Download The most common and widely used sobriety

Final Report
April 29, 2004
Executive Summary
Driving under the influence (DUI) of alcohol was responsible for 41% of all
fatalities in motor vehicle crashes in 2001 [1]. Although over the past 15 years the
number of deaths because of DUI are reducing, it is still a major hazard on roads today.
Breathalyzers are used by the police to measure the Blood Alcohol Content (BAC) to
check for sobriety in drivers. However, BAC does not assure sobriety rather it is just an
indication of the alcohol present in the blood which could be present as a by product of
certain medicines or medical conditions. For instance, diabetics produce alcohol and
ketones as by-products when breaking down simple sugars and so will have a small
amount of alcohol present in their blood anyway.
We present a diagnostic device that uses Horizontal Gaze Nystagmus (HGN) to
test the sobriety of an individual rather than determine the BAC. This way not only can
the test be used to check for the influence of other non-alcoholic narcotics but can also be
an indicator of how much a person is intoxicated. It can be used in conjunction with the
breathalyzer test to develop a more accurate assessment of intoxication or sobriety in
subjects.
This sobriety tester uses a linear photodiode array to track the movement of the
eyeballs and then uses this data to verify if the individual is intoxicated. The following
steps provide a brief synopsis of the working of our design:
§ The subject is asked to visually track a horizontally moving stimulus while
looking into a lens setup connected to a linear array of 128 photodiodes.
§ These diodes capture the movement of the eyeball and send out a continuous
analog signal.
§ Transistor-to-Transistor Logic (TTL) and analog circuitry is used to simplify and
digitize the analog signal.
§ This digital signal is then transferred to the computer where a Digital Signal
Processing program is used to calculate the position of the eyeball.
In the following report we present the final design, design tradeoffs and alternatives and
technical details with an in-depth analysis of the marketing and the economic viability of
this device. We finish the report with a section devoted to assist the next group in
carrying this project forward since some work is still needed before our product is ready
for the market.
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Table of Contents
Introduction………………………………….…………………………………………….4
Design Alternative and Tradeoffs…………………………………………………………5
Marketing & Cost Analysis…………….…………………………………………………6
Project Technical Details………….………………………………………………………9
Tasks & Schedule…………………….………………………………………………….13
Product Demonstration..……….………………………………………………………...17
Conclusions…………………….………………………………………………………...17
Continuation……………………………………………………………………………...18
Bibliography……………………………………………………………………………..20
Appendix A: MATLAB Code for DSP and Visual C++ code for Parallel Port
Communication ………………………………….………………………21
Appendix B: Schematic of Circuit and Pictures of Final Design ……………………….24
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Introduction
According to the Center for Disease and Control (CDC), 33% of the American
population will be involved in an alcohol related fatality. During 2002, 41% of all trafficrelated deaths in the United States died in alcohol-related motor vehicle crashes at a cost
of over $50 billion [2]. The largest groups at risk are male drivers between the ages of 15
through 24. Most of these drivers had a blood alcohol concentration (BAC) well above
the 0.08% legal state limit. Some methods enforced by law officials to prevent “drinking
and driving” (DUI) include license suspension and stricter penalties, and zero tolerance
laws for drivers under the age of 21. The risks of “driving under the influence” of alcohol
is shown in Figure 1.
Figure 1. Risks of accident in relation to the BAC [2].
To combat the serious consequences of driving under the influence, the National
Highway Traffic Safety Administration ("NHTSA") has developed a battery of field
sobriety tests, which are designed to detect the impaired driver [3]. One of the sobriety
tests used by officials in some states is the Horizontal Gaze Nystagmus (HGN) or “eye
test.” The test requires the subject to track a horizontally moving object. When the
subject reaches the horizontal extremes, if they are under the influence of alcohol the
eyes would cause a fluttering or oscillatory motion called nystagmus. However, this is
sometimes a naturally occurring phenomenon in some individuals. One of the major
flaws with this test is it relies on the interpretation of the law enforcer and is therefore
very arbitrary.
The disadvantages of the HGN test will be alleviated by creating a more accepted
quantitative method for law officials. The model will involve a horizontal moving target
on a computer screen and a linear optical array that will track and record the eye
movements. The model is separated into three separate components: an optical
component, an electrical component, and a software component. Each of these after being
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tested separately, will be implemented to test for the nystagmus effect. The data collected
from this analysis will be beneficial for law officials to accurately diagnose if a person is
or is not under the influence of alcohol. However, due to time constraints, there was only
a certain extent of accuracy that was obtained after completing the project due to small
errors in the circuit components, the manual parallel port input and the setup of the
optical device.
Design Alternatives and Tradeoffs
This project is a continuation from a previous semester when a group tried to
detect the Nystagmus effect by using an Electro-Oculogram (EOG) to detect the position
of the eyeball. Although they were successfully able to detect eye movement, their
design was too slow to be able to detect the high frequency movement associated with the
Nystagmus effect. Thus, our first step was to seek an alternative to the design that was
currently being pursued.
We decided to use an optical approach to the problem and detect the presence of
the dark pupil against the white background of the eyeball to determine the eye position.
The device we decided to use to detect the pupil was a linear array of photodiodes. The
photodiodes would have an output voltage depending on the amount of light incident on
it. The output voltages could then be treated in two possible ways:
1. Pass the entire analog signal into a computer using a special card that allows
analog data to be sampled, ported and stored in the computer. The data could
then be analyzed and processed to get the desired information. This would
require a lot of Digital Signal Processing and software development.
2. In this approach the signal would first be processed and cleaned using electrical
components and logic. By cleaning up most of the signal only the information
pertinent to the problem would be kept and would then be sampled into the
computer. This would require extensive analog circuit design and various logic
considerations.
We settled on the second choice because analog circuitry and Transistor-toTransistor Logic (TTL) is our group’s forte. Moreover, as Electrical Engineers we felt
more inclined to do more work with circuitry rather than focus only on high level
programming.
Yet another possible optical approach to this problem would involve using a high
speed camera or even a video camera to capture some footage of the eye. The frames
could then be evaluated to obtain eye movement. This would probably be the most
accurate method but at the same time it will be the most expensive. Such a setup would
have required too much time and money to be a viable option.
Finally, we settled on an optical approach to capture Nystagmus effect. Our
implementation would clean most of the signal using TTL and analog circuitry. By using
counters and TTL output levels we effectively digitized the signal to make signal
processing much easier and almost intuitive. After considering the various alternatives
and tradeoffs we settled not only for an economically viable solution but also for one that
was most appealing to our interests.
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Marketing & Cost Analysis
The most common and widely used sobriety tester today is the breathalyzer. They
are used by the police as well as relied on by people for personal testing. Most consumer
models have typical accuracy levels of ±0.01% at 0.10% BAC. Most models provide an
exact blood alcohol level (BAC) reading to one hundredth of one percent. For most
models, users simply blow through the mouthpiece for 2-4 seconds. The sensors measure
the alcohol level of air in the deep lungs. Testing is most accurate if subjects have not
consumed food or alcohol 15 minutes prior to testing. Different factors like a person's
weight, muscle mass, and recently consumed food or beverages all affect a person's blood
alcohol content (BAC). Just because a person may act or seem sober does not mean that
they are.
Breathalyzers vary in cost with disposable testers such as “BreathScan” costing
$1.95 each to a Phoenix fuel cell sensor breathalyzer that costs as much as $1,945. Please
refer to Table 1 for a price-performance comparison of common consumer and
professional breathalyzers.
Table 1. Price-Performance Comparison of Consumer and Professional Breathalyzers [4]
Breathalyzer
AL-2500
Alcoscan
AlcAlert
AlcoMate
AlcoMate Pro
Lifeloc FC-10
Lifeloc FC-10
Plus
Lifeloc FC-20
CA-5000
Phoenix
Sensor
Semiconductor
type
Semiconductor gas
Semi-conductive
oxide
Semiconductoroxide
Patent pending fuel
cell
Patent pending fuel
cell
Fuel cell
Oxidesemiconductor
Fuel cell
Used By
Personal
Price
$59.95
Personal
Personal, law enforcement
organizations for initial screening
Hospitals, schools, law enforcement
$59.99
$129.95
Law enforcement, corrections,
probations, clinics, schools,
businesses.
DOT/ NHTSA approved.
Check-points, schools, work-release
screening
DOT/NHTSA approved
Bars, restaurants, clubs (coinoperated)
Managers of workplace alcohol testing
programs.
DOT approved.
$539
$139.95
$695
$780
$1,395
$1,945
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Our product is superior to the Breathalyzer test since it indicates the level of
intoxication and not on the BAC, and at the same time we will be able to price it
competitively. The following is the breakdown of the cost of design and development of
our prototype:
Table 2. Cost Assessment for Development of the Prototype [5, 6]
Item
PROTOBOARD ® Bread Board
Toshiba Satellite ® Laptop Computer
(Windows OS)
Texas Instruments ® Hex Inverter
Fairchild Semiconductor ® Comparator
8-Dip
Texas Instruments ® Latch 16-Dip
Texas Instruments ® 8-bit Binary Counter
RadioShack ® T 1-3/4 Red Diffused LED
Lamps
Linear Array
Fresnel Lens
Optical setup (PVC)
Cold mirror
Break out box (for parallel port cable)
TOTAL COST
Model
Number
PB-103
A10-S1291
Unit
Quantity
1
1
Unit
Cost
$35
$900
SN74LS04N
LM311N
1
1
$0.40
$0.48
SN74LS75N
74HC590AN
276-026
2
1
8
$0.92*2
$0.88
$1*8
MLX90255
NT32-684
NT43-960
-
1
1
1
1
1
$120
$52
$20
$27
$33.25
-
-
$1,172.73
The cost of development of our prototype, as seen from Table 2, is very
reasonable as compared to the other professional breathalyzers (see Table 1) that are
thriving well in market now. The fact that we have used very superior equipment to build
our prototype will make our product very accurate while not increasing maintenance
costs significantly. The cost of production will be much lower not only because of the
savings per piece when buying a large quantity but also because we will use a much
simpler and less sophisticated Analog-To-Digital converter and computer. For the
personal handheld device, the Analog-To-Digital converter and computer can be
integrated into one device running of an embedded Microcontroller such as PIC18F452
and displaying the result on an LCD display. This will significantly lower the costs as the
Analog-To-Digital converter and the computer are the two most expensive components in
our prototype.
Since our primary potential marketing targets are the police and the highway
patrol, the functionality of the final device can easily be integrated with the computers
that the police vehicles have onboard. The savings on computer hardware will
significantly lower production costs. With above two changes in the prototype, the
functionality or accuracy does not get affected whatsoever, yet a much cheaper product is
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made. The following table shows the cost of building the device for personal and police
use, with the computer and Analog-To-Digital converter replaced by a microcontroller
and LCD:
Table 3. Cost Assessment of Prototype for Personal and Police Use [5, 6, 7]
Item
Model Number
Microchip Technology ®
Microcontroller
Maxim ® LCD
PROTOBOARD ® Bread
Board
Texas Instruments ® Hex
Inverter
Fairchild Semiconductor ®
Comparator 8-Dip
Texas Instruments ® Latch
16-Dip
Texas Instruments ® 8-bit
Binary Counter
RadioShack ® T 1-3/4 Red
Diffused LED Lamps
Linear Array
Fresnel Lens
Optical setup (PVC)
Cold mirror
TOTAL COST
PIC18F452-I/PT
Unit
Quantity
1
Unit
Cost
$10.7
Cost Per
Hundred
$651
MAX7231BFIPL
PB-103
1
1
$7.88
$35
$525
$3,500
SN74LS04N
1
$0.40
$24
LM311N
1
$0.48
$27
SN74LS75N
2
$0.92*2
$65*2
74HC590AN
1
$0.88
$45.65
276-026
8
$1*8
$100*8
MLX90255
NT32-684
NT43-960
1
1
1
1
$120
$52
$20
$27
$12,000
$5,200
$2,000
$2,700
-
-
$257.98
$24,948.3
Thus with the above cost of production, we can competitively price our product
while offering a better and a cheaper alternative to other professional breathalyzers. The
cost of support required for customers to install and use the final product is essentially
zero. Since the product will be a fresh launch in the market, advertising and marketing
costs will be a bit higher in the first year. Also, some costs will be incurred in getting the
product DOT/ NHTSA approved. While contemplating marketing cost to be 15% of the
production cost, and maintenance cost and other overheads each to be 5% of the
production cost, we are hoping to sell 500 products this year. The following table
provides an annual budget analysis for our company to sell, support, maintain and market
our product.
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Table 4. Annual Budget Analysis for Product
Prototype development cost
Production cost
Maintenance cost at 5%
Marketing cost at 15%
Other overheads at 5%
AVERAGE COST PER UNIT
Entire Expenditure Expenditure Per Unit
$1,172.73
$2.35
$1,24,741.5
$249.48
$6237.08
$12.47
$18,711.23
$37.42
$6237.08
$12.47
$1,57,099.62
$314.19
The above table shows that our overall expenditure per unit will be a meager
$314.19 as compared to our cheapest competitor Lifeloc FC-10 priced at $539.
Considering the worst case scenario, assuming that we will manage to sell only 350
products in this year, we will recover our entire expenditure incurred on the development
of this product, provided the selling price of our product is $450.
In order to develop this lucrative product, the total accumulated number of person
hours required were approximately 200 hours. Four people, Nisha Javia, Narendhra
Seshadri, Brock Wester and Ranit Windlass; each worked for about 3 hours per week for
15 weeks in order to complete this project. About 20 more hours need to be put in to
complete the final assimilation of the electrical, optical and computer components of the
design. Final testing of the device and data collection will follow thereafter.
If the product is finished up as scheduled, then not only will this product offer
police and highway patrol a very accurate way of determining the BAC of an individual,
but will also be a very lucrative business.
Project Technical Details
The DUI quantification device consists of several optical and circuit components
that convert an analog visual input signal to a digital signal that is processed using
computer software. The device is divided into an optical component, a circuit component,
and a computer component.
The optical component of the DUI device is responsible for taking an image of a
moving eye, and converting it from a three dimensional image to a two dimensional
image. The optical component consists of several infrared light emitting diodes as light
sources, a single bi-convex lens, a cylindrical Fresnel lens, and a cold mirror. Each of the
lenses is oriented inside of a long shaft that will block out light interference. Infrared
light emitted from the infrared LEDs will deflect off the eye creating an image that is
passed through the bi-convex lens. This image is then passed through the Fresnel lens,
which effectively sums each of the vertical intensities of light to a single point,
converting the full image into a horizontal line of light. This light is then passed through
the cold mirror, which will pass light in the infrared spectrum, and reflect all else. A
large percentage of the light pollution (which consists mostly of wavelengths outside the
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infrared spectrum) that can enter the shaft from a source other than the eye will
effectively be filtered out by the cold mirror. A diagram of the optical component is
displayed below, showing critical dimensions and relative positions of each of the lenses.
Figure 2. Lens setup.
The circuit component will take the light from the optical setup and convert it into
a digital signal that will be passed through a parallel port to a computer. The input device
to the circuit is a linear optical sensor array, which is an integrated circuit element that
contains an array of light sensitive 200µm by 66µm photodiodes. Each photodiode
outputs a voltage that is directly dependent on the proximal intensity of light. Light
intensity generates photocurrent in each photodiode, which is integrated to provide an
output voltage [8]. The linear array is housed in an evaluation board that has native clock
and integration signals that control the reading of the array of photodiodes. On each
integration signal, the cycle of consecutive reads from each of the photodiodes begins.
On the rising edge of the clock signal, each subsequent photodiode’s voltage is outputted,
making the overall output a series of concatenated photodiode voltages delimited by each
clock signal. In the figure below is an oscilloscope reading of a typical voltage output of
the linear optical array.
Figure 3. Screen capture of the output voltage of the linear array.
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The native clock signal generated by the linear array evaluation board is used to
create new non-overlapping clock signals, which will be used to latch the signaling for
the rest of the circuit. This is accomplished by leading the native clock signal to a monostable multivibrator, or “one shot,” which triggers off the clock edges, creating new clock
signals with duty cycles less than 50%. These will be used in conjunction with the linear
array output to read each individual photodiode signal.
The analog output voltage signal from the linear array leads into a latchable
voltage comparator element which determines if the signal for each photodiode is “light”
or “dark,” effectively digitizing the output. The voltage threshold which separates a light
or dark signal is dependent on the voltage output range, which varies with the lead
voltage supplied to the linear array board. The Output of the comparator circuit chip is
latched so that a read and digitization will occur in the middle of each photodiode output
voltage.
The digitized output of the voltage comparator is run through two latches, which
will temporarily store two consecutive photodiode output readings. These two
consecutive output readings will go into an exclusive-or circuit to determine if the
consecutive signals are different, which would indicate a change across two adjacent
photodiodes from “light” to “dark” or vice versa. These changes from light to dark and
vice versa will set the exclusive-or circuit high, and are used to latch the memory. A
figure showing the behavior of the exclusive-or gate is shown below. Notice how the
firing of this gate minimizes data capture.
Figure 4. Firing of the Exclusive-OR gate
After each of the photodiodes has been read, the values in the stored memory will
begin to paint a picture of the different images present in front of the linear array. The
memory value recorded is simply the number of the diode in the array in which a change
occurred. This number originates from an 8-bit counter circuit that resets its count on the
linear array board’s integration signal that begins a new series of photodiode readings.
Considering the expected image will be an eye, the difference in a change from light to
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dark, and dark to light may not be necessary to record. Over an extended number of
signals, patterns in light changes can be determined, allowing signal processing of
horizontal image movements present in front of the linear optical array. A block diagram
of the entire circuit component of the device is displayed below. A circuit diagram with
individual elements and pin numbers in included in Appendix A.
Figure 5. Block diagram of the entire circuit component of the device.
On each integration signal of the linear array evaluation board, a new series of
image data will be recorded, and passed to the computer component of the DUI device.
This is accomplished by a parallel port cable, utilizing 8 input/output pins, and 1 trigger
pin which are tied directly to the outputs of the counter chip and exclusive-or chip
respectively. A computer software program written in C++, which makes use of a special
driver class to communicate with the parallel port, is used to input data from the circuit
and store it in a text file. This text file can then be parsed into MATLAB, where a
MATLAB file has been written to analyze the data, and reconstruct the original
movement of the eye during the test. This file is able to discern between a blemish and
the pupil and thus provides more than a simple graphing utility. The source code for data
capturing and signal processing can be found in Appendix B.
Clock speeds of the linear array and circuit elements should be adequately fast to
detect, with great accuracy, the quickest possible physiological movement of the eye,
including nystagmus. This design is a new and unique approach to a project from last
year that attempted to measure and quantify nystagmus. The overall goal of measuring
fast eye movements remains, but the previous device used Electro-Oculogram (EOG)
technology instead of optical analyses. None of the previous theoretical design or any of
the components of the previous group have been used in this project. Each aspect of the
device and its design has been reworked.
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Tasks & Schedule
The design and development of this DUI testing device was broken down
into three distinct phases. Since our design required the integration of several different
individual components into one seamless product, we planned ahead to devote adequate
time to debugging and overcoming problems created by integrating the different
components. The first phase requires us to come up with a theoretical design and
evaluate the resources already available to us. Since this project builds on another project
done 4 months earlier, we first need to evaluate the earlier design to ascertain if any of its
components or design can benefit our idea. The initial planning phase of this project was
critical as we needed to chart out a path for the design and fully utilize the work already
done on this project. In the second phase, we implemented the design and at the same
time revised and updated the design to compensate for unforeseen circumstances and
other errors that came up while actually testing our design. The last phase of the project
involved testing the individual components thoroughly and integrating them together into
one seamless product. Figure 6 is a PERT chart that outlines our intended schedule and
breakdown of tasks.
Figure 6. PERT chart outlining the major goals.
Our final tasks and scheduling were significantly different from our intended path.
This was in part due to the unforeseen problems and circumstances. However, in many
cases we wrongly estimated the difficulty of a task and assigned very little time to it.
Thus, we had to spend a lot of time on tasks we initially thought would be very easy to
complete. In spite of these shortcomings, we were able to compensate for this extra time
since we were ahead of schedule for most of the semester. Figure 7 shows a PERT chart
that outlines our actual schedule of tasks performed. Thus it required constant work and
effort as individuals, and good co-ordination as a team to be able to keep working on
schedule.
Following is a detailed look at each of the three phases, the different tasks that
had to be completed and how we divided the work so that not only did we meet the
deadlines, but were also able to utilize each of the group member’s expertise.
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Figure 7. PERT chart showing task scheduling and major goals.
Phase I: Brainstorming, Planning and Initial Design Development
The first two weeks, January 12th through January 25th, were essentially
brainstorming sessions, where the work was driven by each group member’s ideas and
suggestions. Finally, it was decided that our implementation of the DUI testing device
will be based on Brock Wester’s design for the Linear Diode Array. With this as the
starting point, Ranit Windlass and Brock came up with a preliminary circuit design
linking the array with the Analog-To-Digital Converter. Narendhra Seshadri and Nisha
Javia evaluated the design from the previous semester. In the week of January 26, the
two teams compared the results and decided to build an entire new circuit as the old
circuit had too many extraneous components. Thus, by the end of phase I, we had
decided on an initial design, tested the old circuit and found it unacceptable, which gave
us a good start into Phase II.
Phase II: Design Implementation and Integration
This phase consisted of the most amount of work and most of the semester was
used in completing this phase. We had to divide the work since all the three technical
components, Electrical, Optical and Computer, needed to be developed simultaneously.
Brock and Ranit worked on the electrical component and implemented the circuit design
they had presented during Phase I. Meanwhile, Nisha contacted professors in the optics
department and performed some basic experiments to determine the lens setup that would
project the eye onto the linear array. Narendhra tried to configure the Analog-to-Digital
converter used by the previous DUI group for our use. However, the sampling rate was
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too slow and soon he was searching for a different scheme to perform the task of porting
data into the computer. After considering various options we decided to use the PC’s
parallel port to capture data from the Electrical circuit.
Our change of approach prompted Ranit to develop the code for the parallel port
communication. Nisha started working simultaneously on a DSP program in MATLAB
to analyze the ported data. Narendhra continued Nisha’s experiments and came up with a
simple design to test the Optical component of our design. Brock tested and verified the
working of the electric circuit. The electrical design essentially remained unchanged, but
in some cases the implementation of a particular device was slightly different, for
instance we relied on a more TTL based implementation rather than a more analog based
implementation, which is what we had visualized earlier. These few weeks everyone was
working on their own but we communicated effectively and continuously via email.
The development and verification of software took longer than anticipated but this
time was well used in the development of the Electrical and Optical Components.
Narendhra laid the circuit out cleanly on a breadboard whereas Brock made a more
permanent and sturdy setup for the lenses with PVC encasing. After verifying the
working of the DSP and port communication, we were ready to integrate the three
components together and begin phase III.
Phase III: Integrating, Final Testing and Presentation
The final phase involved overcoming all the unanticipated delays, removing any
potential bugs or shortcomings in design and compensating for unforeseen circumstances.
Although we had been doing well as a team till now by compensating for each other to
keep the project on schedule, we were unable to find solutions to the problems in this
phase fast enough. The Optical and Electrical components were integrated with only
minor hiccups. Without much trouble we were able to tie in the native clock signal from
the linear array to the registers and counters. The problem lay in tying in the computer
component with the design.
Despite our sincere efforts and consistent work, we were unable to come up with
a scheme to resolve all the power issues we faced in porting data. However, the solution
is not too far and should only require another week or two to solve. In the following
Gantt chart, a summary of the task breakdown and scheduling is presented. Most of the
work that needs to be done has already been completed and only a small amount of effort
and time is needed in completing the prototype of this excellent product.
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Product Demonstration
Due to the expected portability of the final system, the optical and circuit
components of the device must be able to perform under random and possibly extreme
environmental conditions. It will be possible to take a live reading with the device and
the collection of data by the circuit element, and the displaying of that data using a
graphical user interface will be a possible demonstration. With the graphical display of
the optical data, it will be evident that the circuit has been able to determine the major
visible components of the eye, and can track its movement.
Setup of the device will require a power source of 7V to power the linear array
evaluation board, and a power source of 5V to power the integrated circuit. The parallel
port cable needs to be connected to a computer with the required software to collect data
from the circuit and analyze it.
A complete demonstration of the device takes part in two steps. The first step is
to acquire binary data in a text file based on the movement of the eye, and the second step
is the run the text file through the signal processing algorithm which will graph the
movement of the eye.
To begin a test, the software to collect data must be loaded and then executed
when the examinee is ready to begin testing. The software, which will not require any
initial setup, will be timed and will eventually terminate, at which point a text file will be
created with the data from the test. This data file will then need to be loaded into the
signal processing software where the movement of the eye over time will be graphed.
The actual testing of the eye movement, which will be determined at a later date,
can vary in length, but will contain enough eye movements to acquire sufficient data to
understand physiological behavior. Analysis of the test data will take a matter of seconds,
as the data is interpreted by software.
Conclusions
Though this product was developed after a lot of thought and tremendous effort
was put into its development, a few possible changes in the product will make it simpler,
more accurate, reliable, useful and lucrative. Since the product consists of three main
components, i.e. circuit component, optical component and computer component, we can
individually look at each of these and discuss alternatives to make the overall design
superior.
Optical component: The optical component consists of an arrangement of lenses
and mirrors encased in a PVC tube. An infrared image captured by the moving eyeball is
incident on this system of lenses and mirrors, which is subsequently passed along into the
linear diode array (consisting of 128 photodiodes). This image is interpreted to create an
output which is basically an analog voltage. This optical component of our product could
be improvised in a way so as to reduce its complexity. People with a good understanding
in the field of physics and optics should be able to accomplish this quite easily.
Electric component: The electric component consists of a complex integrated
circuit consisting of several chips connected on a bread board. The output from the linear
array, which is an analog voltage, is analyzed to get significant data. The data so aquired
is converted to a digital signal, which is in turn fed to a computer by means of a parallel
port cable. This electric component of our product could be improvised in a way so as to
directly feed the analog output from the linear array to a computer. This will eliminate the
use of the parallel port cable completely and, hence, reduce the amount of signal
processing. This means adding more hardware components to the design while increasing
costs measly.
Computer component: The computer component consists of a combination of
Visual C++ and MATLAB programs. The data fed into the computer via a parallel port
cable will go through some data communication software code and digital signal
processing code in order to be interpreted for reconstruction of the original eyeball
movement. This computer component of our product could be improvised in a way so as
to include more digital signal processing code to filter out noise and outlier data points
from the signal. Some other means of circuit-to-computer communication could be
devised and implemented which could allow faster data flow and in turn also increase
accuracy.
Although, thorough testing of the individual optical, circuit and computer
components was carried out, due to time and resource constraints our product was never
fully tested after integration of all the three components. Finally, some data collection
and testing needs to be done to evaluate the usefulness and accuracy of our product. In
order to accomplish this task, a stimulus consisting of a horizontally moving light pattern
emitted from an array of LEDs needs to be created.
In some more time, the little work that remains to be done can be finished to
provide the final product as designed to provide a better and more accurate DUI testing
device.
Continuation
There were several complicated and very different components present in the DUI
device which could be improved individually to make the device perform better. The
first component of the device consisted of an optical setup that took an infrared image of
the moving eye, and passed it through several lenses and into a linear optical array, which
created an analog voltage output of the interpreted image. The optical setup of this
device could be improved or reworked by a team more adept in optics, reducing the
overall cost of complexity of this component.
The second component of the device was a integrated circuit that took the analog
output of the linear array, analyzed the signal, decoded it, and converted significant data
it into a digital signal that could be feed to a computer for high speed logging. While this
component considerably reduces the required signal processing by the computer, it is
possible, given the right funding and hardware, that this component could altogether be
removed from the device by feeding the analog output of the linear array directly to a
computer.
18
The third component consisted of several software programs on a computer that
collected data through a parallel port attached to the integrated circuit and interpreted the
data to reconstruct the original movement of the eye. While this component of the
project works correctly, additional signal processing could be used to compensate for
unexpected input or noise from the signal. There are also several other methods possible
for communication between an integrated circuit and a computer which could be
developed to allow for increased or more efficient data flow, and in turn, increased
accuracy for the tests conducted by the device.
Each component required significant amounts of time, and while their
effectiveness and performance could be tested individually, their eventual combination,
and the performance of the entire device, was never fully tested.
Some valid data was collected, which could say that the prototype or at least the
individual components are performing as designed. However, the tests for eye movement
and their execution and analysis, which will dictate the eventual usefulness of the device
in determining the level of intoxication of an individual, have not been created. A
stimulus for the test, consisting of a simple moving light pattern emitted from an array of
regular LEDs will need to be created, and then correlated with the movement of the
patient’s eye. Digital signal processing can then be used to quantify reaction speeds, and
other physiological responses.
It is believed that alternative methods of collecting optical data and passing it
through a circuit to a computer for logging could be achieved. Given another semester,
this device could be re-tweaked to provide for a more professional prototype. However,
considering the time requirements for the PhD student needing the device, with a little
more time, this device will perform as designed.
19
Bibliography
[1]
Bureau of Transport Statistics,”Occupant and Nonmotorist Fatalities in Crashes
by Number of Vehicles and Alcohol Involvement (AI)” [Online Document]
http://www.bts.gov/publications/national_transportation_statistics/2003/html/table
_02_20.html
[2]
CDC, “Impaired Driving,” [Online Document]
http://www.cdc.gov/ncipc/factsheets/drving.htm
[3]
Forensic Evidence, “Horizontal Gaze Nystagmus,” [Online Document]
http://www.forensic-evidence.com/site/Biol_Evid/HGN.html
[4]
Breathalyzer.net, “Consumer and Professional Breathalyzers,” [Online Document]
http://www.breathalyzer.net
[5]
Digi-Key Corporation, “Parts Search,” [Online Document]
http://www.digikey.com/
[6]
SGS-Thomson Microelectronics, “TTL Data Sheets,” [Online Document]
http://www.ulrich-roehr.de/elektronik/pulslimiter/hc123.pdf
[7]
Maxim Semiconductors, “Parts Number Search (Price and availability),” [Online
document]
http://www.maxim-ic.com/index.cfm
[8]
Melexis Microelectronic Integrated Systems, “Linear Optical Array”
[Online Document] http://www.melexis.com/prodfiles/mlx90255ba.pdf
20
Appendix A: MATLAB Code for DSP and Visual C++ code for Parallel Port
Communication
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%% ECE 4006 DUI Tester Group
%% DSP Code to parse and manipulate the data
%% Parses code and then finds midpts from the matrix
load data.txt %% data from the linear array
positions = 64; %% array of the final eye positions
i = 1;
l=0;
midpts = 0;
startpts = 0;
val=0;
while i < length(data),%% going through all the data
l=0;
midpts = 0;
startpts = 0;
val=0;
while (i < length(data) & data(i+1,1) > data(i,1)), %% checking one instance
sol = data(i+1,1)-data(i,1);
if sol >= 30 & sol <= 50 %%checking if big enough to be an eye
l=l+1;
if l==1
midpts = (data(i+1,1)+data(i,1))/2;
startpts = data(i,1);
else
midpts = vertcat(midpts, (data(i+1,1)+data(i,1))/2);
startpts = vertcat(startpts, data(i,1));
end
end
i = i+1;
end
if l>1 & startpts(1,1)==0
val = midpts(2,1);
else
val = midpts(1,1);
end
positions = vertcat(positions, val);
i = i+1;
end
plot(positions)
Figure A1. MATLAB code for DSP.
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// InpoutTest.cpp : Defines the entry point for the console application.
// DUI Tester Group. Code to capture data from parallel port.
#include "stdafx.h"
#include "stdio.h"
#include "string.h"
#include "stdlib.h"
#include <conio.h>
#include <vector>
#include <deque>
/* ----Prototypes of Inp and Outp--- */
short _stdcall Inp32(short PortAddress);
void _stdcall Out32(short PortAddress, short data);
/*--------------------------------*/
int main(int argc, char* argv[])
{
FILE* pfile = fopen("data.txt","w");
std::deque<int> data;
int val;
int test1 = 0;
short status;
status = Inp32(0x379);
int count = 0;
while(1){
//printf("%d \n", status);
if(status != 0){
//printf("%d ", status);
val = Inp32(0x378);
fprintf(pfile,"%d\n",val);
//printf(" value is :%d \n", val);
data.push_back(val);
count = 0;
}
else{
count++;
}
status = Inp32(0x379);
printf("%d %d \n", status, val);
//printf("%d running \n",status);
}
fclose(pfile);
printf("ran fine \n");
printf("completed data capturing. %d values written to data.txt\n", data.size());
printf("press any key to perform DSP and signal analysis \n");
getch();
return 0;
}
Figure A2. Visual C++ code for parallel port data communication
Note: This application is built on a driver class called Inpout32. The complete code for
this driver can be obtained from our materials CD or from www.logix4u.net This
code sets up parallel port communication for any Windows or DOS based system.
23
Appendix B: Schematic of Circuit and Pictures of Final Design
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Figure B1. PSpice schematic of the circuit.
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Figure B3. Top view showing linear array (without lens setup).
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Figure B4. Picture showing the placement of lens setup on the linear array.
Figure B5. Top view showing entire setup and the placement of lenses inside the PVC casing.
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