Body Sensor Networks

Overview

The last decade has seen a rapid surge of interest in new sensing and monitoring devices for healthcare and the use of wearable/wireless devices for clinical applications. One key development in this area is implantable in vivo monitoring and intervention devices. Several promising prototypes are emerging for managing patients with debilitating neurological disorders and for monitoring of patients with chronic cardiac diseases. Despite the technological developments of sensing and monitoring devices, issues ...

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Overview

The last decade has seen a rapid surge of interest in new sensing and monitoring devices for healthcare and the use of wearable/wireless devices for clinical applications. One key development in this area is implantable in vivo monitoring and intervention devices. Several promising prototypes are emerging for managing patients with debilitating neurological disorders and for monitoring of patients with chronic cardiac diseases. Despite the technological developments of sensing and monitoring devices, issues related to system integration, sensor miniaturization, low-power sensor interface circuitry design, wireless telemetric links and signal processing have still to be investigated. Moreover, issues related to Quality of Service, security, multi-sensory data fusion, and decision support are active research topics. This book addresses the issues of this rapidly changing field of wireless wearable and implantable sensors and discusses the latest technological developments and clinical applications of body-sensor networks.

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Product Details

  • ISBN-13: 9781849965699
  • Publisher: Springer London
  • Publication date: 3/9/2011
  • Edition description: Softcover reprint of hardcover 1st ed. 2006
  • Edition number: 1
  • Pages: 494
  • Product dimensions: 6.10 (w) x 9.10 (h) x 1.30 (d)

Table of Contents

1 Introduction 1
1.1 Wireless Sensor Networks 1
1.2 BSN and Healthcare 4
1.2.1 Monitoring Patients with Chronic Disease 6
1.2.2 Monitoring Hospital Patients 7
1.2.3 Monitoring Elderly Patients 9
1.3 Pervasive Patient Monitoring 10
1.4 Technical Challenges Facing BSN 13
1.4.1 Improved Sensor Design 13
1.4.2 Biocompatibility 14
1.4.3 Energy Supply and Demand 15
1.4.4 System Security and Reliability 16
1.4.5 Context Awareness 18
1.4.6 Integrated Therapeutic Systems 19
1.5 Personalised Healthcare 20
1.6 Finding the Ideal Architecture for BSN 22
1.7 The Future: Going from "Micro” to "Nano” 27
1.8 The Scope of the Book 30
References 34
2 Biosensor Design and Interfacing 41
2.1 Introduction 41
2.1.1 What is a Biosensor? 42
2.2 How Do Electrochemical Devices Work? 44
2.2.1 Potentiometric Devices 45

Body Sensor Networks
2.2.2 Amperometry and Voltammetry 53
2.3 Instrumentation 65
2.3.1 Potentiometry 65
2.3.2 Amperometry and Voltammetry 66
2.3.3 Reference and Counter Electrodes 68
2.4 Photoelectrochemistry and Spectroelectrochemistry 69
2.5 Biocompatibility 71
2.5.1 Sensor Fouling 71
2.5.2 Tissue Damage 73
2.6 Novel Approaches to Handling Sensor Data 73
2.7 Conclusions 80
Acknowledgements 82
References 82
3 Protein Engineering for Biosensors 89
3.1 Introduction 89
3.1.1 Electrochemical Sensors 90
3.1.2 Optical Sensors 91
3.1.3 Gravimetric Sensors 92
3.1.4 Consuming and Non-Consuming Biosensors 92
3.2 Protein Engineering 93
3.2.1 The Signal Transduction Module 95
3.2.2 The Recognition Site Module 97
3.2.3 Immobilisation Module 100
3.3 Biocompatibility and Implantation 102
3.4 Conclusions 109
References 109
4 Wireless Communication 117
4.1 Introduction 117
4.2 Inductive Coupling 118
4.3 RF Communication in Body 119
4.4 Antenna Design 121
4.5 Antenna Testing 125
4.5.1 Antenna Impedance and Radiation Resistance Measurement 125
4.5.2 Quarter Wave Line Impedance Measurement 126
4.6 Matching Network 128
4.6.1 Transmitter Tuning 128
4.6.2 The L Network 130
4.6.3 The p Network 131
4.6.4 The T and p -L Networks 132
4.6.5 Parasitic Effects 133

Contents
4.6.6 Network Choice 134
4.6.7 Radio Frequency Losses in Components and Layout Issues 135
4.6.8 Receiver Tuning 135
4.6.9 Base Station Antennas 136
4.7 Propagation 136
4.8 Materials 137
4.9 Environment 138
4.10 External Transceiver (Base Station) 138
4.11 Power Considerations 139
4.11.1 Battery Challenges 140
4.12 Defibrillation Pulse 141
4.13 Link Budget 142
4.14 Conclusions 142
References 143
5 Network Topologies, Communication Protocols and Standards 145
5.1 Network Topologies 145
5.2 Body Sensor Network Application Scenarios 148
5.2.1 Stand-Alone Body Sensor Networks 148
5.2.2 Global Healthcare Connectivity 149
5.2.3 Pervasive Sensor Networks 150
5.3 Wireless Personal Area Network Technologies 152
5.3.1 Overview 152
5.3.2 The Wireless Regulatory Environment 153
5.3.3 Wireless Communication Standards 155
5.3.4 IEEE 802.15.1: Medium-Rate Wireless Personal Area Networks 155
5.3.5 IEEE P802.15.3: High-Rate Wireless Personal Area Networks 158
5.3.6 IEEE 802.15.4: Low-Rate Wireless Personal Area Networks 160
5.3.7 ZigBee 164
5.3.8 Comparison of Technologies 168
5.4 Practical Experiences with IEEE 802.15.4 169
5.5 Healthcare System Integration 174
5.5.1 ExistingInteroperability Standards 174
5.5.2 Wireless Interoperability Standards under Development 176
5.6 Conclusions 177
References 180
6 Energy Scavenging 183
6.1 Introduction 183
6.1.1 Sensor Node Power Requirements 184
6.1.2 Batteries and Fuel Cells for Sensor Nodes 185

Body Sensor Networks
6.1.3 Ambient Energy Sources 186
6.2 Architectures for Inertial Energy Scavenging 187
6.2.1 Energy Extraction Mechanisms for Inertial Generators 187
6.2.2 Performance Limits 191
6.3 Fabrication and Testing 195
6.3.1 Device Fabrication and Structure 195
6.3.2 Device Testing 197
6.4 Module Design and Simulation 200
6.4.1 System Modelling 200
6.4.2 Integrated Simulation 204
6.5 Power Electronics and System Effectiveness 205
6.5.1 Power Electronics Requirements and Trade-offs 205
6.5.2 Semiconductor Device Design 209
6.5.3 Coherent Simulation 211
6.6 Discussion and Conclusions 213
6.6.1 What is Achievable in Body-Sensor Energy Scavenging? 213
6.6.2 Future Prospects and Trends 215
References 216
7 Towards Ultra-Low Power Bio-Inspired Processing 219
7.1 Introduction 219
7.2 Bio-Inspired Signal Processing 220
7.3 Analogue vs Digital Signal Processing 221
7.3.1 Quantised Data/Time vs Continuous Data/Time 221
7.3.2 Analogue/Digital Data Representation 222
7.3.3 Linear Operations 223
7.3.4 Non-Linear Operations 224
7.3.5 Hybrid System Organisation 224
7.4 CMOS-Based Biosensors 225
7.4.1 Ion-Sensitive Field-Effect Transistor (ISFET) 227
7.4.2 ISFET-Based Biosensors 229
7.4.3 Towards Biochemically-Inspired Processing with ISFETs 230
7.5 Applications of Ultra-Low Power Signal Processing for BSN 234
References 236
8 Multi-sensor Fusion 239
8.1 Introduction 239
8.1.1 Information Interaction of Sensor Fusion 240
8.1.2 Levels of Processing 242
8.2 Direct Data Fusion 242
8.2.1 Optimal Averaging for Sensor Arrays 243
8.2.2 Source Recovery 246

Contents
8.3 Feature Level Data Fusion 252
8.3.1 Feature Detection 252
8.3.2 Distance Metrics 253
8.3.3 Instance Based Learning 254
8.3.4 Distance Based Clustering 255
8.4 Dimensionality Reduction 258
8.4.1 Multidimensional Scaling (MDS) 259
8.4.2 Locally Linear Embedding (LLE) 260
8.4.3 Isometric Mapping (Isomap) 261
8.5 Feature Selection 262
8.5.1 Feature Relevance 264
8.5.2 Feature Relevance Based on ROC Analysis 266
8.5.3 Feature Selection Based on ROC Analysis 271
8.6 Decision Level Fusion 274
8.7 Conclusions 278
References 281
9 Context-Aware Sensing 287
9.1 Introduction 287
9.2 Application Scenarios 289
9.3 Preprocessing for Context Sensing 291
9.3.1 Information Granularity 291
9.3.2 Sources of Signal Variations 292
9.3.3 Data Normalisation 293
9.4 Context Recognition Techniques 294
9.4.1 Hidden Markov Models (HMMs) 294
9.4.2 Artificial Neural Networks (ANNs) 302
9.5 Spatio-Temporal Self Organising Maps (STSOMs) 306
9.5.1 The Basic Structure of the STSOM 307
9.5.2 The Use of Multi-Resolution for Improved Class Separation 312
9.5.3 STSOM Algorithm Design 315
9.5.4 STSOM for Context-Aware Sensing 320
9.6 Conclusions 323
References 326
10 Autonomic Sensing 333
10.1 Introduction 333
10.2 Autonomic Sensing 334
10.3 Fault Detection and Self-Healing 336
10.3.1 Belief Networks 337
10.3.2 Belief Propagation through Message Passing 339
10.4 Routing and Self-Organisation 344

Body Sensor Networks
10.5 Security and Self-Protection 348
10.5.1 Bacterial Attacks 350
10.5.2 Virus Infection 356
10.5.3 Secured Protocols 358
10.5.4 Self-Protection 362
10.6 Conclusions 365
References 366
11 Wireless Sensor Microsystem Design: A Practical Perspective 373
11.1 Introduction 373
11.2 The Diagnostic Capsule 375
11.3 Applications for Wireless Capsule Devices 376
11.3.1 Human Medicine 376
11.3.2 Animal Applications 378
11.4 Technology 379
11.4.1 Design Constraints 379
11.4.2 Microsystem Design 379
11.4.3 Integrated Sensors 381
11.5 Electronics System Design 385
11.5.1 Analogue Electronic Front-End Acquisition Design 386
11.5.2 Digital System Design 386
11.6 The Wireless Environment 388
11.7 Power Sources 390
11.8 Packaging 391
11.9 Conclusion 392
References 393
12 Conclusions and Future Outlook 399
Appendix A Wireless Sensor Development Platforms 403
A.1 Introduction 403
A.2 System Architecture 403
A.2.1 Processor 404
A.2.2 Wireless Communication 407
A.2.3 Memory 410
A.2.4 Sensor Interface 411
A.2.5 Power Supply 414
A.2.6 Operating System 415
A.3 Conclusions 418
References 418

Contents vii Appendix B BSN Development Kit and Programming Guide 423
B.1 Introduction 423
B.2 BSN Architectural Design 423
B.2.1 Microcontroller 425
B.2.2 Radio Transceiver 428
B.2.3 Flash Memory 437
B.2.4 Board Connector 438
B.2.5 Antenna 440
B.3 BSN Development Kit 441
B.3.1 BSN Nodes 442
B.3.2 USB Programmer 442
B.3.3 Sensor Board 443
B.3.4 Battery Board 447
B.3.5 Prototype Board 449
B.4 TinyOS 451
B.4.1 nesC 452
B.4.2 Execution Model 458
B.4.3 Hardware Abstraction 460
B.4.4 TOSSIM 461
B.4.5 Deluge – TinyOS Network Programming 466
B.5 BSN Programming Guide 468
B.5.1 Programming Environment 468
B.5.2 Installation Instructions 469
B.5.3 BSN Node Programming 469
B.6 Conclusions 478
References 478
Index 481

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