- •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
11
Modulation and Demodulation
of Biomedical Signals
11.1 Introduction
In general, modulation is a process by which a dc or low-frequency signal of interest is combined nonlinearly with a high-frequency carrier wave to form a modulated carrier suitable for transmission to a receiver/demodulator where the signal is recovered. Modulators and demodulators form essential components of most communication and data transmission systems. Some modulation schemes involve multiplication of the carrier with a function of the modulating signal.
In biomedical engineering, recorded physiological signals are modulated because modulation permits robust transmission by wire or coaxial cable, fiber optic cable, or radio (telemetry by electromagnetic waves) from the recording site to the site where the signal will be demodulated, processed, and stored. As an example, in biotelemetry, physiological signals such as the ECG and blood pressure modulate a carrier sent as an FM radio signal from an ambulance to a remote receiver (in a hospital ER) where the signals are demodulated, interpreted, filtered, digitized, and stored. Five major forms of modulation involve altering a high-frequency sinusoidal carrier wave:
(1) amplitude modulation (AM); (2) single-sideband AM (SSBAM); (3) frequency modulation (FM); (4) phase modulation (PhM); and (5) double-side- band, suppressed-carrier modulation (DSBSCM).
Modulation can also be done using a square wave (or TTL) carrier and can involve FM, NBFM, and PhM. Delta modulation, pulse-position modulation (PPM), and pulse-width modulation (PWM) at constant frequency are done with digital carrier. AM, FM, and DSBSCM are expressed mathematically below for a sinusoidal carrier. vm(t) is the actual physiological signal. The maximum frequency of vm(t) must be ωc, the carrier frequency. The normalized modulating signal, m(t), is defined by the following equation:
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m(t) = |
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Normalized modulating signal |
(11.1A) |
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vmmax |
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ym (t) = A[1+ m(t)]cos(ωct) |
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ym (t) = A m(t)cos(ωct) |
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ym (t) = A cos[ωc t + Kpm(t)] |
PhM |
(11.1E) |
11.2Modulation of a Sinusoidal Carrier Viewed in the Frequency Domain
It is interesting to examine the frequency spectrums of the modulated signals.
For illustrative purposes, let the modulating signal be a pure cosine wave, vm(t) = mo cos(ωm t), 0 < mo ≤ 1. Thus, by using Equation 11.1B and a trig.
identity, the amplitude modulated (AM) signal can be rewritten:
y |
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(t) = A cos(ω |
t)+ (A m |
2) cos((ω |
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+ ω |
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− ω |
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(11.2) |
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Thus, the AM signal has a carrier component and two sidebands, each spaced by the amount of the modulating frequency above and below the carrier frequency. In SSBAM, a sharp cut-off filter is used to eliminate the upper or the lower sideband; the information in both sidebands is redundant, so removing one means less bandwidth is required to transmit the SSBAM signal. SSBAM signals are more noise resistant than conventional AM because they require less bandwidth to transmit the same m(t).
FM and PhM are subsets of angle modulation. FM can be further classified as broadband (BBFM) or narrowband FM (NBFM). In BBFM, Kf ∫ 2πfd, where
fd is called the frequency deviation constant. In NBFM, fd/fmmax 1 fmmax is the highest expected frequency in vm(t), which is bandwidth-limited. Unlike
AM, the frequency spectrum of an FM carrier is tedious to derive. Using m(t) = mo cos(ωm t), the FM carrier can be written as:
ym |
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(t) = A cos ωct+ (Kf |
ωm )mo sin(ωmt)˙ |
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© 2004 by CRC Press LLC
Modulation and Demodulation of Biomedical Signals |
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Using the trigonometric identity cos(α + β) = cos(α)cos(β) − sin(α)sin(β), Equation 11.3 can be written as:
ym (t) = A cos(ωct)cos[(Kf ωm )m0 sin(ωmt)]
(11.4)
− A sin(ωct)sin[(Kf ωm )m0 sin(ωmt)]
Now the cos[(Kf/ωm)mo sin(ωm t)] and sin[(Kf /ωm)mo sin(ωm t)] terms can be expressed as two Fourier series whose coefficients are ordinary Bessel
functions of the first kind and argument β (Clarke and Hess, 1971); note that
β ∫ mo 2πfd/ωm:
cos[βsin(ωmt)]= J0 (β) |
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+ 2 J2n (β)cos(2nωmt) |
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n=1 |
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sin βsin |
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n= 0
The two Bessel sum relations for cos[β sin(ωmt)] and sin[β sin(ωm t)] can be recombined with Equation 11.4 using the trigonometric identities cos(x) cos(y) = ½[cos(x + y) + cos(x − y)] and sin(x) sin(y) = ½[cos(x − y) − cos(x + y)], and one can finally write for the FM carrier spectrum, letting mo = 1:
ym (t) = A{J0 (β)cos(ωct)+ J1(β)[cos((ωc + ωm )t)− cos((ωc − ωm )t)]
+ J2 (β)[cos((ωc |
+ 2ωm )t)+ cos((ωc |
− 2ωm )t)] |
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+ J3 (β)[cos((ωc |
+ 3ωm )t)+ cos((ωc |
− 3ωm )t)] |
(11.6) |
+J4 (β)[cos((ωc + 4ωm )t)+ cos((ωc − 4ωm )t)]
+J5 (β)[cos((ωc + 5ωm )t)+ cos((ωc − 5ωm )t)]+≡}
At first inspection, this result appears quite messy. However, it is evident that the numerical values of the Bessel terms tend to zero as n becomes large. For example, let β = 2πfd/ωm = 1; then J0(1) = 0.7852; J1(1) = 0.4401; J2(1) = 0.1149; J3(1) = 0.01956; J4(1) = 0.002477; J5(1) = 0.0002498; J6(1) = 0.00002094; etc. Bessel constants Jn(1) for n ≥ 4 contribute less than 1% each to the ym(t) spectrum, so they can be neglected. Thus, the practical bandwidth of the FM carrier, ym(t), for β = 1 is ±3ωm around the carrier frequency, ωc. In general, as β increases, so does the effective bandwidth of the FM ym(t). For example,
© 2004 by CRC Press LLC