- •Analysis and Application of Analog Electronic Circuits to Biomedical Instrumentation
- •Dedication
- •Preface
- •Reader Background
- •Rationale
- •Description of the Chapters
- •Features
- •The Author
- •Table of Contents
- •1.1 Introduction
- •1.2 Sources of Endogenous Bioelectric Signals
- •1.3 Nerve Action Potentials
- •1.4 Muscle Action Potentials
- •1.4.1 Introduction
- •1.4.2 The Origin of EMGs
- •1.5 The Electrocardiogram
- •1.5.1 Introduction
- •1.6 Other Biopotentials
- •1.6.1 Introduction
- •1.6.2 EEGs
- •1.6.3 Other Body Surface Potentials
- •1.7 Discussion
- •1.8 Electrical Properties of Bioelectrodes
- •1.9 Exogenous Bioelectric Signals
- •1.10 Chapter Summary
- •2.1 Introduction
- •2.2.1 Introduction
- •2.2.4 Schottky Diodes
- •2.3.1 Introduction
- •2.4.1 Introduction
- •2.5.1 Introduction
- •2.5.5 Broadbanding Strategies
- •2.6 Photons, Photodiodes, Photoconductors, LEDs, and Laser Diodes
- •2.6.1 Introduction
- •2.6.2 PIN Photodiodes
- •2.6.3 Avalanche Photodiodes
- •2.6.4 Signal Conditioning Circuits for Photodiodes
- •2.6.5 Photoconductors
- •2.6.6 LEDs
- •2.6.7 Laser Diodes
- •2.7 Chapter Summary
- •Home Problems
- •3.1 Introduction
- •3.2 DA Circuit Architecture
- •3.4 CM and DM Gain of Simple DA Stages at High Frequencies
- •3.4.1 Introduction
- •3.5 Input Resistance of Simple Transistor DAs
- •3.7 How Op Amps Can Be Used To Make DAs for Medical Applications
- •3.7.1 Introduction
- •3.8 Chapter Summary
- •Home Problems
- •4.1 Introduction
- •4.3 Some Effects of Negative Voltage Feedback
- •4.3.1 Reduction of Output Resistance
- •4.3.2 Reduction of Total Harmonic Distortion
- •4.3.4 Decrease in Gain Sensitivity
- •4.4 Effects of Negative Current Feedback
- •4.5 Positive Voltage Feedback
- •4.5.1 Introduction
- •4.6 Chapter Summary
- •Home Problems
- •5.1 Introduction
- •5.2.1 Introduction
- •5.2.2 Bode Plots
- •5.5.1 Introduction
- •5.5.3 The Wien Bridge Oscillator
- •5.6 Chapter Summary
- •Home Problems
- •6.1 Ideal Op Amps
- •6.1.1 Introduction
- •6.1.2 Properties of Ideal OP Amps
- •6.1.3 Some Examples of OP Amp Circuits Analyzed Using IOAs
- •6.2 Practical Op Amps
- •6.2.1 Introduction
- •6.2.2 Functional Categories of Real Op Amps
- •6.3.1 The GBWP of an Inverting Summer
- •6.4.3 Limitations of CFOAs
- •6.5 Voltage Comparators
- •6.5.1 Introduction
- •6.5.2. Applications of Voltage Comparators
- •6.5.3 Discussion
- •6.6 Some Applications of Op Amps in Biomedicine
- •6.6.1 Introduction
- •6.6.2 Analog Integrators and Differentiators
- •6.7 Chapter Summary
- •Home Problems
- •7.1 Introduction
- •7.2 Types of Analog Active Filters
- •7.2.1 Introduction
- •7.2.3 Biquad Active Filters
- •7.2.4 Generalized Impedance Converter AFs
- •7.3 Electronically Tunable AFs
- •7.3.1 Introduction
- •7.3.3 Use of Digitally Controlled Potentiometers To Tune a Sallen and Key LPF
- •7.5 Chapter Summary
- •7.5.1 Active Filters
- •7.5.2 Choice of AF Components
- •Home Problems
- •8.1 Introduction
- •8.2 Instrumentation Amps
- •8.3 Medical Isolation Amps
- •8.3.1 Introduction
- •8.3.3 A Prototype Magnetic IsoA
- •8.4.1 Introduction
- •8.6 Chapter Summary
- •9.1 Introduction
- •9.2 Descriptors of Random Noise in Biomedical Measurement Systems
- •9.2.1 Introduction
- •9.2.2 The Probability Density Function
- •9.2.3 The Power Density Spectrum
- •9.2.4 Sources of Random Noise in Signal Conditioning Systems
- •9.2.4.1 Noise from Resistors
- •9.2.4.3 Noise in JFETs
- •9.2.4.4 Noise in BJTs
- •9.3 Propagation of Noise through LTI Filters
- •9.4.2 Spot Noise Factor and Figure
- •9.5.1 Introduction
- •9.6.1 Introduction
- •9.7 Effect of Feedback on Noise
- •9.7.1 Introduction
- •9.8.1 Introduction
- •9.8.2 Calculation of the Minimum Resolvable AC Input Voltage to a Noisy Op Amp
- •9.8.5.1 Introduction
- •9.8.5.2 Bridge Sensitivity Calculations
- •9.8.7.1 Introduction
- •9.8.7.2 Analysis of SNR Improvement by Averaging
- •9.8.7.3 Discussion
- •9.10.1 Introduction
- •9.11 Chapter Summary
- •Home Problems
- •10.1 Introduction
- •10.2 Aliasing and the Sampling Theorem
- •10.2.1 Introduction
- •10.2.2 The Sampling Theorem
- •10.3 Digital-to-Analog Converters (DACs)
- •10.3.1 Introduction
- •10.3.2 DAC Designs
- •10.3.3 Static and Dynamic Characteristics of DACs
- •10.4 Hold Circuits
- •10.5 Analog-to-Digital Converters (ADCs)
- •10.5.1 Introduction
- •10.5.2 The Tracking (Servo) ADC
- •10.5.3 The Successive Approximation ADC
- •10.5.4 Integrating Converters
- •10.5.5 Flash Converters
- •10.6 Quantization Noise
- •10.7 Chapter Summary
- •Home Problems
- •11.1 Introduction
- •11.2 Modulation of a Sinusoidal Carrier Viewed in the Frequency Domain
- •11.3 Implementation of AM
- •11.3.1 Introduction
- •11.3.2 Some Amplitude Modulation Circuits
- •11.4 Generation of Phase and Frequency Modulation
- •11.4.1 Introduction
- •11.4.3 Integral Pulse Frequency Modulation as a Means of Frequency Modulation
- •11.5 Demodulation of Modulated Sinusoidal Carriers
- •11.5.1 Introduction
- •11.5.2 Detection of AM
- •11.5.3 Detection of FM Signals
- •11.5.4 Demodulation of DSBSCM Signals
- •11.6 Modulation and Demodulation of Digital Carriers
- •11.6.1 Introduction
- •11.6.2 Delta Modulation
- •11.7 Chapter Summary
- •Home Problems
- •12.1 Introduction
- •12.2.1 Introduction
- •12.2.2 The Analog Multiplier/LPF PSR
- •12.2.3 The Switched Op Amp PSR
- •12.2.4 The Chopper PSR
- •12.2.5 The Balanced Diode Bridge PSR
- •12.3 Phase Detectors
- •12.3.1 Introduction
- •12.3.2 The Analog Multiplier Phase Detector
- •12.3.3 Digital Phase Detectors
- •12.4 Voltage and Current-Controlled Oscillators
- •12.4.1 Introduction
- •12.4.2 An Analog VCO
- •12.4.3 Switched Integrating Capacitor VCOs
- •12.4.6 Summary
- •12.5 Phase-Locked Loops
- •12.5.1 Introduction
- •12.5.2 PLL Components
- •12.5.3 PLL Applications in Biomedicine
- •12.5.4 Discussion
- •12.6 True RMS Converters
- •12.6.1 Introduction
- •12.6.2 True RMS Circuits
- •12.7 IC Thermometers
- •12.7.1 Introduction
- •12.7.2 IC Temperature Transducers
- •12.8 Instrumentation Systems
- •12.8.1 Introduction
- •12.8.5 Respiratory Acoustic Impedance Measurement System
- •12.9 Chapter Summary
- •References
Sources and Properties of Biomedical Signals |
|
11 |
||
|
|
Action potentials |
|
SA node AP |
|
|
|
|
AV node AP |
|
|
|
|
t |
Sup. vena cava |
|
|
Atrial muscle AP |
|
SA node |
LA |
− 90 mV |
|
|
AV node |
|
|
||
|
|
|
||
RA |
|
Delays in |
|
Common bundle AP |
|
|
|
||
|
|
conduction |
Bundle branch AP |
|
|
|
bundles |
|
Purkinje fiber AP |
|
|
LV |
|
|
|
|
|
|
|
|
RV |
−95 mV |
|
|
|
|
|
|
|
|
|
+20 mV |
|
Ventricular AP |
|
|
0 mV |
|
|
|
> 150 V/sec. |
|
− 90 mV |
|
|
|
R |
|
|
ECG |
|
|
(Lead III) |
|
0 |
P |
T |
|
||
|
Q |
S |
|
|
ca. 1 sec |
FIGURE 1.4
Schematic cut-away of a mammalian heart showing the SA and AV node pacemakers, as well as intracellular action potentials from different locations in the heart. Bottom trace is a typical lead III skin surface-recorded ECG waveform.
and otherwise not grounded. Other biopotential amplifiers used in a clinical or research setting with humans, such as for measurement of EEG, EMG, ERG, ECoG, etc., must also have galvanic isolation.
1.6Other Biopotentials
1.6.1Introduction
Many other biopotentials are measured for research and clinical purposes. These include the electroencephalogram (EEG); electroretinogram (ERG); electrooculogram (EOG); and electrocochleogram (ECoG) (Northrop, 2002). All of these signals are low amplitude (hundreds of microvolts at peak) and contain primarily low frequencies (0.01 to 100 Hz).
© 2004 by CRC Press LLC
12 |
Analysis and Application of Analog Electronic Circuits |
1.6.2EEGs
The electroencephalogram is used to diagnose brain injuries and brain tumors noninvasively, as well as in neuropsychology research. Electroencephalograms are generally recorded from the scalp, which means the underlying, cortical brain electrical activity must pass through the pia and dura mater membranes, cerebrospinal fluid, skull, and scalp. Considerable attenuation and spatial averaging occurs due to these structures relative to the electrical activity, which can be recorded directly from the brain’s surface with wick electrodes. The largest EEG potentials recorded on the scalp are approximately 150 μV at peak. In an attempt to localize sites of EEG activity on the brain’s surface, multiple electrode EEG recordings are made from the scalp. The standard 10 to 20 EEG electrode array uses 19 electrodes; some electrode arrays used in brain research use 128 electrodes (Northrop, 2002).
EEGs have traditionally been divided into four frequency bands:
•Delta waves have the largest amplitudes and lowest frequencies (≤3.5 Hz); they occur in adults in deep sleep.
•Theta waves are large-amplitude, low-frequency voltages (3.5 to 7.5 Hz) and are seen in sleep in adults and in prepubescent children.
•The spectra of alpha waves lie between 7.5 and 13 Hz and their amplitudes range from 20 to 200 μV. Alpha waves are recorded from adults who are conscious but relaxed with the eyes closed. Alpha activity disappears when the eyes are open and the subject focuses on a task. Alpha waves are best recorded from posterior lateral portions of the scalp.
•Beta waves are defined for frequencies from 13 to 50 Hz and are most easily found in the parietal and frontal regions of the scalp. Beta waves are subdivided into types I and II: type I disappears and type II appears during intense mental activity (Webster, 1992).
EEG amplifiers must work with low-frequency, low amplitude signals; consequently, they must be low noise types with low 1/f noise spectrums. EEG amplifiers can be reactively coupled; their –3-dB frequencies should be about 0.2 and 100 Hz. Amplifier midband gain needs to be on the order of 104 to 105.
EEG measurement also includes evoked cortical potentials used in experimental brain research. A patient is presented with a periodic stimulus, which can be auditory (a click or tone), visual (a flash of light or a tachistoscopically presented picture), tactile (a pin prick), or some other transient sensory modality. Following each stimulus, a transient EEG response is added to the ongoing EEG activity. Very often this evoked response cannot be seen on a monitor with the naked eye. Because the pass band of the evoked response is the same as the interfering or masking EEG activity, linear filtering does not help in extracting transient response. Thus, signal averaging must be used to bring forth the desired evoked transient from the unrelated, accompanying
© 2004 by CRC Press LLC