About the Editors xi
List of Contributors xiii
Preface xv
1 Smart Sensor Design 1
Kofi Makinwa
1.1 Introduction 1
1.2 Smart Sensors 2
1.2.1 Interface Electronics 3
1.2.2 Calibration and Trimming 5
1.3 A Smart Temperature Sensor 5
1.3.1 Operating Principle 6
1.3.2 Interface Electronics 6
1.3.3 Recent Work 8
1.4 A Smart Wind Sensor 8
1.4.1 Operating Principle 8
1.4.2 Interface Electronics 10
1.4.3 Recent Work 11
1.5 A Smart Hall Sensor 11
1.5.1 Operating Principle 11
1.5.2 Interface Electronics 12
1.5.3 Recent Work 13
1.6 Conclusions 14
References 14
2 Calibration and Self-Calibration of Smart Sensors 17
Michiel Pertijs
2.1 Introduction 17
2.2 Calibration of Smart Sensors 18
2.2.1 Calibration Terminology 18
2.2.2 Limited Validity of a Calibration 19
2.2.3 Specifics of Smart Sensor Calibration 20
2.2.4 Storing Calibration Data in the Sensor 20
2.2.5 Calibration in the Production Process 23
2.2.6 Opportunities for Smart Sensor Calibration 24
2.2.7 Case Study: A Smart Temperature Sensor 24
2.3 Self-Calibration 27
2.3.1 Limitations of Self-Calibration 27
2.3.2 Self-Calibration by Combining Multiple Sensors 27
2.3.3 Self-Calibrating Sensactors 30
2.3.4 Case Study: A Smart Magnetic Field Sensor 31
2.3.5 Null-Balancing Sensactors 33
2.3.6 Case Study: A Smart Wind Sensor 35
2.3.7 Other Self-Calibration Approaches 36
2.4 Summary and Future Trends 38
2.4.1 Summary 38
2.4.2 Future Trends 39
References 40
3 Precision Instrumentation Amplifiers 42
Johan Huijsing
3.1 Introduction 42
3.2 Applications of Instrumentation Amplifiers 43
3.3 Three-OpAmp Instrumentation Amplifiers 44
3.4 Current-Feedback Instrumentation Amplifiers 46
3.5 Auto-Zero OpAmps and InstAmps 48
3.6 Chopper OpAmps and InstAmps 52
3.7 Chopper-Stabilized OpAmps and InstAmps 56
3.8 Chopper-Stabilized and AZ Chopper OpAmps and InstAmps 62
3.9 Summary and Future Directions 65
References 66
4 Dedicated Impedance-Sensor Systems 68
Gerard Meijer, Xiujun Li, Blagoy Iliev, Gheorghe Pop, Zu-Yao Chang, Stoyan Nihtianov, Zhichao Tan, Ali Heidari and Michiel Pertijs
4.1 Introduction 68
4.2 Capacitive-Sensor Interfaces Employing Square-Wave Excitation Signals 71
4.2.1 Measurement of Single Elements 71
4.2.2 Energy-Efficient Interfaces Based on Period Modulation 71
4.2.3 Measurement of Capacitive Sensors with High Speed and High Resolution 74
4.2.4 Measurement of Grounded Capacitors: Feed-Forward Active Guarding 76
4.3 Dedicated Measurement Systems: Detection of Micro-Organisms 78
4.3.1 Characterization of Conductance Changes Due to Metabolism 78
4.3.2 Impedance Measurements with a Relaxation Oscillator 81
4.4 Dedicated Measurement Systems: Water-Content Measurements 83
4.4.1 Background 83
4.4.2 Capacitance Versus Water Content 83
4.4.3 Skin and Proximity Effects 85
4.4.4 Dedicated Interface System for Water-Content Measurements 87
4.5 Dedicated Measurement Systems: A Characterization System for Blood Impedance 89
4.5.1 Characteristics of Blood and Electrical Models 89
4.5.2 In-vivo Blood Analysis System 92
4.5.3 Experimental Results 95
4.6 Conclusions 97
References 98
5 Low-Power Vibratory Gyroscope Readout 101
Chinwuba Ezekwe and Bernhard Boser
5.1 Introduction 101
5.2 Power-Efficient Coriolis Sensing 101
5.2.1 Review of Vibratory Gyroscopes 102
5.2.2 Electronic Interface 102
5.2.3 Readout Interface 103
5.2.4 Improving Readout Interface Power Efficiency 105
5.2.5 Exploiting the Sense Resonance 106
5.3 Mode Matching 108
5.3.1 Estimating the Mismatch 109
5.3.2 Tuning Out the Mismatch 112
5.3.3 Closing the Tuning Loop 114
5.3.4 Practical Considerations 116
5.4 Force Feedback 119
5.4.1 Mode-Matching Consideration 119
5.4.2 Preliminary System Architecture and Model for Stability Analysis 120
5.4.3 Accommodating Parasitic Resonances 121
5.4.4 Positive Feedback Architecture 126
5.5 Experimental Prototype 133
5.5.1 Implementation 133
5.5.2 Experimental Results 138
5.6 Summary 142
References 143
6 Introduction to CMOS-Based DNA Microarrays 145
Roland Thewes
6.1 Introduction 145
6.2 Basic Operation Principle and Application of DNA Microarrays 146
6.3 Functionalization 149
6.4 CMOS Integration 150
6.5 Electrochemical Readout Techniques 153
6.5.1 Detection Principles 153
6.5.2 Potentiometric Setup 160
6.5.3 Readout Circuitry 162
6.6 Further Readout Techniques 165
6.6.1 Labeling-Based Approaches 165
6.6.2 Label-Free Approaches 166
6.7 Remarks on Packaging and Assembly 169
6.8 Concluding Remarks and Outlook 169
References 170
7 CMOS Image Sensors 173
Albert Theuwissen
7.1 Impact of CMOS Scaling on Image Sensors 173
7.2 CMOS Pixel Architectures 175
7.3 Photon Shot Noise 180
7.4 Analog-to-Digital Converters for CMOS Image Sensors 181
7.5 Light Sensitivity 184
7.6 Dynamic Range 186
7.7 Global Shutter 187
7.8 Conclusion 188
Acknowledgment 188
References 188
8 Exploring Smart Sensors for Neural Interfacing 190
Tim Denison, Peng Cong and Pedram Afshar
8.1 Introduction 190
8.2 Technical Considerations for Designing a Dynamic Neural Control System 192
8.3 Predicate Therapy Devices Using Smart-Sensors in a Dynamic Control Framework: Lessons Derived from Closed-Loop Cardiac Pacemakers 195
8.4 The Application of âIndirectâ Smart Sensing Methods: A Case Study of Posture Responsive Spinal Cord Stimulation for Chronic Pain 198
8.4.1 Overview of the Posture Responsive Control System 198
8.4.2 The Design Challenge: Defining the Desired Patient State 198
8.4.3 The Physical Sensor: Three Axis Accelerometer 200
8.4.4 Design Details of the Three-Axis Accelerometer 202
8.4.5 Making the Sensor âSmartâ with State Estimation: The Position Detection Algorithm and Titration Algorithm 205
8.4.6 âClosing the Loopâ: Mapping Inertial-Information to Stimulation Parameters for Posture-Based Adaptive Therapy 206
8.5 Direct Sensing of Neural States: A Case Study in Smart Sensors for Measurement of Neural States and Enablement of Closed-Loop Neural Systems 207
8.5.1 Implantable Bidirectional Brain-Machine-Interface System Design 209
8.5.2 Design Overview of a Chopper Stabilized EEG Instrumentation Amplifier 210
8.5.3 Exploration of Neural Smart Sensing in the Brain: Prototype Testing in an Animal Models 219
8.5.4 Demonstrating the Concepts of Smart Sensing in the Brain: Real-Time Brain-State Estimation and Stimulation Titration 224
8.6 Future Trends and Opportunities for Smart Sensing in the Nervous System 231
Disclosure 233
References 233
9 Micropower Generation: Principles and Applications 237
Ruud Vullers, Ziyang Wang, Michael Renaud, Hubregt Visser, Jos Oudenhoven and Valer Pop
9.1 Introduction 237
9.2 Energy Storage Systems 240
9.2.1 Introduction 240
9.2.2 Supercapacitors 241
9.2.3 Lithium-Ion Batteries 242
9.2.4 Thin-Film Lithium-Ion Batteries 244
9.2.5 Energy Storage Applications 245
9.3 Thermoelectric Energy Harvesting 246
9.3.1 Introduction 246
9.3.2 State-of-the-Art 247
9.3.3 Conversion Efficiency 252
9.3.4 Power Management 252
9.3.5 Conclusion 253
9.4 Vibration and Motion Energy Harvesting 253
9.4.1 Introduction 253
9.4.2 Machine Environment: Resonant Systems 254
9.4.3 Human Environment: Non-Resonant Systems 259
9.4.4 Power Management 261
9.4.5 Summary 261
9.5 Far-Field RF Energy Harvesting 262
9.5.1 Introduction 262
9.5.2 General principle 262
9.5.3 Analysis and Design 265
9.5.4 Application 266
9.6 Photovoltaic 268
9.7 Summary and Future Trends 268
9.7.1 Summary 268
9.7.2 Future Trends 270
References 270
Index 275
