Body Sensor Networks

Preface
About the Editor
Contents
Contributors
Chapter 1: Introduction
1.1 Wireless Sensor Networks
1.2 BSN for Healthcare and Wellbeing
1.2.1 Monitoring Patients with Chronic Disease
1.2.2 Monitoring Hospital Patients
1.2.3 Monitoring Elderly Patients
1.2.4 Life Style and Wellbeing
1.3 The Need for Pervasive Health Monitoring
1.4 Technical Challenges Facing BSN
1.4.1 Improved Sensor Design
1.4.2 MEMS and BioMEMS
1.4.3 Biocompatibility, Integratability and Resorbability
1.4.4 Energy Supply and Demand
1.4.5 Wireless Data-Paths, Antenna Design, System Security and Reliability
1.4.6 Context Awareness
1.4.7 Integrated Therapeutic Systems
1.5 From Wellbeing to Personalised Healthcare
1.6 Finding the Ideal Architecture for BSN
1.7 The Future: Going from ``Micro´´ to ``Nano´´
1.8 The Scope of the Book
References
Chapter 2: Biosensors and Sensor Systems
2.1 Introduction
2.2 Bioanalysis
2.2.1 Some Jargon
2.2.2 Bioanalysis - What Does Chemical Concentration Mean in Biology?
2.3 Molecular Recognition
2.4 Electrochemical Sensors
2.4.1 Potentiometry
2.4.1.1 Underlying Principles of Operation
2.4.1.2 Calibration
2.4.1.3 Selectivity
2.4.1.4 Limit of Detection
2.4.1.5 Other Potentiometric Devices
2.4.1.6 Recent Developments in Ion Selective Electrodes
2.4.2 Amperometry and Voltammetry
2.4.2.1 Amperometric Methods
2.4.2.2 Voltammetry and the Use of Non-steady Potential Programmes
2.4.3 Instrumentation
2.4.4 Signal Processing and Data Analysis
2.5 Multiple Sensors and Microsensor Arrays
2.5.1 Microelectrode Arrays for Primary Mammalian Cell Culture
2.5.2 Assessing Biocompatibility
2.6 New Materials
2.7 Future Perspectives and Research Challenges
References
Chapter 3: Biosensor Design with Molecular Engineering and Nanotechnology
3.1 Introduction
3.2 Biomolecular Engineering for Biosensors
3.2.1 Engineering Proteins by Rational Design
3.2.2 Engineering Proteins by Evolutionary Design
3.2.3 Nucleic Acid Aptamers
3.3 Biosensor Applications
3.3.1 The Signal Transduction Module
3.3.2 The Molecular Recognition Module
3.3.3 Immobilisation Module
3.4 Nanotechnology
3.4.1 Miniaturisation and Scaling Laws: Nanoscale Devices and Performance Enhancements of Biosensors
3.4.2 Graphene
3.4.3 Nanoelectrochemical Sensors
3.4.4 Graphene Electrochemical Sensors
3.5 Biocompatibility and Implantable Biosensors
3.6 Conclusions
References
Chapter 4: Wireless Communication
4.1 Introduction
4.2 Inductive Coupling
4.3 RF Communication in the Body
4.4 Implanted Transceiver
4.5 Antenna Design
4.6 Antenna Testing
4.6.1 Antenna Impedance and Radiation Resistance Measurement
4.6.2 Quarter Wave Line Impedance Measurement
4.7 Matching Network
4.7.1 Transmitter Tuning
4.7.2 The L Network
4.7.3 The pi Network
4.7.4 The T and pi - L Networks
4.7.5 Parasitic Effects
4.7.6 Network Choice
4.7.7 Radio Frequency Losses in Components and Layout Issues
4.7.8 Receiver Tuning
4.7.9 Base Station Antennas
4.8 Propagation
4.9 Materials
4.10 Environment
4.11 External Transceiver (Base Station)
4.12 Power Considerations
4.13 Miniaturised Construction
4.13.1 Battery Challenges
4.14 Defibrillation Pulse and X-rays
4.15 Link Budget
4.16 Electro-stimulation: A Non-MICS Example
4.17 Conclusions
References
Chapter 5: Network Topologies, Communication Protocols, and Standards
5.1 Network Topologies
5.2 Body Sensor Network Application Scenarios
5.2.1 Stand-Alone Body Sensor Networks
5.2.2 Pervasive Sensor Networks
5.2.3 Global Healthcare Connectivity
5.3 The Standardisation of Wireless Personal and Body Area Networking
5.3.1 The Wireless Regulatory Environment
5.3.2 Wireless Communication Standards
5.3.3 IEEE 802.15.1: Medium-Rate Wireless Personal Area Networks
5.3.3.1 Bluetooth Low Energy
5.3.4 IEEE P802.15.3: High-Rate Wireless Personal Area Networks
5.3.5 IEEE 802.15.4: Low-Rate Wireless Personal Area Networks
5.3.5.1 The ZigBee Specification
5.3.5.2 The ZigBee Healthcare Profile
5.3.6 IEEE 802.15.6: Wireless Body Area Networks
5.3.7 Comparison of Technologies
5.4 Interference and Coexistence
5.5 Healthcare System Integration
5.5.1 ISO/IEEE 11073 Personal Health Device Communication
5.5.2 Continua Health Alliance
5.6 Conclusions
References
Chapter 6: Energy Harvesting and Power Delivery
6.1 Introduction
6.1.1 Sensor Node Power Requirements
6.1.2 Batteries and Fuel Cells for Sensor Nodes
6.1.3 Ambient Energy Sources
6.2 Inertial Energy Harvesters: Principles and Performance Limits
6.2.1 Energy Extraction Mechanisms for Inertial Generators
6.2.2 Performance Limits
6.3 Inertial Energy Harvesters: Practical Examples
6.3.1 Electrostatic Harvesters
6.3.2 Electromagnetic Harvesters
6.3.3 Piezoelectric Harvesters
6.4 Power Electronics for Energy Harvesters
6.4.1 Electrostatic Harvester Interfaces
6.4.2 Electromagnetic Harvester Interfaces
6.4.3 Piezoelectric Energy Harvester Interfaces
6.5 Wireless Power Delivery
6.5.1 Near Field Inductive Power Transfer
6.5.2 Ultrasonic Power Delivery
6.5.3 Radiative Power Transfer
6.6 Discussion and Conclusions
6.6.1 What Is Achievable in Body-Sensor Energy Harvesting?
6.6.2 Future Prospects and Trends
References
Chapter 7: Towards Ultra-low Power Bio-inspired Processing
7.1 Introduction
7.2 Bio-inspired Signal Processing
7.3 Analogue Versus Digital Signal Processing
7.3.1 Quantised Data/Time vs. Continuous Data/Time
7.3.2 Analogue/Digital Data Representation
7.3.3 Linear Operations
7.3.4 Non-linear Operations
7.3.5 Hybrid System Organisation
7.4 CMOS-Based Biosensors
7.4.1 Ion-Sensitive Field-Effect Transistor (ISFET)
7.4.2 ISFET-Based Biosensors
7.4.2.1 ChemFET
7.4.2.2 GasFET
7.4.2.3 EnFET
7.4.3 Towards Biochemically-Inspired Processing with ISFETs
7.4.3.1 Weak Inversion Operation
7.4.3.2 Translinear Design Methodology
7.4.4 An ISFET-Based ASIC for Rapid Point-of-Care Gene Detection
7.5 Future Outlook
References
Chapter 8: Multi-sensor Fusion
8.1 Introduction
8.1.1 Information Interaction
8.1.2 Levels of Processing
8.2 Direct Data Fusion
8.2.1 Optimal Averaging for Sensor Arrays
8.2.2 Source Recovery
8.3 Feature-Level Fusion
8.3.1 Feature Detection
8.3.2 Distance Metrics
8.3.3 Instance-Based Learning
8.3.4 Distance-Based Clustering
8.4 Dimensionality Reduction
8.4.1 Multidimensional Scaling (MDS)
8.4.2 Locally Linear Embedding (LLE)
8.4.3 Laplacian Eigenmaps
8.4.4 Isometric Mapping (Isomap)
8.5 Feature Selection
8.5.1 Feature Relevance
8.5.2 Feature Relevance Based on ROC Analysis
8.5.3 Feature Selection Based on ROC Analysis
8.5.4 Multi-objective Feature Selection
8.5.5 Feature Redundancy
8.6 Decision-Level Fusion
8.7 Methods for Computing with Large Datasets
8.8 Fusing Datasets in Parallel Using MapReduce
8.9 Alternatives and Beyond MapReduce
8.10 Conclusions
References
Chapter 9: Context Aware Sensing
9.1 Introduction
9.2 Application Scenarios
9.3 Preprocessing for Context Sensing
9.3.1 Sources of Signal Variations
9.3.2 Data Normalisation
9.3.3 Information Granularity
9.4 Context Recognition Techniques
9.4.1 Artificial Neural Networks (ANNs)
9.4.2 Hidden Markov Models (HMMs)
9.4.3 Factor Graphs (FGs)
9.4.4 Other Techniques
9.5 From Context Sensing to Behaviour Profiling
9.5.1 Behaviour Profiling
9.5.2 Transitional Activities
9.5.3 Concurrent and Interleaving Contexts
9.5.4 A Distributed Inferencing Model for Context Recognition
9.6 Conclusions
References
Chapter 10: Autonomic Sensing
10.1 Introduction
10.2 Autonomic Sensing
10.3 Fault Detection and Self-Healing
10.3.1 Belief Networks
10.3.2 Belief Propagation Through Message Passing
10.3.3 Self-Healing with Hidden Node
10.4 Networking and Self-Organisation
10.4.1 Medium Access Control Sub-layer
10.4.2 Network Layer
10.4.3 Application Layer
10.5 Security and Self-Protection
10.5.1 Bacterial Attacks
10.5.2 Viral Infection
10.5.3 Secured Protocols
10.5.3.1 SNEP
10.5.3.2 muTESLA
10.5.3.3 Cryptography for Ad Hoc Links
10.5.3.4 Biometrics-Based Cryptography
10.5.4 Self-Protection
10.6 Conclusions
References
Chapter 11: Wireless Sensor Microsystem Design: A Practical Perspective
11.1 Introduction
11.2 The Endoscopic Capsule
11.3 Applications for Wireless Capsule Devices
11.4 Technology
11.4.1 Design Constraints
11.4.2 Microsystem Design
11.4.3 Integrated Sensors
11.4.3.1 Physical
11.4.3.2 Chemical
11.4.3.3 Biological
11.5 Electronics System Design
11.5.1 Analogue Electronic Front-End Acquisition Design
11.5.2 Digital System Design
11.6 Wireless Transmission
11.7 Power Sources
11.8 Packaging
11.9 Conclusions
References
Chapter 12: Wearable Sensor Integration and Bio-motion Capture: A Practical Perspective
12.1 Introduction
12.1.1 Optical Tracking Systems
12.1.2 Mechanical-Based Tracking Systems
12.1.3 Wearable Inertial-Sensor Based Tracking Systems
12.2 Orientation Representation: Quaternion
12.2.1 Quaternion Definition
12.2.2 Quaternion Algebra
12.2.3 Quaternion and Rotation Matrix
12.2.4 Quaternion Integration
12.3 Bayesian Fusion for Orientation Estimation
12.3.1 Bayesian Fusion Theory
12.3.2 Dynamic and Measurement Model
12.3.3 Kalman Filtering
12.3.4 Temporary Interference and Processing
12.4 Human Body Motion Reconstruction
12.4.1 Human Biomechanical Model
12.4.2 Posture Estimation
12.5 Applications of Bio-motion Analysis
12.6 Network and Quality-of-Service for Bio-motion Analysis
12.7 Conclusions
References
Appendix A: Wireless Sensor Development Platforms
A.1 Introduction
A.2 System Architecture
A.2.1 Processor
A.2.2 Wireless Communication
A.2.2.1 Radio Transceiver
A.2.2.2 Antenna
A.2.2.3 Communication Protocol
A.2.3 Memory
A.2.4 Sensor Interface
A.2.4.1 Analogue Interface
A.2.4.2 Digital Interface
A.2.4.3 Integrated Sensors
A.2.5 Power Supply
A.3 Conclusions
References
Appendix B: BSN Software and Development Tools
B.1 Introduction
B.2 BSN Requirements and Issues
B.3 Operating Systems for BSNs
B.4 BSNOS - An Operating System for BSN
References
Index