Bio-Medical CMOS ICs

Preface

Contents

Contributors

1 Introduction to Bio-Medical CMOS IC

1.1 Introduction to Bio-Medical CMOSIC

1.2 Architecture of Sensor Systems with Bio-medical CMOS IC

1.3 Applications and Future Trends

1.4 Organization of the Book

References

Part I Vital Signal Sensing and Processing

2 Introduction to Bioelectricity

2.1 Introduction

2.2 Electrical Properties of the Human body

2.2.1 Cell Membrane

2.2.2 Membrane Potential

2.2.3 Equivalent Circuit Model for the Plasma Membrane

2.2.4 Graded Response of Membrane Potential

2.2.5 Action Potential

2.2.6 Synaptic Transmission

2.3 Equivalent Circuit Model of Tissues and Organs

2.4 Biomedical Devices

2.4.1 Electrocardiography

2.4.2 Electroencephalography

2.4.3 Electromyography

2.5 Current Research Trends in Biomedical Electrical Instruments

References

3 Biomedical Electrodes For Biopotential Monitoring and Electrostimulation

3.1 Introduction

3.2 Electrical Properties of Electrode-Skin Interface

3.2.1 The Electrode-Electrolyte Interface

3.2.1.1 The Electrode-Electrolyte Potential

3.2.1.2 The Electrode-Electrolyte Impedance

3.2.1.3 Complex Impedance Plot

3.2.1.4 Bode Plot

3.2.1.5 Polarization

3.2.1.6 Transient Response and Tissue Damage

3.2.1.7 Limit Voltages and Currents of Linearity

3.2.1.8 Electrode Metals

3.2.2 The Skin

3.2.2.1 Structure of the Skin

3.2.2.2 Electrical Properties of the Skin

3.2.2.3 The Skin's Parallel Capacitance, CSP

3.2.2.4 The Skin's Parallel Resistance, RSP

3.3 Electrode Design

3.3.1 External Biosignal Monitoring Electrodes

3.3.1.1 Historical Background

3.4 Modern Disposable Electrodes

3.5 Solid Conductive Adhesive Electrodes

3.6 Wearable Electrodes for Personalized Health

3.6.1 External Electrostimulation Electrodes

3.6.1.1 Historical Background

3.6.1.2 Current Density Considerations

3.6.1.3 Modern Electrode Designs

3.7 Implant Electrodes

3.7.1 Historical Background

3.7.2 Some Modern Electrode Designs

3.7.3 Microelectrodes

3.8 Electrode Standards

3.8.1 Standards for Biosignal Monitoring Electrodes

3.8.1.1 Standards for Disposable ECG electrodes. ANSI/AAMI EC 12 (2000)

3.8.2 Standards for Stimulation Electrodes

3.8.2.1 Standards for Automatic External Defibrillators and Remote-Control Defibrillators. ANSI/AAMI DF 80 (2003)

3.8.2.2 Standards for Electrosurgical Devices. ANSI/AAMI HF 18 (2001)

3.9 Summary

References

4 Readout Circuits

4.1 Introduction

4.2 Biopotential Acquisition

4.2.1 Biopotential Signals

4.2.2 Biopotential Electrodes

4.2.3 Interference Theory

4.2.4 Noise Considerations

4.3 How Application Affects the Choice of Instrumentation Amplifier Topology

4.4 Power Efficient Instrumentation Amplifier Topologies for Biopotential Signal Extraction

4.4.1 Limitations of Existing Off-the-shelf Instrumentation Amplifier Topologies

4.4.2 Instrumentation Amplifiers Utilizing Pseudo Resistors

4.4.3 Introduction to Chopper Modulation

4.4.4 Chopper Modulating Amplifiers for Biopotential Signal Extraction

4.4.5 Summary and Comparison of Topologies

4.5 Current Mode Instrumentation Amplifiers

4.5.1 Open-Loop Current Mode Instrumentation Amplifiers

4.5.2 Closed-Loop Current Mode Instrumentation Amplifiers (Current Balancing/Feedback Instrumentation Amplifiers)

4.5.3 Chopper Modulated Current Balancing Instrumentation Amplifiers

4.6 Examples of ICs for Biopotential Acquisition

4.7 Conclusion

References

5 Low-Power ADCs for Bio-Medical Applications

5.1 ADC Specifications

5.1.1 Ideal ADC Specifications

5.1.2 Practical ADC Specifications

5.1.3 ADC Implementation Issues

5.2 Charge-Sharing Successive Approximation ADCs

5.2.1 Basic Operation Principle

5.2.1.1 Input Sampling

5.2.1.2 Successive Approximation, MSB

5.2.1.3 Successive Approximation, MSB-1

5.2.1.4 Successive Approximation, Remaining Bits

5.2.1.5 First Block Diagram

5.2.2 Asynchronous Operation

5.2.3 Binary Scaled Capacitor Array

5.2.4 Comparator Noise

5.2.4.1 Comparator Offset

5.2.5 Implementation

5.3 Comparator-Based Asynchronous Binary Search ADCs

5.3.1 Operating Principle

5.3.2 Implemented Two-Step 1-b Coarse 6-b Fine Architecture

5.3.2.1 Clock Generation and A/D-Converter Timing

5.3.2.2 Dynamic Comparator with Embedded Threshold and Encoding

5.3.2.3 Passive Track-and-Hold

5.3.2.4 Feedback D/A Converter

5.3.2.5 Calibration

5.3.2.6 Power Breakdown

5.3.3 Experimental Results

5.3.3.1 Layout Implementation

5.3.3.2 Measurement Setup

5.3.3.3 Measurement Results

5.3.3.4 Sensitivity to Environmental Parameters

5.3.3.5 Energy Efficiency

5.3.4 Summary

5.4 Conclusions

References

6 Low Power Bio-Medical DSP

6.1 Introduction

6.2 ECG Signal Processor Design

6.2.1 Algorithm Overview

6.2.2 Hardware Implementation

6.3 Pre Processing

6.3.1 Filtering

6.3.2 Feature Extraction

6.3.3 ECG Skeleton

6.3.4 Segmentation Memory

6.4 Classification Processing

6.4.1 ECG Classification Algorithm

6.4.2 Micro Architecture of RISC

6.5 Post-processor

6.5.1 Huffman Coding

6.5.2 AES-128

6.6 Low Energy Techniques

6.6.1 Heterogeneous Processor Integration

6.6.2 Low Supply Voltage Operation

6.6.3 Segmentation-Based Pipelined Operation

6.6.4 Clock Gating

6.6.5 On-Chip Memory Reduction

References

Part II Bio-Medical Wireless Communication

7 Short Distance Wireless Communications

7.1 Introduction

7.2 Biomedical Telemetry Methods

7.2.1 Wave Propagation

7.2.1.1 EM Wave Propagation

7.2.1.2 Acoustic Wave Propagation

7.2.2 Conduction

7.2.3 Near-Field Coupling

7.2.3.1 Capacitive Links

7.2.3.2 Inductive Links

7.2.4 Near-Field versus Far-Field

7.3 Modulation Methods

7.3.1 Analog Modulation

7.3.1.1 AM

7.3.1.2 FM and PM

7.3.1.3 Discussion on Analog Modulation Methods

7.3.2 Analog Pulse Modulation Encoding

7.3.2.1 Pulse Amplitude Modulation (PAM)

7.3.2.2 Pulse Width/Duration Modulation (PWM or PDM)

7.3.2.3 Pulse Position Modulation (PPM)

7.3.2.4 Pulse Frequency Modulation (PFM)

7.3.2.5 Analog Multiple Channel Modulation Methods

7.3.3 Digital Pulse Modulation Encoding

7.3.3.1 Pulse Code Modulation (PCM)

7.3.3.2 Line Encoding

7.3.4 Digital Modulation

7.3.4.1 ASK

7.3.4.2 FSK

7.3.4.3 PSK

7.3.4.4 Digital Multiple Channel Transmission

7.3.5 Analog or Digital Modulation?

7.3.6 Data Rates

7.4 Compression

7.4.1 Loss-Less Compression Algorithms

7.4.2 Lossy Compression Algorithms

7.5 Error Correction

7.5.1 Block Codes

7.5.2 Convolutional Codes

7.6 Carrier Frequency Selection for RF Links

7.6.1 Tissue Absorption vs. Antenna Size

7.6.2 Antenna Size vs. Bandwidth Requirements

7.6.3 Regulations vs. Bandwidth Requirements

7.7 Biomedical Telemetry Applications

7.7.1 Physiological Monitoring

7.7.1.1 Bladder Pressure Monitoring

7.7.1.2 Wireless ECG Monitoring Integrated in Textile

7.7.1.3 Textile Integrated Breathing and ECG Monitoring System

7.7.1.4 Pacemaker Monitoring and Programming

7.7.1.5 Inductive Power and Data Transmission for Wireless Endoscopy

7.7.1.6 Wireless Capsule Endoscopy: Given Imaging Pillcam

7.7.2 Orthopedic Implant Monitoring and Control

7.7.2.1 Distraction Nail Driver

7.7.2.2 Hip Prosthesis Fixation Analysis

7.7.2.3 Telemetry IC Design for Orthopedic Monitoring

7.7.3 Nerve Implant Monitoring and Stimulation

7.7.3.1 Cochlear Implants

7.7.3.2 Retinal Prosthesis

7.7.4 General Monitoring and Identification

7.7.4.1 RFID

7.7.4.2 Portable Heart Rate Monitoring

7.7.5 Overview of Commercial Biomedical Transmitters

7.7.5.1 Zarlink ZL70101

7.7.5.2 Zarlink ZL70250

7.7.5.3 Nordic NR24L01+

7.7.5.4 Other Manufacturers

References

8 Bio-Medical Application of WBAN: Trends and Examples

8.1 The New Wave of Healthcare Systems

8.2 An Enabling Technology: Body Area Networks

8.3 Ambulatory Cardiac Monitoring

8.3.1 Trends

8.3.2 Snapshot on the State-of-the-Art

8.3.3 Detailed View on IMEC Low-Power Ambulatory ECG Prototypes

8.4 Wireless Sleep Monitoring

8.4.1 Trends

8.4.2 Snapshot on the State-of-the-Art

8.4.3 Detailed View on IMEC Wireless Sleep Staging Prototype

8.5 Mental Health and Emotion Monitoring

8.5.1 Trends

8.5.2 Snapshot on the State-of-the-Art

8.5.3 Detailed View on IMEC Wireless ANS Monitoring Prototype

8.6 Remaining Challenges

8.6.1 Ultra-Low-Power Technologies

8.6.2 Increasing Functionality

8.6.3 Autonomous Systems

8.6.4 Multi-Parameter Sensors

8.6.5 Dry Electrodes

8.6.6 Integration and Packaging Technology

8.7 Conclusions

References

9 Body Channel Communication for Energy-Efficient BAN

9.1 Introduction

9.1.1 Motivation

9.1.2 Human Body Communications

9.2 Channel Characteristics

9.3 Design of Wideband Signaling Communication Link

9.4 Wideband Signaling Transceiver

9.4.1 WBS Receiver AFE

9.4.2 All-Digital Quadratic Sampling CDR Circuit

9.4.3 Direct Digital Transmitter

9.5 Measurement Results

9.5.1 WBS Receiver AFE

9.5.2 WBS Transceiver

9.6 System Operation Demonstration

9.6.1 Introduction

9.6.2 Related Works

9.6.3 Design Architecture

9.6.4 Realization

9.6.4.1 Summary

9.7 Conclusion

References

Part III Examples of Bio-Medical ICs

10 Wearable Healthcare System

10.1 Introduction

10.1.1 Issues on Continuous Wearable Healthcare Using BSNs

10.1.2 Snapshots of Previous Works in Health Monitoring

10.1.3 An Example Wearable Healthcare System

10.2 Reliable and Low Cost BSN for Wearable Healthcare

10.2.1 Self-Configured Wearable BSN

10.2.2 Adaptive Power Transmission

10.2.3 Network Controller SoC

10.2.4 Summary

10.3 Fabric Circuit Board

10.3.1 Introduction

10.3.2 Dry Electrodes by P-FCB

10.3.2.1 Electrode Impedance

10.3.2.2 Impedance Versus Frequency

10.3.2.3 Impedance Over Time

10.3.3 Inductors by P-FCB

10.3.4 Summary

10.4 Wirelessly Powered Sensor

10.4.1 Introduction

10.4.2 Form Factor

10.4.3 Sensor Design

10.4.4 Wireless Power Transmission

10.4.4.1 Conventional Rectifier

10.4.4.2 Adaptive Threshold Rectifier (ATR)

10.4.5 Sensor Readout Front-End

10.4.6 Implementation

10.4.7 Summary

10.5 System Implementation

10.5.1 Wirelessly Powered Adhesive Bandage Sensor

10.5.2 Health Monitoring Chest Band

10.6 Conclusion

References

11 Digital Hearing Aid and Cochlear Implant

11.1 Introduction of the Digital Hearing Aid

11.1.1 Population Trends of the Hearing Aids

11.1.2 Future of the Hearing Aids

11.2 Conventional Digital Hearing Aids

11.2.1 Types of the Digital Hearing Aids

11.2.2 Design Issues of the Digital Hearing Aids

11.3 An Adaptive Digital Hearing Aid Chip with On Chip Human Factors Consideration

11.3.1 Introduction

11.3.2 An Internal Gain Verification Algorithm

11.3.2.1 Conventional Gain Verification Method

11.3.2.2 Autonomous Gain Verification Algorithm

11.3.2.3 Simulation Results

11.3.3 A Multi Mode Audio Processor

11.3.3.1 Hearing Aid Mode Operation

11.3.3.2 Smart Earphone Mode Operation

11.3.3.3 Direction Perception Mode Operation

11.3.4 Low Power Analog Front-End

11.3.4.1 System Design Considerations

11.3.4.2 Overall Architecture of the Analog Front-End

11.3.4.3 Adaptive Analog Front-End Design

11.3.4.4 Building Block Circuits Design

11.3.5 Low Power Digital Back-End

11.3.5.1 16 Channel IFIR DSP

11.3.5.2 Heterogeneous DAC

11.3.5.3 H-bridge as a Speaker Driver

11.3.6 Implementation and Measurement Results

11.3.7 Conclusions

11.4 Cochlear Implant

11.4.1 Introduction of the Cochlear Implant

11.4.2 Design of the Cochlear Implant

11.4.3 Future of the Cochlear Implant

References

12 Cardiac Rhythm Management ICs

12.1 Introduction

12.1.1 Anatomy of the Heart

12.1.2 Pacemakers

12.1.3 Implantable Cardioverter Defibrillators

12.2 Components of Pacemaker and ICD

12.2.1 Leads

12.2.2 Device Programmer

12.2.3 Device Subsystems

12.2.4 Case, Feedthrough and Header

12.2.5 Battery

12.2.6 ICD Capacitors

12.3 Electronics

12.3.1 Basic Pacemaker Functions

12.3.2 Sensing Circuits

12.3.3 ADC

12.3.4 Pace Driver and Mux

12.3.5 MCU

12.3.6 Sensor I/O

12.3.7 Telemetry

12.3.8 Clock Generator and Power Management

12.4 Basic ICD Functions

12.5 IC Process Technology

12.5.1 Process Technology

12.5.2 Low Power Design Techniques

12.6 Future Trends

References

13 Neurostimulation Design from an Energy and Information Transfer Perspective

13.1 Introduction

13.2 Overview of Challenges and System Requirements

13.3 Completing the Energy Transfer Circuit: From Battery to Body

13.3.1 Secondary Cell Recharge

13.3.2 Energy Source Characteristics

13.3.3 Boosting the Voltage---Providing Overhead for the Stimulation Engine

13.3.4 Generating the Stimulation Signal

13.3.4.1 Reference Current Generator

13.3.4.2 Active Sources and Sinks

13.3.4.3 Scaling Considerations for Electrode Sinks and Sources

13.3.4.4 Output Regulation with a Reference Resistor

13.3.4.5 Fractional Current Regulation Through Electrodes

13.3.4.6 Tying It All Together: A Complete Stimulation Engine

13.4 The Tissue Interface and General Safety Considerations

13.5 Future Directions and Trends

13.5.1 Closed-Loop, Adaptive Stimulation

13.5.2 Optogenetic Neuromodulation

13.6 Conclusion

References

14 Artificial Retina IC

14.1 Introduction

14.2 Fundamentals for Artificial Retina

14.2.1 Retina and Blindness

14.2.2 Principle of Artificial Retina

14.2.3 Classification of Artificial Retina

14.2.3.1 Extraocular Artificial Retina

14.2.3.2 Intraocular Artificial Retina

14.2.4 Artificial Retina System

14.3 Basic Circuits for Artificial Retina

14.3.1 Stimulation of Retinal Cells

14.3.2 Stimulator

14.3.2.1 Charge Balance

14.3.3 Photosensor

14.3.3.1 Photodiode

14.3.4 Photosensor Array in Artificial Retina IC

14.3.4.1 Micro PD Array

14.3.4.2 Active Pixel Sensor

14.3.4.3 Log Sensor

14.3.4.4 Photosensor Based on Pulse Frequency Modulation

14.3.5 Power and Data Transmission

14.4 Case studies: Artificial retina Device for over 1000 Electrodes

14.4.1 Multiple Microchip Architecture

14.4.1.1 Microchip Specification

14.4.1.2 Stimulator Specificaton

14.4.1.3 In vivo experiment

14.4.2 Multiple Microchip-Based Retinal Stimulator with Light-Controlled Function

References

Index