3.3.2 Classification
			3.3.3 Segmentation
	4 One-Class Classification (OCC)
		4.1 How to Generate Negative Class Data
	5 IoT Testbed for OCC-Based Recognition
	6 Dataset
	7 Experimental Setup and Results
	8 Chapter Summary
	References
Detecting and Monitoring Behavioural Patterns in Individuals with Cognitive Disorders in the Home Environment with Partial Annotations
	1 Introduction
	2 The CUBOId Project
	3 Visualising Sensor Data
	4 Methods
		4.1 Indoor Localisation
		4.2 Machine Learning Models for Indoor Localisation
		4.3 Model Selection with Weak Labels
	5 Findings
		5.1 Sleep Disturbance
		5.2 Wandering
		5.3 Shadowing
		5.4 Identifying Change and Confounders
	6 Conclusions and Future Work
	References
Toward On-Device Weight Monitoring from Selfie Face Images Using Smartphones
	1 Introduction
		1.1 Our Contribution
	2 Prior Work
	3 Inference on the Server or on the Device
	4 Convolutional Neural Networks Used
	5 Experimental Validations
		5.1 Dataset and Protocol
		5.2 Results
	6 Conclusion and Future Work
	References
Convergence Between IoT and AI for Smart Health and Predictive Medicine
	1 Introduction
	2 Exploring IoT Technologies for Smart Healthcare
	3 Exploring AI Techniques for Smart Healthcare
	4 Opportunity and Obstacles of IoT and AI Integration
		4.1 Benefits
		4.2 Challenges
	5 Conclusion
	References
An Artificial Intelligence and Internet of Things Platform for Healthcare and Industrial Applications
	1 Introduction
	2 A Large-Scale AI and IoT Platform
		2.1 AI Platform for Face Recognition
			2.1.1 Introduction to Face Recognition
			2.1.2 System Function Stacks
			2.1.3 AI Pipeline
			2.1.4 AI Engine: Feature Vector Extractor
			2.1.5 Search Engine
		2.2 IoT Platform
			2.2.1 The IoT Pipeline
			2.2.2 IoT Device Protocols
			2.2.3 Web/Mobile App API Management
	3 Application of the AI Platform in Tracing COVID-19 Patients and Close Contacts
		3.1 Motivation
		3.2 Fever Screening Camera
		3.3 Tracing Fever Patients and Close Contacts
		3.4 Demonstration of the User Console
	4 Industrial Applications of the IoT Platform
	5 Potential AI+IoT Application in Healthcare
		5.1 Summary of Platform Features
		5.2 Application in COVID-19 Diagnosis
		5.3 Integration to Platform
	6 Conclusions
	References
Methods in Digital Mental Health: Smartphone-Based Assessment and Intervention for Stress, Anxiety, and Depression
	1 Introduction: Short Morphogenesis of Assessment and Intervention
	2 Digital Metamorphosis of Assessment and Intervention
		2.1 Related Work
		2.2 Digital Assessment
			2.2.1 Stress
			2.2.2 Anxiety
			2.2.3 Depression
		2.3 Digital Intervention
			2.3.1 Stress
			2.3.2 Anxiety and Depression
	3 Conclusion: Speculative Evolution of Assessment and Intervention
	References
AI for the Detection of the Diabetic Retinopathy
	1 Introduction
	2 Diabetic Retinopathy
	3 The Contribution of AI for the Detection of the Diabetic Retinopathy
	4 Concluding Remarks
	References
Enhancing EEG-Based Emotion Recognition with Fast Online Instance Transfer
	1 Introduction
	2 Related Work
	3 Methods
		3.1 Conceptual Ideas for the Fast Online Transfer
		3.2 Fast Online Instance Transfer
			3.2.1 Model Weighting
			3.2.2 Instance Selection
			3.2.3 Model Ensemble
		3.3 Active Learning
		3.4 Transfer Component Analysis
		3.5 Multi-Source Style Transfer Mapping
	4 Experiments and Results
		4.1 Dataset
		4.2 Preprocessing
		4.3 Implementation Details
		4.4 Comparison with Baselines
		4.5 Ablation Experiments
		4.6 Comparison with Other Methods
		4.7 Additional Evaluations
	5 Discussions
	6 Conclusion
	References
Using Association Rules to Mine Actionable Knowledge from Internet of Medical Thinks Data
	1 Introduction
	2 Background
		2.1 Internet of Medical Thinks
		2.2 Association Rules
	3 Proposed Approach
	4 Conclusion
	References
Index