BRIAN HUMPHREY AARON SEITZ BRENDAN LONG SHAYAN DARAYAN EE 464K SPRING 2010 Final Presentation...
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Transcript of BRIAN HUMPHREY AARON SEITZ BRENDAN LONG SHAYAN DARAYAN EE 464K SPRING 2010 Final Presentation...
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BRIA N HUM P HREYA A RON SEIT Z
BRENDA N LONGSHAYA N DA RAYA N
EE 464KSP RIN G 2010
Final PresentationElectrical Impedance
Tomography
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Outline
Design Problem StatementDesign Problem SolutionTest and EvaluationTime and Cost ConsiderationsSafety and Ethical Aspects of Design
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Introduction
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Introduction
Electrical Impedance Tomography (EIT): A method of visualizing an object’s internal electrical properties by analyzing the surface responses to electrical stimuli.
Figure 1: (Left) EIT Phantom under test; (Right) Reconstructed Image
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EIT –Possible applications
Medical Imaging Real-time (breathing/heartbeat monitoring) High precision (embolism detection, cancer detection)
Industrial Flow rate through a pipe Detecting obstructions in a pipe Detecting oil Non-destructive strain testing of materials
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Design Problem Statement
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Design Goals and Motivation
Goals Create a low cost, user friendly,
portable EIT System Capable of internal human
imaging Motivation
Current EIT systems are large, power hungry, and stationary, much like CT
System involves no expensive hardware
If system could be made portable and low cost, would open up safe internal imaging diagnosis for local clinics around the world
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Our Approach
No replication of measurement hardware Switch signals with cheaper
analog muxes to reduce costUse high accuracy specific
function chips for waveform measurement More accuracy where needed,
lower power than using a high clock rate microcontroller
Software used to correct errors Take into account noise in system
and accurate model of system
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Design Requirements
System Specifications Safe injected signal Maximum reconstruction latency
of 1 s Total component cost< $50 Low noise
Reconstruction Quality Minimum explicit feature size of
5mm Smaller detectable feature size Relative scale Reduce effect of noise and
artifacts
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Theoretical Problem
An inverse matrix problem
Similar to Ohm’s law
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Theoretical Problem
The finite element model
Figure 2: FEM element mesh
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Design Problem Solution
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Design Problem Solution
To construct a simple and affordable EIT measurement device that is based on a PC computer, commercial data acquisition board and software, and an external current generation and switching board
Figure 3: EIT measurement system
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Design Problem Solution
Figure 4: Block diagram overview of our system
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Design Problem Solution
Figure 5: Block diagram overview of our system
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Design Problem Solution
Figure 6: Actual overview of our system
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Design Problem Solution
Figure 7: Power supply hub
15V to -15V inverter
15V to 5V regulator
15V input
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Design Problem Solution
Figure X: Signaling circuitry
1. Sinusoid generation
2. Amplitude adjustment
4. V to I
8. BPF Filter
7. INA
5. I to demux
6. V from mux
9. To gain detector
3. BPF Filter
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Design Problem Solution
Figure 9: ICL4038 schematic
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Design Problem Solution
Figure X: Signaling circuitry
1. Sinusoid generation
2. Amplitude adjustment
3. BPF Filter
4. V to I
8. BPF Filter
7. INA
5. I to demux
6. V from mux
9. To gain detector
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Design Problem Solution
Figure 11: Fourth-order BPF filter
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Design Problem Solution
Figure X: Signaling circuitry
1. Sinusoid generation
2. Amplitude adjustment
3. BPF Filter8. BPF Filter
7. INA
5. I to demux
6. V from mux
9. To gain detector
4. V to I
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Design Problem Solution
Figure X: Howland current pump
VARIABLE LOAD
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Design Problem Solution
Figure X: Analog switching elements
3. I input and V output
2. V and I control signals
1. Enable switches
4. I output and V input
to/from prototype
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Design Problem Solution
Figure 13: (Left) Analog switch pin out; (Right) Analog switch layout
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Design Problem Solution
Figure 14: Tank prototype
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Design Problem Solution
Figure X: Signaling circuitry
1. Sinusoid generation
2. Amplitude adjustment
3. BPF Filter
4. V to I
8. BPF Filter
7. INA
5. I to demux
6. V from mux
9. To gain detector
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Design Problem Solution
Figure 17: INA schematic
PASSIVE HPF
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Design Problem Solution
Figure 18: Gain measurement circuitry
1. Sinusoid voltage input
2. Full-wave rectifier
3. LPF filter
4. Voltage regulator
5. To ADC
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Design Problem Solution
Figure 19: Gain measurement schematic
Full-wave rectifier
LPF filter
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COMPUTER SOFTWARE
Design Problem Solution
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Embedded Software tasks
Coordinate switching signals to route hardware to electrodes. Interrogate the tank according to a known stimulation
pattern No unnecessary replication of hardware
Sample the voltages resulting from the injected current
Relay data back to PC for reconstruction
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Design Problem Solution
Embedded Controller: ARM Cortex M-3Similar in capability to the MC9S12DP512
used in EE319kBenefits of Cortex M-3:
Better Development environment Faster processing On-board LCD and buttons Blue Used in current class (code reuse)
Figure 20: ARM microcontroller
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Overview
Microcontroller InterfaceUser Interface
Use in debugging and for presentation
Backend C# Structure Separation of tasks
Matlab Computation Initialization Scripts EIDORS computation algorithm
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MicrocontrollerInterface
Stream commands Used to set stimulation pattern Reduces communication latency
Calibration routine Take 5 data sets Throw out min and max Average remaining 3 for
calibration Compensates for noise in the
hardware and impedance of medium
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GraphicalInterface
Debugging Interface
Raw data displayed
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GraphicalInterface
Final Interface
2304 elements on gridConductivity legendNo raw data output
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ReconstructionMethod
Initialize an instance of the EIDORS engine
Load in calibration data Can re-calibrate at any point
EIDORS Configuration Circular tank, 16 point electrodes,
2304 elements enclosed Adjacent stimulation pattern at 70 uA
Solved using method by Adler & Guardo, 1996 Takes into account noise variance of
measurements in the system Covariance of conductivity
distribution Fast reconstruction
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ReconstructionMethod
Receive back matrix 64 x 64 matrix, mapped onto 512 x
512 bitmap 4096 total elements, but only 2304
nonzero as a filled circle in the middle
Values in matrix map to colors in a 256-color heatmap scale
Parse into an image Uses direct bitmap data access Scales the image up 64x by
mapping one matrix value to and 8x8 block
>100x faster than using .NET supported SetPixel method
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Test and Evaluation
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Test and Evaluation
Figure 21: Power supply hub
15V to -15V inverter
15V to 5V regulator
15V input
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Test and Evaluation
Figure 22: Oscilloscope view of +15V supply
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Test and Evaluation
Figure 23: Oscilloscope view of -15V supply
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Test and Evaluation
Figure 24: Oscilloscope view of +5V supply
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Test and Evaluation
Figure X: Signaling circuitry
1. Sinusoid generation
2. Amplitude adjustment
8. BPF Filter
7. INA
5. I to demux
6. V from mux
9. To gain detector
4. V to I
3. BPF Filter
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Test and Evaluation
Figure 26: Oscilloscope view of ICL4038 sine wave
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Test and Evaluation
Figure 27: Oscilloscope view of filtered wave
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Test and Evaluation
Figure 28: Oscilloscope view of current output
RVI pkpkpkpk / kI pkpk 43/48.4
uAI pkpk 19.104
%19.4errorI
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Test and Evaluation
Figure X: Signaling circuitry
1. Sinusoid generation
2. Amplitude adjustment
3. BPF Filter
4. V to I
8. BPF Filter
7. INA
5. I to demux
6. V from mux
9. To gain detector
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Test and Evaluation
Figure 30: Analog switching elements
3. I input and V output
2. V and I control signals
1. Enable switches
4. I output and V input
to/from prototype
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Test and Evaluation
Figure 31: Oscilloscope view without and with analog switching elements
VV pkpkloss 76.18.1
VV pkpkloss 04.0
Attenuation = 2.2%
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Test and Evaluation
Figure 32: Tank prototype
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Test and Evaluation
Figure 33: Comparison of electrode resistance values
Ravg = 0.4 Ω
Rmax = 0.6 ΩRmin = 0.2 Ω
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Test and Evaluation
Video 1: Tank prototype voltage with insulator and conductor
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Test and Evaluation
Video 2: Tank prototype current with insulator and conductor
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Test and Evaluation
Figure 34: Gain measurement circuitry
1. Sinusoid voltage input
2. Full-wave rectifier
3. LPF filter
4. Voltage regulator
5. To ADC
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Test and Evaluation
Figure 35: Oscilloscope view of full-wave rectifier and DC LPF
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Test and Evaluation
1: sample the ADC 512 times. Transmit to PC.
2: transmit a known data set to PC. Verify correct reconstruction.
3: print out stimulation pattern order
4: Verify stimulation pattern control codes with logic analyzer.
5: measure time for full data set under continuous measurement
Figure 36: ARM microcontroller
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Test and Evaluation
Figure 37: ARM microcontroller
A command line interpreter helped debug the embedded system.
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Test and Evaluation
Qualitative evaluation of different EIDORS reconstruction methods
Continuous reconstruction with simulated data set for optimization of reconstruction method
Continuous reconstruction with microcontroller to test overall serial reconstruction speed
Failure testing to catch most common errors with plain explanation
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Test and Evaluation
Figure 3: Video of software speed
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ReconstructionProblem
Individual data sets are completely independent
Serial bottleneck in the data set collection by the microcontroller
Time required Data set collection ~ 100 ms Reconstruction ~ 66 ms Communication/Display ~ 34 ms
Total time required – 200 ms 5 Frames/sec
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Time and Cost Considerations
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Time and Cost Considerations
System shown operational by deadline Time lost for total system testing & optimization
Switching circuitry required extended evaluation Switching circuitry also required multiple part orders Waveform sampling required extended evaluation and
testing Some difficulties interfacing some modules
Estimated total delay 2 working weeks
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Time and Cost Considerations
System slightly over cost expectations Points of overrun
Switching circuitry required multiple, large part orders Should have been ordered in smaller, testing quantities
Testing and optimization required better op amps Several chip types ordered for evaluation
Waveform sampling design modified 3 times Several chips ordered for evaluation
Estimated total cost overrun $ 105.44
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Time and Cost Considerations
Table 1: Final system cost breakdown
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Safety and Ethical Aspects of Design
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Safety and Ethical Aspects of Design
Safety EIT is intended as a medical device
Our prototype was built to demonstrate principles of design Not used on a person, but proved safe operation
• Signal current = 100uA across varying load• Signal voltage < 10V Peak-to-Peak• Operation at fixed 15V DC voltage
Not fully implemented as medical imaging device. Images not precise enough to detect small blood clots
(smallest feature size is about Lag time too slow to watch heart beat.
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Safety and Ethical Aspects of Design
Ethics EIT is intended as a medical device
Prototype clearly shows safe operation System provided with concrete operational specifications
Testing ensures system meets specified quality Optimization ensures system falls within acceptable
tolerances Specific information so user can make accurate conclusions
Only environmental concern is for batteries and electronics Rechargeable pack would be utilized Electrical/battery waste can be conveniently disposed of
Helps bring advanced medical imaging to more people Can be deployed far from major hospitals Safer than other technologies, such as X-rays
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Recommendations
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Recommendations
Proposed major hardware changes Use a DSP
Faster sampling and waveform generation Precise filtering Multi-frequency waveforms
Better ADC Faster and more precision
Increase electrode count to 64 electrodes and implement 3D EIT
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Recommendations
What we would do differently? Plan for higher circuit voltage (30V Dual Supply) Use more electrodes from the beginning
Where would we go from here? Testing Apparatus: Smaller electrodes, More electrodes Switching: Faster ICs, PCB EMI concerns, TriState
protection Waveform Capture: Multiple ADCs or faster ADCs Waveform Gen/V-I: Better op amps
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ReconstructionPipelining
GUI
GUISync
.
uCSync
.
Work Thread 1
WorkThread 2
Hardware
Data Set Request
Images
Start
Start
Matrix Matrix
Data Set Data Set
Data SetRequest
Start
Command Data Set
Example Pipeline forDual Core Processor
- Busy/Wait Thread
- Processing Thread
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PipeliningResults
Reduces time to maximum time of any operation By speeding up dataset collection,
we could speed up frame rateReconstruction also speeds up
with clock rateRequires a multi-core processor
capable of matching the frame rate of the microcontroller ie. If the microcontroller supplies
frames at 4/sec, processor needs 1 core running a frame every 250 ms, a 2 core running a frame every 500 ms, etc.
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Delocalized Computation
Small data sets and small responses
Can be sent off to a central server for processing and send back picture with little increase in time
Can send over MMS using capable cell phone
Cell phone collects dataset from microcontroller, sends off, gets back picture.
No computer cost for reconstruction
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Conclusion
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Conclusion
Our concept was for a portable EIT deviceOur problem solution:
Inexpensive, simple solution Small, portable device capable of powering by battery
Our design concept prototype completed on time Some budget overrun incurred during testing Prototype illustrated feasibility of design Prototype illustrated safety of design for human use
Identified several improvements for the design
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Questions?