With rise of smart medical sensors, cloud computing and the health care technologies, “connected health” is getting remarkable consideration everywhere. Recently, the Internet of Things (IoT) has brought the vision of a smarter world into reality. Cloud computing fits well in this scenario as it can provide high quality of clinical experience. Thus an IoT-cloud convergence can play a vital role in healthcare by offering better insight of heterogeneous healthcare content supporting quality care. It can also support powerful processing and storage facilities of huge data to provide automated decision making. This book aims to report quality research on recent advances towards IoT-Cloud convergence for smart healthcare, more specifically to the state-of-the-art approaches, design, development and innovative use of those convergence methods for providing insights into healthcare service demands. Students, researchers, and medical experts in the field of information technology, medicine, cloud computing, soft computing technologies, IoT and the related fields can benefit from this handbook in handling real-time challenges in healthcare. Current books are limited to focus either on soft computing algorithms or smart healthcare. Integration of smart and cloud computing models in healthcare resulting in connected health is explored in detail in this book.
Author(s): Sushruta Mishra, Alfonso González-Briones, Akash Kumar Bhoi, Pradeep Kumar Mallick, Juan M. Corchado
Series: Studies in Computational Intelligence, 1021
Publisher: Springer
Year: 2022
Language: English
Pages: 486
City: Cham
Preface
Contents
Integration of Cloud and IoT for Smart e-Healthcare
1 Introduction
2 Literature Review
3 E-Health Systems IoT and Cloud Integration
4 Innovation and Enhancing e-Health Concepts
5 IoT Cloud-Based e-Health Improvement Services Difficulties
5.1 IoT-Cloud e-Health Systems Management of Resources
5.2 Electrical Equipment in e-Health Technologies Based on IoT Infrastructure
5.3 IoT Computing e-Health Solutions for Confidentiality and Protection
6 IoT-Cloud Based e-Health Systems Safety, Confidentiality, and Technical Requirements
6.1 Confidentiality in E-health Systems Based on IoT Cloud
6.2 Access to Available IoT-Cloud e-health Platforms
7 Limitations
7.1 Confidentiality in e-health Technologies Based on IoT Cloud
7.2 Context Awareness IoT-Cloud-Based e-Health Systems
7.3 Safety in e-health Systems Based on the IoT Cloud
8 IoT Cloud-Based e-Health Systems Constraints and Critical Problems
9 Conclusions and Future Work
References
Integration of Medical Internet of Things with Big Data in Healthcare Industry
1 Introduction
2 Healthcare as an IoT Repository
3 Healthcare as a Big Data Repository
4 Internet of Things to Improvise Healthcare
4.1 Related Work on IoT in Healthcare
5 Big Data to Improvise Healthcare
5.1 Related Work on BigData in Healthcare
6 Mobile Apps for Healthcare
6.1 Related Work on Mobile Apps for Healthcare
7 Advantages of IoT in Healthcare
7.1 Assists Non-Stop Tracking of one’s Fitness
7.2 Improves the Efficiency of Hospitals
7.3 Assists You in Keeping Tabs on Your Patients
7.4 Transparency in Insurance Claims
8 Advantages of Big Data in Healthcare
8.1 More Powerful Diagnosis and Treatment
8.2 Reduced Total Healthcare Expenditures
8.3 Better User Experience and Personalization
9 Challenges for IoT
9.1 Data Security and Privacy
9.2 Integration: Multiple Devices and Protocols
9.3 Simple Availability
9.4 Simple Gadget the Board
9.5 Data Ingestion
9.6 Educational Analytics
9.7 Reduced Danger
10 Challenges for Big Data in Healthcare
11 Current Challenges in the Personalized Healthcare
12 Case Study
12.1 TERUMOBCT
12.2 CitiusTech Technology Platforms
12.3 A Hospital Dashboard with Big Data in Healthcare
12.4 Telemedicine
13 Conclusion and Future Work
References
Decrypting the Black Boxing of Artificial Intelligence Using Explainable Artificial Intelligence in Smart Healthcare
1 Introduction
1.1 Explainable Artificial Intelligence (XAI)
1.2 Background
2 Transparency and Trust of AI in Biomedical Domain: Needs and Challenges
2.1 “Clever Han” Predictors Explanation
2.2 Explanations Foster Trust and Verifiability
2.3 Characteristics/Pillars of Explainable AI in Healthcare
3 Explanations AI Methods in Biomedical Domain
3.1 Framework for Interpreting Explicability and Trust in Healthcare
4 Quality Evaluating of Explanations in Biomedical Domain
4.1 How to Choose Amongst Different Explainable AI Methods?
4.2 XAI Evaluating Measurements
4.3 Some Existing Real-Time Case Studies on XAI in Healthcare
5 Conclusions
References
Soft Computing and Machine Learning Techniques for e-Health Data Analytics
1 Introduction
1.1 Diagnosis Process in Healthcare System
1.2 Artificial Intelligent Based Electronic Health Records
1.3 Soft Computing Based Clinical Diagnosis
1.4 BDA Tools
2 Analysis of AI and ML in Health Systems
3 Intellect Approaches in Healthcare
3.1 Role of AI and ML in Healthcare System
3.2 ML in Medicine
3.3 Growth of Clinical System
3.4 Development of Clinical Data Using AI
3.5 Detection of Illness in EHR
3.6 Cognitive Approaches for Cancer Diseases
3.7 Effective Operation in EHR
3.8 Approach of Deep Learning (DL) in Clinical System
3.9 Transform of Data in Healthcare
3.10 Cancer Prediction Using ML
4 Precision Medicine Approaches
4.1 Medicine with EMR Analysis
4.2 AI Based Exactitude Medicine
4.3 Tumor Cells Measurements
5 Use Several Methodologies of AI, ML in Clinical System
6 Big Data Analytics Tools for Healthcare System
6.1 Hadoop-Based Tools for Health Industry
6.2 Architecture for Healthcare System
7 Conclusion
References
Swarm Intelligence and Evolutionary Algorithms in Processing Healthcare Data
1 Introduction
2 Concept of Swarm Intelligence and Evolutionary Algorithms
3 The Applications of Swarm Intelligence in Healthcare System
4 Applications of Evolutionary Algorithm in Healthcare Industry
5 Swarm Intelligence and Evolutionary Algorithms in Healthcare Data Processing
6 The Challenges of Bio-Inspired Algorithms in Healthcare Sector
7 Conclusion
References
AI in Acquisition, Analysis and Processing of Medical Signal Data Collected By Wearable Devices
1 Introduction
2 Respiratory Signals
3 Heart Rate Veracity Validation
4 Sleep Quality and Sleep Disorder Screening Report
5 HRV Analysis Report
6 Predicting Alzheimer’s Disease
7 Wearable Sweat Sensor
8 Wearable Peritoneal Dialysis Device
9 Photo Plethysmogram Signal
10 Smart Insole for Gait Analysis
11 Wearable Blood Sensors
12 Wearable ECG Monitors
13 Electronic Wearable Footwear
14 Textile-Based Wearables
15 Future Scope
16 Conclusion
References
Wearable Sensor Signals: An Overview of the AI Models Most Commonly Applied to Time Series Data Analysis
1 Introduction
2 Machine Learning Techniques
2.1 Decision Tree
2.2 Rule-Based Learning
2.3 Bayesian Classification
2.4 Instance-Based Learning
2.5 Support Vector Machine
2.6 Ensemble Techniques
3 Deep Learning Techniques
3.1 Recurrent Neural Network
3.2 Convolutional Neural Networks
4 Tools
5 Conclusions
References
An Articulated Learning Method Based on Optimization Approach for Gallbladder Segmentation from MRCP Images and an Effective IoT Based Recommendation Framework
1 Introduction
2 Review of Research Literature
3 Importance of Interpretability and Explainability
4 Taxonomy of Interpretability/explainability
5 Proposed Methodology
6 Optimization of DNN Using TSA
7 Simulation Results
8 Conclusion
References
Interval Type-2 Fuzzy Kalman Filtering and Forecasting of the Dynamic Spread Behavior of Novel Coronavirus 2019
1 Introduction
1.1 Related Works
1.2 Motivation and Contributions of the Proposed Methodology
2 Interval Type-2 Fuzzy Kalman Filter
2.1 Pre-processing by Singular Spectral Analysis
2.2 Parametric Estimation of Interval Type-2 Fuzzy Kalman Filter
2.3 Computational Load Analysis of Interval Type-2 Fuzzy Kalman Filter Algorithm
3 Experimental Results
3.1 Experimental Environment and Dataset
3.2 Interval Type-2 Fuzzy Kalman Filtering and Forecasting Analysis of the COVID-19 Dynamic Propagation in Brazil
3.3 Comparative Analysis and Discussions
4 Conclusion
4.1 Further Works Proposal
References
Artificial Intelligence in Medical Image Processing for Airway Diseases
1 Introduction
1.1 Components of Airway Disease
1.2 AI for Medical Imaging
1.3 Organization of Chapter
2 Motivation
3 Background Study
3.1 Medical Imaging
3.2 Types of Airway Diseases and Their Diagnosis
3.3 Epidemiology of Airway Illness
3.4 Development of Artificial Intelligence to Process the Medical Images
3.5 Framework of Artificial Intelligence to Interpret Airway Diseases Through Medical Images
4 Related Work
5 Comparison
6 Discussion
7 Conclusion and Future Direction
References
Artificial Intelligence Techniques in Health Informatics for Oral Cancer Detection
1 Introduction
1.1 About the Study
1.2 Organization of Chapters
2 Motivations
3 Backgrounds
3.1 Framework for Oral Cancer Detection
3.2 Segmentation
3.3 Feature Extraction
3.4 Classifier
4 Oral Cancer Dataset
4.1 How Oral Cancer Develops
5 Reported WORKS
6 Conclusion and Future Directions
References
Smart Healthcare Systems for Rheumatoid Arthritis: The State of the Art
1 Introduction
2 Work Done in the Field of Rheumatoid Arthritis
3 Performance Analysis
4 Conclusion
References
Quantitative Assessment of Fetal Wellbeing Through CTG Recordings
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset Description
3.2 Pre-processing
3.3 Classifications
4 Implementation and Result Analysis
4.1 Dataset Description of Dataset-1
5 Dataset Description of Dataset-2
6 Conclusion and Feature Work
References
Wearable Devices: Evolution and Usage in Remote Patient Monitoring System
1 Introduction and Evolution of Wearables
2 Wearable Devices in Healthcare
2.1 Cardiovascular Monitoring System
2.2 Activity Monitoring System
2.3 Blood Oxygen Saturation Monitoring System
2.4 GSR Monitoring System
2.5 Body Temperature Monitoring System
2.6 Blood Glucose Monitoring System
2.7 Biometrics System
3 How and Why Wearables Applied in Remote Patient Monitoring
4 Intelligent Sensors for Remote Patient Monitoring
5 Research Challenge and Future Scope
6 Conclusion
References
In Hospital and in Home Remote Patient Monitoring
1 Introduction
2 Remote Patient Monitoring (RPM)
2.1 Wearable Heart Beat Sensor
2.2 Wearable Temperature Sensor
2.3 Wearable Blood Pressure Sensor
2.4 Glucometers
2.5 Wearable Pulse Oximeter
2.6 Bluetooth Interface Unit
2.7 Android Mobile with Internet
2.8 Server
2.9 Robotic Process Automation (RPA)
2.10 Android Mobile Phone
3 Classification of Patients
3.1 Identification of Disease and Monitoring Patients
3.2 Implementation
4 Doctors Appointment to Patients
5 Applications
6 Challenges in Remote Patient Monitoring
7 Conclusion
References
IoT-Based In-Hospital-In-Home Heart Disease Remote Monitoring System with Machine Learning Features for Decision Making
1 Introduction
2 Related Works
2.1 Internet of Things (IoT) in Healthcare
2.2 Healthcare Remote Monitoring System
2.3 Data Analytics and Machine Learning in Healthcare
3 Methodology
3.1 Modelling Phase
3.2 Assessment Phase
3.3 Design Phase
3.4 Prototype Phase
4 Data Analysis, Results, and User Interface
4.1 Data Analysis and Results
4.2 User Interface
5 Discussion and Conclusion
References
IoT and Cloud Based Remote Healthcare for Elderly
1 Introduction
1.1 Hardware Architecture
1.2 Software Architecture
1.3 Cloud Computing
1.4 Fog Computing
2 Background Study
2.1 Elderly Population Distribution
2.2 Sensors Used for Elderly Health Monitoring
2.3 Internet of Things
2.4 Cloud Based Remote Healthcare for Elderly
3 Discussed Methodology
4 Comparison Analysis
4.1 Fog Computing
5 Result Discussion
5.1 Fog IOT System
6 Conclusion
References
Indoor Positioning System Assisted Big Data Analytics in Smart Healthcare
1 Introduction to Smart Healthcare
2 Introduction to Big Data
3 Big Data Analytics
4 Importance of Big Data Analytics
5 Industry Applications of Big Data
6 Healthcare and Big Data
7 Big Data Sources and Stakeholders
8 Disjoint Areas of Big Data Analytics for Healthcare
9 Indoor Positioning System
10 Features of IPS
11 Working of Indoor Positioning System
12 Indoor Positioning System in Healthcare
13 Challenges in Smart Healthcare Transformation
14 Fusion of Hierarchical Data in Smart Healthcare
15 Infrastructure
16 Software Used: Data Infusion
17 Types of Data Fusion
18 Architecture of the Data Fusion Software
19 Complex Event Processing
20 Methods of Implementation
21 Conclusion
References
Explainable Artificial Intelligence in Genomic Sequence for Healthcare Systems Prediction
1 Introduction
2 Explainable Artificial Intelligence in Healthcare System
3 Reason for Explainable Artificial Intelligence in Healthcare System
4 Explainable Artificial Intelligence in Genomic Sequence
5 The Challenges of Explainable Artificial Intelligence in Genomic Sequence
6 Conclusion
References
Privacy and Security Issues in IoT Cloud Convergence of Smart Health Care
1 Introduction
2 Motivation and Objective
2.1 Related Work
3 Basic Features of a Smart Healthcare System
4 Security and Privacy Challenges in IoT-Cloud Based Smart Health Care Prospective
4.1 Resource Management
4.2 System Components
4.3 Security and Privacy
5 Privacy and Security Solutions in Smart Health Care System
5.1 Service Oriented Architecture for Smart Health Care System Using Security and Privacy Model
6 Conclusion
References
Dual Secured Reversible Medical Image Watermarking for Internet of Medical Things
1 Introduction
2 Related Work
3 Proposed Work
3.1 Pseudo Random Key Generation
3.2 EPR Encryption and EPR Extraction
3.3 BR Embedding and Extraction
3.4 NBR Embedding and Extraction
4 Experimental Results and Discussion
4.1 Visual Quality (Imperceptibility)
4.2 Robustness
4.3 Confidentiality Test
4.4 Computational Complexity
5 Conclusion
References
A Smart and Intelligent Security System for Healthcare Facilities with AWS and Raspberry Pi Integration
1 Introduction
2 Objective
3 Vital Highlights
4 Proposed Methodology
5 Result Analysis
6 Conclusion and Future Scope
References
