Intelligent Pervasive Computing Systems for Smarter Healthcare

A guide to intelligent decision and pervasive computing paradigms for healthcare analytics systems with a focus on the use of bio-sensors

Intelligent Pervasive Computing Systems for Smarter Healthcare describes the innovations in healthcare made possible by computing through bio-sensors. The pervasive computing paradigm offers tremendous advantages in diversified areas of healthcare research and technology. The authors--noted experts in the field--provide the state-of-the-art intelligence paradigm that enables optimization of medical assessment for a healthy, authentic, safer, and more productive environment.

Today's computers are integrated through bio-sensors and generate a huge amount of information that can enhance our ability to process enormous bio-informatics data that can be transformed into meaningful medical knowledge and help with diagnosis, monitoring and tracking health issues, clinical decision making, early detection of infectious disease prevention, and rapid analysis of health hazards. The text examines a wealth of topics such as the design and development of pervasive healthcare technologies, data modeling and information management, wearable biosensors and their systems, and more. This important resource:

• Explores the recent trends and developments in computing through bio-sensors and its technological applications

• Contains a review of biosensors and sensor systems and networks for mobile health monitoring

• Offers an opportunity for readers to examine the concepts and future outlook of intelligence on healthcare systems incorporating biosensor applications

• Includes information on privacy and security issues on wireless body area network for remote healthcare monitoring

Written for scientists and application developers and professionals in related fields, Intelligent Pervasive Computing Systems for Smarter Healthcare is a guide to the most recent developments in intelligent computer systems that are applicable to the healthcare industry.

Autorentext

ARUN KUMAR SANGAIAH, PHD, is currently associated with the School of Computer Science and Engineering, VIT University, Vellore, India. S. P. SHANTHARAJAH, PHD, is currently associated with the School of Information Technology and Engineering, VIT University, Vellore, India. PADMA THEAGARAJAN, PHD, is currently associated with the Department of Computer Applications, Sona College of Technology, Salem, India.

Inhalt
List of Contributors xvii

1 Intelligent Sensing and Ubiquitous Systems (ISUS) for Smarter and Safer Home Healthcare **1
Rui Silva Moreira, José Torres, Pedro Sobral, and Christophe Soares

1.1 Introduction to Ubicomp for Home Healthcare 1

1.2 Processing and Sensing Issues 3

1.2.1 Remote Patient Monitoring in Home Environments 4

1.2.1.1 Hardware Device 5

1.2.1.2 Sensed Data Processing and Analysis 6

1.2.2 Indoor Location Using Bluetooth Low Energy Beacons 8

1.2.2.1 Bluetooth Low Energy 9

1.2.2.2 Distance Estimation 9

1.3 Integration and Management Issues 14

1.3.1 Cloud-Based Integration of Personal Healthcare Systems 15

1.3.2 SNMP-Based Integration and Interference Free Approach to Personal Healthcare 17

1.4 Communication and Networking Issues 19

1.4.1 Wireless Sensor Network for Home Healthcare 21

1.4.1.1 Home Healthcare System Architecture 21

1.4.1.2 Wireless Sensor Network Evaluation 25

1.5 Intelligence and Reasoning Issues 26

1.5.1 Intelligent Monitoring and Automation in Home Healthcare 26

1.5.2 Personal Activity Detection During Daily Living 30

1.6 Conclusion 32

Bibliography 33

2 PeMo-EC: An Intelligent, Pervasive and Mobile Platform for ECG Signal Acquisition, Processing, and Pre-Diagnostic Extraction **37
Angelo Brayner, José Maria Monteiro, and João Paulo Madeiro

2.1 Electrical System of the Heart 37

2.2 The Electrocardiogram Signal: A Gold Standard for Monitoring People Suffering from Heart Diseases 38

2.3 Pervasive and Mobile Computing: Basic Concepts 40

2.4 Ubiquitous Computing and Healthcare Applications: State of the Art 42

2.5 PeMo-EC: Description of the Proposed Framework 44

2.5.1 Acquisition Module: Biosensors and ECG Data Conditioning 44

2.5.2 Patient's Smartphone Application: ECG Signal Processing Module 49

2.5.3 Physician's Smartphone Application: Query/Alarm Module 54

2.5.4 The Collaborative Database: Data Integration Module 55

2.5.4.1 Motivation 55

2.5.4.2 The Design of the Collaborative Database 57

2.5.4.3 Data Mining and Pattern Recognition 59

2.6 Conclusions 61

Acknowledgements 61

Bibliography 62

3 The Impact of Implantable Sensors in Biomedical Technology on the Future of Healthcare Systems **67
Ashraf Darwish, Gehad Ismail Sayed, and Aboul Ella Hassanien

3.1 Introduction 67

3.2 Related Work 71

3.3 Motivation and Contribution 74

3.4 Fundamentals of IBANs for Healthcare Monitoring 75

3.4.1 ISs in Biomedical Systems 75

3.4.2 Applications of ISs in Biomedical Systems 78

3.4.2.1 Brain Stimulator 78

3.4.2.2 Heart Failure Monitoring 78

3.4.2.3 Blood Glucose Level 80

3.4.3 Security in Implantable Biomedical Systems 80

3.5 Challenges and Future Trends 82

3.6 Conclusion and Recommendation 85

Bibliography 86

4 Social Network's Security Related to Healthcare **91
Fatna Elmendili, Habiba Chaoui, and Younés El Bouzekri El Idrissi

4.1 The Use of Social Networks in Healthcare 91

4.2 The Social Media Respond to a Primary Need of Security 92

4.3 The Type of Medical Data 95

4.3.1 Security of Medical Data 96

4.4 Problematic 97

4.5 Presentation of the Honeypots 98

4.5.1 Principle of Honeypots 98

4.6 Proposal System for Detecting Malicious Profiles on the Health Sector 99

4.6.1 Proposed Solution 100

4.6.1.1 Deployment of Social Honeypots 100

4.6.1.2 Data Collection 103

4.6.1.3 Classification of Users 104

4.7 Results and Discussion 108

4.8 Conclusion 111

Bibliography 111 5 Multi-Sensor Fusion for Context-Aware Applications **115<br /&g...