Pervasive Healthcare: A Compendium of Critical Factors for Success (EAI/Springer Innovations in Communication and Computing)

"This book provides in depth knowledge about critical factors involved in the success of pervasive healthcare. The book first presents critical components and importance of pervasive healthcare. The authors then give insight into the pervasive healthcare information systems and key consideration related to remote patient monitoring and safety. The book provides in-depth discussion about the security issues and protocols for pervasive healthcare. This book explores concepts and techniques behind the successive pervasive healthcare systems by providing in-depth knowledge about patient empowerment, remote patient monitoring, network establishment and protocols for effective pervasive healthcare. The book also provides case studies in the field. It is an ideal resource for researchers, students and healthcare organizations to get insight about the state of the art in pervasive healthcare systems. Provides current research, developments, and applications in pervasive healthcare; Includes technologies such as machine learning, cryptography, fog computing, and big data in the advancement of e-healthcare; Pertinent for researchers, students, practitioners and healthcare decision makers."--Back cover Preface Emerging Need Purpose Audience Emphasis What You Will Learn Book Organization Acknowledgments Contents Contributors Chapter 1: Pervasive Healthcare Computing and its Contribution to Hospitals, Chronic and Preventive Care 1.1 Introduction 1.2 Pervasive Computing for Hospital Care 1.2.1 Context-Aware Services and Awareness 1.2.2 Hospital Information System Information System for Patient Care 1.3 Major Goals and Purposes of Patient Care Information Systems 1.3.1 The Associations of the System Are Shown in the Graphic Representation Underneath: Healthcare Information Management System Clinical Information System Clinical Support Systems 1.3.2 Electronic Medical Record (EMR) 1.3.3 Computerized Physician Order Entry 1.3.4 Remote Monitoring 1.4 Overall Impact of Pervasive Computing on Hospital 1.5 Chronic Care Supervision and Supported Cognition 1.5.1 Pervasive Monitoring for Self-Management 1.5.2 Computerized Algorithm-Driven Care 1.5.3 Remote Patient Monitoring 1.5.4 Cost-Effective Treatment 1.5.5 Improved Patient Experience 1.6 Pervasive Computing for Preventive Care 1.6.1 Automated and Selective Capture and Access of Health Information 1.6.2 Patient Electronic Portals 1.6.3 Persuasive Technologies for Self-Monitoring 1.6.4 Direct Interaction vs. Mediation 1.6.5 Persuasion by Social Motivators 1.7 Conclusions References Chapter 2: The Imperative Role of Pervasive Data in Healthcare 2.1 A Brief History of Pervasive Computing 2.2 Main Features of Pervasive Computing 2.2.1 Context Awareness 2.2.2 Adaptation 2.2.3 Scalability 2.2.4 Heterogeneity 2.3 Pervasive in Healthcare 2.4 Pervasive Applications in Healthcare 2.4.1 Security Features for Patients’ Data 2.4.2 Lifecycle of Pervasive Healthcare Data 2.4.3 Classification of Pervasive Healthcare Data 2.4.4 Dynamics of Pervasive Healthcare Data 2.4.5 Dynamics Labelling Process for Healthcare Data Designing 2.4.6 Pervasive Healthcare Data Labelling Techniques References Chapter 3: Pervasive Healthcare Computing: Applications, Challenges and Solutions 3.1 Introduction 3.2 Pervasive Healthcare Applications 3.2.1 Modern Computer Technologies in Hospitals 3.2.2 Hospital Information System and Electronic Patient Record Management 3.2.3 Medical Imaging and Communication Systems (MICS) 3.2.4 Clinical Laboratory Computing 3.3 Present-Day Uses and Problems in Pervasive Healthcare Computing 3.3.1 In Relation to Information Systems, the Subsequent Problems Need to Be Resolved as Follows 3.3.2 Technological Issues 3.3.3 Management-Level Issues 3.4 Challenges in Pervasive Healthcare Computing 3.4.1 Mobility Amongst Heterogeneous Electronic Devices 3.4.2 Rapid Context Switching for Patient Caring 3.4.3 A Precise Summary of Major Challenges and Related Technologies 3.5 Scientific Solution of Pervasive Healthcare Challenges 3.5.1 A Heterogeneous Wireless Architecture Intended for Pervasive Healthcare Applications 3.5.2 Prioritized Operation Designed for Healthcare Services 3.5.3 Providing Location-Level Management Support Global Positioning System and A-GPS Support Cellular as Well as Wireless Network Support 3.6 Conclusions References Chapter 4: Pervasive Healthcare Computing as a Scientific Care Discipline for Patients 4.1 Introduction 4.2 Pervasive Healthcare Computing Systems 4.3 Applications of Pervasive Healthcare System 4.3.1 Modern Pathological Clinical Methods 4.3.2 Smart Blood Pressure Monitoring System 4.3.3 The Future of Pervasive Healthcare 4.3.4 Adoption and Acceptance 4.4 Open Data Research in Pervasive Healthcare System 4.5 Conclusions and Future References Chapter 5: Improving the Healthcare and Public Health Critical Infrastructure by Soft Computing: An Overview 5.1 Introduction 5.2 Information and Telecommunication Technology in Healthcare 5.3 Application of Artificial Intelligence in Healthcare Systems 5.4 Application of Machine Learning Systems in Healthcare 5.4.1 Surgical Robots 5.5 Application of Artificial Intelligence System in a Diagnostic Centre 5.6 Buoy Health 5.7 Enlitic 5.7.1 Decision Tree 5.7.2 Making a Decision Tree 5.8 Decision Support System 5.9 Disadvantages of Decision Support Systems 5.10 Uninformed Assumptions 5.11 System Design Failure 5.12 Difficulty in Collecting all the Required Data 5.13 Lack of Technology Knowledge in Users 5.14 Conclusion References Chapter 6: An Approach Towards Privacy and Security in Pervasive Healthcare System 6.1 Introduction 6.2 Privacy Standards in Healthcare Systems 6.3 Healthcare System Protection 6.4 Security Models in e-Healthcare Systems 6.5 Sharing and Access-Level Security Models 6.6 Intelligence-Based Access Control Security Model 6.7 Working Principle of the IBAC Model 6.8 Conclusion and Future Work References Chapter 7: Body Sensor Networks for Healthcare: Advancements and Solutions 7.1 Introduction 7.2 Applications, Issues and Challenges 7.3 Architecture of BSN 7.4 Body Sensor Networks 7.4.1 Wearable BSNs 7.4.2 Nonwearable BSN 7.5 Advancements in Infrastructure of BSNs 7.5.1 Sensors for BSN 7.5.2 Wireless BAN 7.6 Security in BSN 7.7 Conclusion References Chapter 8: Artificial Intelligence Algorithms for Healthcare and Neurorehabilitation Engineering 8.1 Introduction 8.2 Artificial Intelligence and Algorithms 8.2.1 Data Classification Algorithms 8.2.2 Regression Algorithms 8.2.3 Clustering Algorithms 8.3 Rehabilitation and Devices 8.3.1 Walkers and Wheelchairs 8.3.2 Electrical Stimulators 8.3.3 Brain-Computer Interfaces 8.3.4 Orthoses and Exoskeleton 8.4 Conclusion References Chapter 9: Enabling Speech Emotional Intelligence as a Service in Homecare Platforms 9.1 Introduction 9.2 Background and Related Work 9.3 Proposed Methodology 9.3.1 Audio Analysis Conventional Classification Schemes Convolutional Neural Network-Based Recognition 9.3.2 SER Integration in Homecare Platform Store in Personal Health Record Near-Real-Time Operation 9.4 Experimental Results: The System in Practice 9.4.1 Training Dataset Description 9.4.2 Classification Experiments Conventional Classification Schemes Convolutional Neural Networks 9.5 Conclusions and Future Work References Chapter 10: A Study of the Impact of Covid-19 Using a Sieve Approach 10.1 Introduction 10.2 Machine Learning 10.3 COVID-19 and Medical Science 10.4 Discussion with Sieve Diagram 10.5 Observed Significance References Chapter 11: A Comparative Study on Data Mining Approach Using Machine Learning Techniques: Prediction Perspective 11.1 Introduction 11.2 Background 11.3 Breast Cancer 11.4 Data Mining Approaches 11.4.1 Classification Learning Steps Classification Steps 11.5 Basic Algorithms for Cancer Detection 11.5.1 Data Interpretations 11.5.2 Dataset 11.6 Experimental Results 11.7 Discussion and Conclusion References Chapter 12: Indoor Air-Quality Monitoring Systems: A Comprehensive Review of Different IAQM Systems 12.1 Introduction 12.2 Air Pollutant Types 12.3 Air Pollution Monitoring System Categories 12.4 Reasons for Developing IAQM System 12.5 Requirements of IAQM System 12.6 Fundamentals of Data Mining Methods for Environmental Pollution Controls 12.7 IAQM System Architecture 12.7.1 WSN-Based Architecture 12.7.2 IOT-Based Architecture 12.8 IAQM’s Domain 12.9 Conclusion References Chapter 13: Computer-Based Techniques for Detecting the Neurological Disorders 13.1 Introduction 13.1.1 Significance of EEG in the Detection of Neurological Disorders 13.1.2 Significance of the Computer-Assisted Algorithm in Detection of Neurological Disorders 13.2 Neurological Disorders 13.3 Prevalence of Neurological Disorders in India 13.4 Seizures as Biomarkers of Neurological Disorders 13.5 Introduction to Coupling 13.6 Significance of Detection of Coupling in Biomedical System 13.7 Computer-Based Techniques for Detection of Neurological Disorders by Using EEG Signals 13.8 Recurrence-Based and Machine Learning-Assisted Computer-Based Method for Detection of Neurological Disorder 13.8.1 Recurrences 13.9 The Novel Computer-Assisted Algorithm for Detection of Neurological Disorders 13.9.1 Features 13.9.2 Machine Learning Models that Can be Used with Computer-Assisted Algorithms Naive Bayes Classifier Nearest Neighbor Logistic Regression (Predictive Learning Model) Decision Trees Random Forest Neural Network 13.10 Various Other Algorithms Used for the Detection of Neurological Disorders 13.11 Results and Comparisons of the Novel Algorithm with Relevant Works 13.12 Future Scope References Chapter 14: A Prediction of Disease Using Machine Learning Approach 14.1 Introduction 14.2 Background 14.3 Diabetes 14.4 Methodology 14.4.1 Model Development 14.4.2 Model Implication 14.5 Conclusion References Chapter 15: Security in Digital Healthcare System 15.1 Introduction 15.1.1 Security Attributes 15.1.2 Confidentiality 15.1.3 Reliability 15.1.4 Availability 15.1.5 Privacy and Security Issues in Healthcare 15.2 Threats to Privacy of Information 15.2.1 Web-Enabled Healthcare Information Security 15.2.2 Information Security for Authorized Data Access (Disclosure) 15.2.3 Information Security and Data Interoperability 15.2.4 Attacks and Types Mistake Improper Use of Access Privileges Unauthorized Use for Profit Unauthorized Physical Intrusion Technical Break-in 15.2.5 Some Existing Solutions 15.2.6 Role-Based Access Security and Access Control 15.2.7 Authentication Mechanism 15.2.8 Encryption 15.2.9 Digital Watermarking [3] 15.3 Literature Review 15.3.1 Authentication Code Using Cryptographic Hash Function [5] 15.3.2 Digital Signature Method for Authentication [6] 15.3.3 Authentication Using Content [1, 2] 15.3.4 Embedding Using Mean [3, 7] 15.3.5 ANN-Based Approach [8, 9] 15.3.6 Genetic Algorithm-Based Approach [10–12] 15.3.7 Cosine Transform-Based Approach [3, 7, 10] 15.3.8 Chaos-Based Approach [13] 15.3.9 SVD-Based Approach [11] 15.3.10 Steganography-Based Approach 15.3.11 Visual Cryptography-Based Approach [6] 15.4 Some Important Algorithms 15.5 Conclusion and Future Scope References Chapter 16: Classification Algorithms for Predicting Diabetes Mellitus: A Comparative Analysis 16.1 Introduction 16.2 Literature Survey 16.3 Materials and Methods 16.3.1 Dataset 16.3.2 Feature Selection Techniques Linear Discriminant Analysis Principal Component Analysis Random Forest Extra Trees Variance Threshold 16.3.3 Classification Algorithms Linear Discriminant Analysis Quadratic Discriminant Analysis Gaussian Naive Bayes Gaussian Process Classifier Support Vector Machine Classifier MLP Classifier AdaBoost Classifier Logistic Regression Decision Tree Random Forest (RF) Bagging Gradient Boosting (GB) K-Nearest Neighbor SGD Classifier Bernoulli Naïve Bayes 16.4 Methodology Used 16.5 Results and Discussion 16.6 Discussions 16.6.1 Limitations of the Study 16.7 Conclusion and Future Work References Chapter 17: Blockchain Technology for Healthcare Record Management 17.1 Introduction 17.1.1 Major Challenges in the Healthcare Industry 17.1.2 Solution via ICT for Healthcare Challenges 17.2 Pervasive Computing and Healthcare 17.2.1 Pervasive Healthcare 17.2.2 Open Issues and Challenges in Pervasive Computing Implementation 17.3 Electronic Medical Records (EMR) and Electronic Health Records (EHR) 17.3.1 Benefits of Using EMR 17.3.2 EHR and EMR Integration with Blockchain 17.3.3 Components of a Blockchain Block Consensus Algorithm Cryptography 17.4 Blockchain Networks 17.4.1 Peer-to-Peer Network 17.4.2 Public Networks (Permissionless) 17.4.3 Private Networks (Permissioned) 17.5 Blockchain Technology Challenges 17.5.1 Scalability and Storage Capacity 17.5.2 Lack of Social Skills 17.5.3 Lack of Globally Acknowledged Standards 17.6 Managing Healthcare by Implementing Blockchain 17.6.1 Advantages of Managing Healthcare Using Blockchain 17.7 Blockchain Use Cases in Healthcare During the COVID-19 Pandemic 17.8 Conclusion References Chapter 18: An Experimental Approach for Prediction of Breast Cancer Diseases Using Clustering Concepts 18.1 Introduction 18.2 Related Work 18.3 Breast Cancer 18.4 Data Interpretation Evauation 18.5 Conclusion and Discussion References Chapter 19: Post-COVID-19 View of Indian Economy with Emphasis on Service Sector: A Regression Implementation 19.1 Introduction 19.2 Subsector Comprising Travel and Tourism 19.3 Subsector Comprising Finance, Real Estate, and Business Services 19.4 Subsector Comprising Trade, Hotels, Transport and Communication, and Services Related to Broadcasting 19.4.1 Data Preprocessing 19.4.2 Econometric Model 19.4.3 Multivariate Data Analysis Travel and Tourism Finance, Real Estate, and Business Services Trade, Hotels, Transport and Communication, and Services Related to Broadcasting 19.4.4 Significance of the Proposed Methodology 19.5 Literature Review 19.6 Methodology 19.7 Subsector 1: Travel and Tourism 19.7.1 Subsector 2: Finance, Real Estate, and Business Services 19.7.2 Subsector 3: Trade, Hotels, Communication, and Broadcasting Services 19.7.3 Linear Regression and Logistic Regression 19.8 Results and Discussions 19.8.1 Travel and Tourism 19.8.2 Finance, Real Estate, and Business Services 19.9 Trade, Hotels, Transport, and Communication and Services Related to Broadcasting 19.9.1 Limitations of the Study 19.10 Implications of the Study 19.11 Recommended Solutions and Future Work References Chapter 20: Diabetes Management System in Mauritius: Current Perspectives and Potentials of Pervasive Healthcare Technologies 20.1 Introduction 20.2 Diabetes Management System in Mauritius 20.3 Critical Appraisal of the Diabetes Management System of Mauritius 20.4 Method 20.4.1 Study Design and Subjects 20.4.2 Instrument 20.4.3 Ethical Considerations 20.4.4 Statistical Methods 20.5 Results 20.5.1 Sociodemographic Factors and Health Characteristics 20.5.2 Treatment Satisfaction and Patient Characteristics 20.5.3 Impacts of Diabetes on Different Life Domains 20.5.4 Patient Attitudes Toward Using Mobile Phone Technology to Monitor Diabetes 20.6 Discussion 20.7 Future Research Directions 20.7.1 Sensor-Level Challenges Data Acquisition and Sensing Data Transmission Data Compression Data Acquisition and Efficiency 20.7.2 Communication-Level Challenges Security and Privacy Reliability of Data Transmission Dependability 20.7.3 Human-Centric-Level Challenges Data Representation Personalized Feedback 20.8 Conclusions References Chapter 21: Aiding IoT and Cloud to Control COVID-19: A Systematic Approach 21.1 Introduction 21.2 Literature Survey 21.3 Proposed Work 21.3.1 Data Collection Phase 21.3.2 Sharing the Data Among Various Personnel 21.4 Analysis of the Work 21.4.1 Reliability 21.4.2 Availability 21.4.3 Scalability of Information 21.5 Conclusion References Index