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Electronic Measurements in Biomedical Engineering Biomedical Measurements in Embedded Applications Enderle, Blanchard, Bronzino, Introduction to Biomedical Engineering, Elsevier (2005). Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 1 Electronic Measurement Systems Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 2 Dr. Martin Land 4 Physiological Measurements Analog domain systems Sensor (transducer) Mechanical General physical measurement Examples Physiological property of tissue → electrical signals Amplifier Length, weight, pressure, temperature, motion Sensor output → input requirements of measuring system Analog filter Electrical / chemical Contact with tissue → electrical signal Examples Amplifier output → information of interest Analog to digital converter (A/D) Signal → binary coded sample sequence EKG, EEG, blood glucose Digital domain systems Imaging Stimulate tissue — pressure, sound, electromagnetic waves Detect induced emissions Examples Microcontroller Process automation: measurement → display process Digital signal processing (DSP) Digital domain filtering Storage Ultrasound, X-ray, infrared, MRI Interface → information systems Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 3 Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Electromagnetism Electric Circuit Concepts Force on charged particle Functions of time F = q[E + u × B ] , charge q, electric field E, magnetic field B , velocity u Measured from ground v1 = v1G , v2 = v2G Voltage (potential) Measure of work performed against electric force F A Pushing current → perform work → loss of voltage B Voltage source Reference point for measuring voltage Power supply = source of energy for work = – drop vB = voltage from ground to point B Kirchhoff laws (graph theory) Current Sum of currents entering any node = 0 Measure of motion of charged particles i1 – i2 – i3 = 0 i = total charge crossing unit area per second Sum of voltage drops around any loop = 0 Analogous to flow in a water pipe Embedded Systems — Hadassah College — Spring 2012 – v1 + vdrop + v2 = 0 Biomedical Applications Dr. Martin Land 5 Electrical Circuit Elements Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 6 Frequency Domain Analysis Conductor Carries current with voltage drop → 0 Resistor General circuit Ordinary differential equations with respect to time i1 Example Inductor LA and resistor RB Current i(t) causes voltage drop v(t) = R × i(t) Resistance R i1 = i2 = i i1 Capacitor i2 v1 = v A + vB = L A vA Current i = C × dv / dt Capacitance C v1 v1 ∞ v ( t ) = ∫ V ( ω ) e jωtdt ⇔ V ( ω ) = Voltage drop v = L × di / dt ∞ i ( t ) = ∫ I( ω ) e jωtdt ⇔ I( ω ) = −∞ Inductance L v1 ( t ) = L A Example — resistor elements RA and RB i1 = i2 = i v1 RB v RB v1 = v A + vB = iRA + iRB ⇒ i = ⇒ vB = iRB = v1 ⇒ B = RA + RB RA + RB v1 RA + RB Dr. Martin Land vB di + iRB dt −∞ Biomedical Applications i2 vA Fourier transform vB Inductor Embedded Systems — Hadassah College — Spring 2012 i3 Voltage drop Force F Ground v1 i2 v2 Current i(t) vAB = work required to push unit charge (q = 1) from A to B Analogous to pressure in a water pipe vdrop i1 Voltage v(t) VB ( ω ) = 7 1 ∞ v ( t ) e‐jωtdω 2π ∫−∞ 1 ∞ i ( t ) e‐jωtdω ∫ −∞ 2π di + iRB → V1 ( ω ) = jωI( ω ) L A + I( ω ) RB dt RB V1 ( ω ) RB + jω Embedded Systems — Hadassah College — Spring 2012 ⇒ VB ( ω ) V1 ( ω ) = Biomedical Applications ω 2π frequency f = ⇒ I( ω ) = V1 ( ω ) RB + jωL A RB R + ω2L2A 2 B Dr. Martin Land 8 Frequency and Analog Filters Amplifiers Low pass filter H( ω ) = Transfer function VB ( ω ) V1 ( ω ) RB = R +ω L 2 B 2 2 A 1 = 1+ Higher frequency ω ⇒ lower transfer R ω0 = B LA , 2 ω ω20 v out = A ( v + − v − ) iin = Simplified model High pass filter A, Rin → ∞ ⇒ v + − v − = Resistor RA and inductor LB Transfer function Operational amplifier (op amp) Analog integrated circuit Differential amplifier H( ω ) = VB ( ω ) V1 ( ω ) = ωLB R +ω L 2 A 2 2 B = ω ω +ω 2 0 2 , ω0 = H( ω ) = Resistor R, inductor L, and capacitor C ω = ω0 ⇒ highest transfer ⎛ ω2 ⎞ ω + ω ⎜1 − 2 ⎟ ⎝ ω0 ⎠ 2 Biomedical Applications 2 2 1 R2 R1 Dr. Martin Land 9 Analog to Digital Conversion — Sampling v- v R2 R v in ⇒ out = − 2 R1 vin R1 Embedded Systems — Hadassah College — Spring 2012 v+ i1 vin v out = i2R2 = −i1R2 = − vout - v out v − v− ⎯⎯⎯ → 0, iin = + ⎯⎯⎯ →0 A →∞ Rin →∞ A Rin v i1 = in R1 ω + v+ − v− Rin iin → 0 ⇒ i1 + i2 = 0 ⇒ i2 = −i1 Band pass filter iin v- Feedback amplifier v + − v − → 0 ⇒ v + = 0 RA LB Higher frequency ω ⇒ higher transfer Embedded Systems — Hadassah College — Spring 2012 v+ i2 + vout Set R1 and R2 to any convenient values for arbitrary amplification Biomedical Applications Dr. Martin Land 10 Convert Samples to Digital Form Nyquist Theorem Rounding-off n-bit integer codes 2n levels Round-off samples to n-bit integer Filter data signal to bandwidth fmax Sample data signal at sample rate fsample ≥ 2 × fmax Distorts data Equivalent to added noise Reproduce data signal from samples without distortion 161 Larger n ⇒ more levels ⇒ higher resolution ⇒ less noise data signal d(t) 160 159 158 157 Sequence of sample values rounding 158 159 160 160 159 159 t sampling signal S(t) Example t sampled signal S(t)d(t) Sampled values 158.276 158.879 159.724 159.821 159.312 158.791 Rounded values 158 159 160 159 159 159 t Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 11 Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 12 Sampling for Standard Telephony Sampling for Standard CD Audio Telephone line Filter audio frequencies 300 Hz to 3300 Hz CD audio Filter audio frequencies 20 Hz to 22,000 Hz Sample voice channel Sample voice channel fsample = 8000 samples / second > 2 × 3300 Hz fsample = 44,100 samples / second > 2 × 22,000 Hz 161 160 Round-off samples Scale = 28 = 256 levels (0 to 255) Each sample encoded as 8-bit byte 159 Round-off samples Scale = 216 = 65,536 levels (0 to 65,535) Each sample encoded as 16-bit word 158 157 158 160 160 159 159 159 161 160 159 158 157 158 DS-0 voice channel 8000 samples/second × 8 bits/sample = 64 kbps 10011110 158 10011111 159 Embedded Systems — Hadassah College — Spring 2012 10100000 160 10100000 160 10011111 159 160 160 159 159 CD audio channel 44,100 samples/second × 16 bits/sample = 705,600 bps MP3 encoding → 5 times compression rate 705,600 bps / 5 ~ 140 kbps ~ 17,508 bytes / sec ~ 1 MB / minute 10011111 159 Biomedical Applications Dr. Martin Land 13 Biomedical Sensors Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 14 Dr. Martin Land 16 Electrochemical concepts Classification by interaction type Interaction → analog electrical signal (voltage / current) Ion Atom / molecule with electrons ≠ protons Cation Physical / electrical / optical / chemical Biosensor Electrons < protons ⇒ net + charge Biological element — enzyme / antibody / receptor Biochemical reaction → optical / electrical / physical signal Anion Electrons > protons ⇒ net – charge Packaging Safe — biocompatibility Reliable — long operational lifetime Isolate sensor from body Metal Material containing free electrons ⇒ electrical conductor Electrolyte Material containing free ions ⇒ electrical conductor Typically ions in solution Polymer (plastic) covering / barrier layers Host body affects sensor function Sensor affects implantation site Ionization current Environmental factors Interactions affected by temperature / pressure / noise ... Biomedical Applications + - electrons - Primary reference: Yitzhak Mendelson, "Biomedical Sensors," chapter 9 in Enderle, Blanchard, Bronzino, Introduction to Biomedical Engineering, Elsevier (2005). Embedded Systems — Hadassah College — Spring 2012 159 Dr. Martin Land 15 Embedded Systems — Hadassah College — Spring 2012 - electrolyte Biomedical Applications + + cations + + Half‐Cell Potential Common Electrode Types Metal / electrolyte interface Electrons flow to / from metal Charge distribution near surface Voltage between metal and electrolyte — half-cell potential Battery (cell) 2 half-cells with different metals Electrons flow from metal 1 ⇒ net + Electrons flow into metal 2 ⇒ net – Biopotential electrodes Electrolyte = host tissue 2 half-cells with same metal Electrocardiogram (ECG) electrodes Common electrode — flexible polymer + carbon / metal powder Pre-pasted electrolyte gel for application to skin Electromyographic (EMG) electrodes Sense signals from muscles Surface EMG recording 1 cm circular discs of silver / platinum Direct recording Percutaneous (skin puncture) needle electrodes Electroencephalographic (EEG) electrodes Sense signals from brain Cup electrodes Equal half-cell potentials (ideal model) ⇒ half-cell potentials cancel 5 – 10mm discs of platinum / tin with conducting gel attached to scalp Example Subdermal Two similar electrodes taped to chest near heart Measure electrical potentials generated by heart Differential amplifier → electrocardiogram (ECG = EKG) signals Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Platinum / stainless-steel needle electrodes 10mm long by 0.5mm wide Dr. Martin Land 17 Magnetism Biomedical Applications Dr. Martin Land 18 Electromagnetic Effects Magnetic field Induced by accelerating charge Example — electron in stable orbit around nucleus N Electromagnet Electric current in wire coil (winding) → magnetic field Field configuration + S Identical to permanent bar magnet Many atoms with electrons in stable parallel orbits Compass aligns with earth's magnetic field Earth's North Pole is a magnetic S Mechanical forces Opposite poles (N ↔ S) attract Like poles (N ↔ N / S ↔ S) repel S N S N S N N S S N N S N S S N S F = q (u × B ) y z http://hyperphysics.phy‐astr.gsu.edu/hbase/magnetic/elemag.html Biomedical Applications N Current level + direction → field strength + polarity Induction Varying magnetic field → varying current in conductor Mutual induction Varying current in coil → magnetic field → current in second coil Hall effect Current in magnetic field Charges spread to edges of conductor → induced voltage VHall Permanent ferromagnet Metal (typically iron) with permanent magnetic field Embedded Systems — Hadassah College — Spring 2012 Embedded Systems — Hadassah College — Spring 2012 Dr. Martin Land 19 Embedded Systems — Hadassah College — Spring 2012 u along x B along z x F along y + + + + charge separation u - - - Biomedical Applications induced voltage Dr. Martin Land 20 Physical Measurements — 1 Physical Measurements — 2 Linear Variable Differential Transformer (LVDT) Mutual induction effect L = displacement of core from exact center Secondary voltage VS = kgeometry × VP × L VS VP Precise measure of position Elastic resistive transducer Thin elastic tube containing conductor Electrical resistance depends on length Breathing → expanding chest → higher resistance → voltage change Strain gauge Similar to elastic resistive transducer Stress (force) → strain (change in size) → higher resistance Smaller range of expansion Electromagnetic flow transducer Magnetic field surrounds blood vessel Hall effect → electrolytes separate to walls Transverse voltage measures blood flow Bonded Single thin wire in flexible frame Unbonded Multiple thin wires in two-part frame Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 21 Variable Capacitance Biomedical Applications Dr. Martin Land 22 Pressure Transducers Capacitor Parallel metal plates A = area of plate D = distance between plates Apply voltage → separate charges Capacitance = charge stored per volt q = C×V cations + + + + + Piezoresistance effect Pressure on crystal → contraction → higher resistance Used in portable blood pressure monitors - electrons insulator - Piezoelectric effect Voltage on crystal → contraction Pressure on crystal → contraction → voltage Sensitive to short mechanical pulses Used in sensitive cardiac monitors voltage C = constant × A × D Capacitor current dq dV dC i= =C +V dt dt dt Measure small changes in displacement Ultra-sound Apply high frequency (1 to 10 MHz) voltage to crystal Crystal vibrates at voltage frequency → pressure wave → ultra-sound Varying D with constant V dD i = constant × V × A × dt Embedded Systems — Hadassah College — Spring 2012 Embedded Systems — Hadassah College — Spring 2012 Apply ultra-sound to crystal Pressure wave → crystal vibrates → voltage at ultra-sound frequency Biomedical Applications Dr. Martin Land 23 Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 24 Temperature Measurement Blood Pressure Set High Level Design Contact thermometer Measure body temperature in direct contact with skin Thermistor cuff Metallic mixtures change resistance with temperature T controller display switches air pump air hose ⎡ ⎛ 1 1 ⎞⎤ R = R0exp ⎢β ⎜ − ⎟ ⎥ ⎣ ⎝ T T0 ⎠ ⎦ air hose connector Noncontact thermometer Measure temperature of ear canal near tympanic membrane Infrared (IR) radiation guided to sensor Thermopile sensor cuff air hose motor control pump Two metal plates in contact Heated plates → voltage depending on temperature Used in standard thermostat Pyroelectric sensor pressure sensor Heated crystal → voltage depending on temperature Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications LCD display LCD control switches digital input amplifier filter A/D microcontroller Dr. Martin Land 25 Blood Pressure Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 26 Sphygmomanometer Pressure Force per unit area Measured as mmHg vacuum weight of Hg External pressure balances weight of Hg in column air pressure Pulse Heart muscle contracts Internal surface area decreases ⇒ pressure increases Cuff Pump air into cuff Pressure measured in gauge Pressure on artery → restrict blood flow Blood flow Unrestricted artery Laminar (smooth) flow → silent Restricted (occluded) artery Systolic pressure Turbulent flow → BP oscillations → Korotkoff sounds Maximum BP at peak contraction Normal range: 90 – 120 mmHg Diastolic pressure Minimum BP at minimum contraction Normal range: 60 – 79 mmHg L. A. Geddes, Handbook of Blood Pressure Measurement Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 27 Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 28 BP Measurement with Sphygmomanometer BP Measurement in Digital Test Set Inflate cuff on upper arm Pump cuff to 160 – 200 mmHg Brachial artery occluded → no flow → silent Oscillometric method Filter + amplify oscillations Cuff inflation Cuff deflation Pressure in cuff Gradually deflate cuff Listen to pulse with stethoscope Systolic BP Onset of Korotkoff sounds Maximum contraction BP > cuff pressure High pass filter (at 1 Hz) SBP / DBP criteria determined by comparison with clinical data Korotkoff sounds Minimum contraction BP < cuff pressure < maximum contraction BP Diastolic BP Silent flow ⇒ minimum contraction BP > cuff pressure Amplify Chua and Hin, Digital Blood Pressure Meter, Freescale Semiconductor Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 29 Embedded Systems — Hadassah College — Spring 2012 Biomedical Applications Dr. Martin Land 30