Vanderbilt University
Biomedical Engineering Department
Senior Design 2011
The Digital
Craniometer
Application
An iOS application to aid in
the screening of
plagiocephaly in infants
Chris Heelan – Cody Hall – Jorge Perez
Robert Galloway (Advisor)
Contents
Abstract ......................................................................................................................................................... 1
Introduction ................................................................................................................................................... 3
Current Methods for Cranial Measurement .......................................................................................... 3
Operational Scenario ................................................................................................................................. 5
Initial Design Concept .............................................................................................................................. 6
iOS Concept for Image Based Craniometer .............................................................................................. 7
Methodology ................................................................................................................................................. 9
Results ......................................................................................................................................................... 14
Conclusion .................................................................................................................................................. 16
Recommendations ....................................................................................................................................... 17
Table of Figures/Tables
Figure 1. Malformations of Infant Cranium.................................................................................................. 3
Figure 2. Normal (left) vs. Supported Sleeping positions ............................................................................. 4
Figure 3. Plagiocephaly Diagnosis vs. Age for treatment with positional modification .............................. 4
Figure 4. Aggressive treatment method using corrective band ..................................................................... 5
Figure 5. Initial Design Concept Digital Caliper .......................................................................................... 6
Figure 6. Requirements Hierarchy ................................................................................................................ 7
Figure 7. Offset marker ............................................................................................................................... 13
Figure 8. Splash Screen and Menu Screen .................................................................................................. 14
Figure 9. Measurement Screen.................................................................................................................... 15
Table 1. Collected Accuracy Data .............................................................................................................. 16
Abstract
The purpose of this senior design project was to provide an easy, accurate and fast solution for
measuring critical measurements of an infant’s head. Plagiocephaly is a condition where an
infant has a deformed head due to either gestational or positional pressures on the skull. 70% of
all infants will be screened for plagiocephaly in the first two years after birth. Given the
percentage of children screened and the ability to better treat malformations at early stages, it is
beneficial to have a simple and accurate method to diagnose plagiocephaly early in a child’s
development. The result of our project was a fully functional manual iOS application built to
iPhone 4 specifications that can determine critical diagonal measurement ratios and angle
measurements useful for early detection of plagiocephaly in newborns. The project could be
expanded in the future to include image processing and a more automated application by
incorporating edge detection and absolute measurement options.
Introduction
Current Methods for Cranial Measurement
Our team interviewed two pediatricians to determine what current methods are applied to
measuring baby heads. We discovered that purely conventional means, such as tape measure, are
employed each day to determine critical lengths. Measurements are then hand calculated on
paper or with a calculator. This scenario required multiple steps to complete and sometimes
became redundant with room for error according to the initial feedback from our surveys.
Figure 1. Malformations of Infant Cranium
Current methods also include plastic calipers that help speed up the process of diagnosing
plagiocephaly. Two sets of measurements are useful for determining the extent of plagiocephaly
and other deformations. Figure 1 shows an example of plagiocephaly on the left.5 Not only is
there a difference in diagonal measurements but there is also an angle between the midline of the
head and the ears that is not orthogonal. This is also useful for a specialist to use for verifying the
correct treatment option based on the degree of malformation. Treatment options include
positional correction by relieving pressure on the back of the head during sleep or by a more
dramatic means of a corrective helmet.4
Figure 2. Normal (left) vs. Supported Sleeping positions
Figure 3. Plagiocephaly Diagnosis vs. Age for treatment with positional modification
Figure 4. Aggressive treatment method using corrective band
Operational Scenario
The purpose of the project was to measure the necessary dimensions of an infant's head in
order to determine if they are developing plagiocephaly. These measurements included two
linear distance measurements (combined to calculate a ratio) and an angular measurement
(indicating alignment of the ears relative to the mid-line of the head). If the values of these
measurements pass certain thresholds, the pediatrician will recommend the infant to a specialist.
To accomplish this goal, we created an iPhone application to be used by pediatricians. The
device utilized the camera API, allowing the user to take a new picture or load a previously taken
picture. Once the picture was loaded, markers appeared giving the user the ability to drag these
markers to the positions on the head that the doctor would like to measure (placement differs
depending on whether the ratio or angle calculation is needed). In ‘Ratio-mode’, the application
measured the ratios of the diagonal distances across the head along with the angle from the mid
line. A ratio was calculated and displayed as an output to the doctor. Likewise, in ‘Angle-mode’
the application calculated the angle between the lines designating the mid-line and the ear-line.
The angle will be displayed as an output. With the ratio and angle values, the pediatrician can
determine if the infant should seek a specialist’s help.
Initial Design Concept
At the onset of the project our team wanted to create a physical device to measure the required
distances in a more automated fashion. We called this concept ‘digital craniometer calipers.’ Our
team designed a hat that could be placed on a child’s head that would read out critical
measurements on an LCD screen.
Figure 5. Initial Design Concept Digital Caliper
This concept drawing in Figure 5 shows the inner workings of the digital caliper. This
would be sewn into a hat and fit over a child’s head. The drawing on the left shows the arms that
would be finely positioned after the hat is on. The drawing to the right shows the top view, where
an LCD screen could be read while the hat is on the baby.
iOS Concept for Image Based Craniometer
In order to utilize existing equipment and distribution available to over half of healthcare
professionals today1, an image based solution was considered the best solution for a semiautomated measurement system. The iPhone was chosen as the platform for our new solution
due to the high rate of adoption within healthcare professionals and the success of the Apple App
Store.
An image guided approach proved to be the strongest alternative to a physical device
because of the ability to extend normal diagnosis to future applications available on network
connected devices running iOS. In a certain scenario, a physician can upload the photograph of a
patient to an electronic medical record and this photo would document disease state and be
available to share with specialist should they need to be consulted.
Figure 6. Requirements Hierarchy
Figure 6 displays the requirement hierarchy for the iOS image based craniometer. This shows
each of the necessary considerations for building our device on an image based platform.
Methodology
The project’s initial approach involved designing a physical device that would be placed
on the child’s head to gather the needed measurements. The basic concept involved anchoring
two sets of calipers to a central electronics housing. Each set of calipers contained a digital angle
sensor thereby providing the needed data (along with the dimensions of the calipers) to calculate
the linear distance of the desired diagonals of the infant’s head thereby providing the values
needed to determine the infant’s plagiocephaly ratio. Additionally, a digital angle sensor
connected between the two sets of calipers allowed the user to find the midline to ear-line angle
by placing one set of calipers along the midline and the other along the ear-line. This design
required mechanical design and fabrication, electronic hardware selection, PCB design, and
microcontroller coding in order to attain a final product.
After presenting this idea to our advisors and their graduate students, a much simpler
approach than a physical device was realized. Since the required ratio and angle measurements
were both relative (as opposed to absolute) measurements, the values could be determined using
arbitrary units such as the pixels of a digital image. Furthermore, the image analysis required to
find the ratio and angle values was simple enough that the calculations could be computed with
much less processing power than is available on most desktop and laptop computers. In fact, the
calculations could be performed by most smart phones which also usually include a fairly high
resolution camera. By designing an application for a smart phone instead of creating a physical
device, the complexity of the project was reduced from hardware and software development to
solely software. This transition also removed any physical contact with the child (safer for the
infant and easier for the pediatrician) as well as limiting the cost of the project since the
hardware platform would already be owned by the pediatrician.
Due to the recent release of the iPhone 4 and the iOS 4 operating system, this phone was
chosen as the platform for the digital craniometer. Further research showed that about 41% of
pediatricians currently use an iPhone indicating that our application would have an initial market
base.1 The 5 megapixel camera, 960x640 touchscreen at 326ppi, and an 800MHz A4 processor
indicated that the hardware of the iPhone 4 was most likely more than adequate for the
application’s required precision (approximately 1mm) and calculations.2 This assumption would
later be verified during application testing. Finally, the App Store offered a simple and quick
method for mass distribution of the application both domestically and internationally.
While all members of the digital craniometer team had coding experience, none had ever
designed an application for a smart phone. Therefore, the first stage of developing the application
involved heavily researching not only iOS application development but also object-oriented
programming in general. This was accomplished using a video lecture series found on iTunes
University from Stanford University along with numerous textbooks.
Once familiar with Apple’s software development kit (SDK), an initial application was
created that included a splash screen, menu screen with two buttons (‘Load Image’ and
‘Camera’), and a measurement screen consisting of a pre-loaded image of an infant’s head
(navigated to by pressing the ‘Load Image’ button). This application was then expanded by
adding markers to the measurement screen that could be moved around the screen by the user’s
touch gestures.
A ‘Calc. Angle’ button was then added to the measurement screen which displayed the angle
between the midline (designated by a white pair of markers) and ear-line (designated by a blue
pair of markers) in a message box. A description of how this angle was calculated is shown
below:
1) Calculate the midline and ear-line vector by subtracting the x and y-values of the white
and blue markers respectively
2) Calculate the angle between the vectors using the following equation:
𝐴𝑛𝑔𝑙𝑒 = 𝑎𝑡𝑎𝑛2 (𝑚𝑖𝑑𝑙𝑖𝑛𝑒𝑦 , 𝑚𝑖𝑑𝑙𝑖𝑛𝑒𝑥 ) − 𝑎𝑡𝑎𝑛2(𝑒𝑎𝑟 − 𝑙𝑖𝑛𝑒𝑦 , 𝑒𝑎𝑟 − 𝑙𝑖𝑛𝑒𝑥 )
eq. #1
Likewise, a ‘Calc. Ratio’ button was added to the measurement screen which initiated the
process of finding the desired diagonals and calculating their ratio. A description of this process
is shown below:
1) Calculate the slope of the midline using the x and y-values of the white markers
2) Calculate the slope of the longest diagonal using the x and y-values of the blue markers
3) Calculate the y-intercept of the midline line using the slope and one of the white marker
coordinates
4) Calculate the y-intercept of the longest diagonal line using the slope and one of the blue
marker coordinates
5) Calculate the angle between the midline and the longest diagonal using eq. #1
6) Using the angle found above, rotate the white markers this angle from the midline using
the following equations:
𝑥𝑛𝑒𝑤 = (𝑥𝑜𝑙𝑑 − 𝑖𝑛𝑡𝑒𝑟𝑠𝑒𝑐𝑡𝑖𝑜𝑛𝑃𝑜𝑖𝑛𝑡𝑥 ) ∗ cos(𝛼) − (𝑦𝑜𝑙𝑑 − 𝑖𝑛𝑡𝑒𝑟𝑠𝑒𝑐𝑡𝑖𝑜𝑛𝑃𝑜𝑖𝑛𝑡𝑦 ) ∗ sin(𝛼) +
𝑖𝑛𝑡𝑒𝑟𝑠𝑒𝑐𝑡𝑖𝑜𝑛𝑃𝑜𝑖𝑛𝑡𝑥
eq. #2
𝑦𝑛𝑒𝑤 = (𝑥𝑜𝑙𝑑 − 𝑖𝑛𝑡𝑒𝑟𝑠𝑒𝑐𝑡𝑖𝑜𝑛𝑃𝑜𝑖𝑛𝑡𝑥 ) ∗ sin(𝛼) + (𝑦𝑜𝑙𝑑 − 𝑖𝑛𝑡𝑒𝑟𝑠𝑒𝑐𝑡𝑖𝑜𝑛𝑃𝑜𝑖𝑛𝑡𝑦 ) ∗ cos(𝛼) +
𝑖𝑛𝑡𝑒𝑟𝑠𝑒𝑐𝑡𝑖𝑜𝑛𝑃𝑜𝑖𝑛𝑡𝑦
eq. #3
7) Calculate the slope and y-intercept of the new diagonal using the x and y-values of the
white markers
8) Lock the movement of the blue markers to prevent accidental relocation
9) Restrict the movement of the white markers to only in the y-direction (user changes yvalue of white marker and x-value is automatically calculated using the slope and yintercept found in step #7)
10) Calculate the ratio of the diagonals by dividing the length of one (in pixels) by the length
of the other (in pixels)
Up to this point, the application had only been tested using the iPhone simulator included in
Apple’s SDK. In order to implement the true functionality of the menu screen’s ‘Load Image’
and ‘Camera’ buttons, the application had to be loaded onto a physical iPhone because the
camera application programming interface (API) could not be accessed from within the
simulator. After purchasing a developer’s package from Apple that provided us with the
necessary permissions to develop an application on an iPhone, the camera API was fully
implemented in the craniometer application. Testing the application on an iPhone verified that
the user could load a previously saved image or capture a new one by clicking the appropriate
button on the menu screen.
Once the application’s functionality had been tested, the team’s focus turned towards its
usability. Creating new offset markers shown in Figure #7 allowed the user to see the marker’s
point even while their finger was still on the screen.
Figure 7. The revised offset marker allowed the user to precisely place the point of the marker without blocking the point
with their finger.
This provided for more precise placement of the markers. Certain marker locations were also
locked during the ratio determination process thereby preventing the user from moving markers
that would result in an inaccurate measurement. Finally, a triple-tap function was added that
allowed the user to return to the menu screen by triple-tapping anywhere on the measurement
screen. Using a gesture (triple-tap) to accomplish this prevented the measurement screen from
becoming cluttered with buttons.
Once the usability of the application seemed adequate to the design team, testing began to
both verify the application’s accuracy and gather input about its usability. Ten people were given
instructions on how to use the application. They were provided with a standardized photo with
marked points for ratio measurements and angle measurements. The design team calculated the
true ratios and angles by hand which provided true values to compare the collected data against.
The collected data was averaged across subjects, and percent error was calculated to quantify the
accuracy of the digital craniometer application. Lastly, usability suggestions were collected from
the test subjects.
Results
The efforts described in the “Methodology” section resulted in an iPhone 4 application that
was simple to use yet extremely effective at its purpose. When the application is launched, the
user is shown a splash screen and menu screen as shown in Figure #8.
Figure 8. The splash screen (left) and menu screen (right) are the first screens shown to the user after launching the
application.
After selecting the source of the image (the user’s photo library or camera), the image is loaded
onto the measurement screen with two sets of markers (white and blue) as shown in Figure #9.
Figure 9. The splash screen (left) and menu screen (right) are the first screens shown to the user after launching the
application.
The following process outlines how to find the ratio of the longest diagonals once an image is
loaded:
1) Place white markers on midline and blue markers on longest diagonal
2) Press the “Calc. Ratio” button
3) Adjust the white markers to the edge of the infant’s head. Note that the x-value of the
marker will be automatically calculated from the provided y-value in order to maintain
the proper angle of the diagonal
4) Press the “Calc. Ratio” button
5) Result is displayed. Press the “Go Back” button to return to the measurement screen
Similarly, the angle between the midline and ear-line can be found by following the procedure
described below:
1) Place white markers on midline and blue markers on ear-line
2) Press the “Calc. Angle” button
3) Result is displayed. Press the “Go Back” button to return to the measurement screen
At any time during either of these processes, the user may triple-tap the screen to return to the
menu screen and start over.
The data collected from the ten individuals showed that the application was extremely
accurate while determining the ratio of the longest diagonals. Table #1 shows a summary of the
collected data indicating that, on average, the application has a percent error of only 1.036%.
Length A (cm)
Length B (cm)
Ratio
Average User Results
Percent Error
14
13.3
12.6
11.9
11.2
14
14
14
14
14
1
0.95
0.9
0.85
0.8
0.99731
0.94128
0.8834
0.84107
0.79119
0.27%
0.92%
1.84%
1.05%
1.10%
Table #1. A summary of the collected accuracy data. Please note the very low percent error values.
Unfortunately, a coding error made the midline to ear-line angle results invalid. This problem
was quickly remedied once discovered and further testing suggested a similar accuracy as the
longest diagonal data. This was as expected since the accuracy of the application has mostly to
do with the resolution of the touchscreen. The most prominent usability suggestions included
removing buttons from the measurement screen and automating the ratio and angle processes
using edge-detection algorithms. While the latter suggestion was explored throughout the
semester, a shortage of time prohibited the development of a fully automated application using
image processing algorithms. However, the test subjects unanimously agreed that the application
was simple to use and fairly robust in its operation.
Conclusion
In conclusion, the Digital Craniometer for iOS devices was a success. In regards to the
actual functionality of the device, we were able to obtain testing that verified the accuracy of the
device to calculate ratios between selected lengths on the screen. In the testing, we were able to
obtain an average of slightly more than 1% error in the accuracy of the actual device. In regards
to the accuracy of the test in determining the presence of plagiocephaly, it becomes dependent on
the ability of the user to determine the correct segments to measure. Given correct usage of the
device by either a trained professional or a user who is capable of following the directions, the
device does have the ability to accurately determine the symmetrical integrity of the child’s head
along with the angle of the ear-line. The subjectivity of the test itself comes into question when
regarding this accuracy. The test, as given now, requires the use of a caliper (plastic, fork shaped
device that is used to physically measure the linear distance). The user will estimate the longest
diagonal distance across the child’s head and then measure the distance of the diagonal at the
same angle to the midline. The issue with this is that it falls on the user to determine the longest
diagonal along with accurately mirroring the angle across the midline. The goal with our
application was to remove all of the physical aspects of the test (i.e. touching the child at all);
however the subjectivity described above remains.
While we did meet our specifications for a manual version of our application, we were
unable, due to our time constraint, to create a fully automatic version of the application. With the
help of edge detection image processing algorithms the application could become fully
automated thereby eliminating even more error and increasing the speed and ease of the test.
Recommendations
This application has incredible potential in terms of revolutionizing the way initial
plagiocephaly detections are done. Eliminating the need to physically contact the infant removes
a removes any possible safety concerns while also making the test easier to perform on a
squirming child. This alone is reason enough for most doctors to download and use our
application for detection in their office.
Looking forward, the design team hopes to release this application in the Apple App
Store, possibly with the help of the tech transfer office at Vanderbilt. Submitting the application
to Apple actually requires a much greater effort than if this application was released for the
Android platform. While we will need to ensure our application follows all the guidelines for
successful submission, the team is capable of fixing these bugs.
In regards to the actual market, our application has enormous potential. As mentioned
before, the devices now used to detect plagiocephaly in children are calipers, which cost an
average of about $15. These devices are made of plastic and require manufacturing to produce
them. One of the most important factors in the success of our product is the fact that the design
team did not create a device; it developed software for existing devices. Therefore, in regards to
the project as a viable product, it requires no overhead, manufacturing costs, or distribution costs.
In addition, due to the chaotic environment of a pediatrician’s office, every room in the office
would require a physical device such as a set of calipers. With our application, each doctor
would only have to purchase the application once. And, at a cost of $5.99 per download, the
application will cost a third of the price of one caliper. Not only would an office save 2/3 the cost
of the device, they would also need to purchase less copies.
According to research done by a California based consulting company, there is a rise in the
popularity of smartphones among physicians. More specifically, it was reported that 94% of
physicians use smartphones, with 44% of them choosing the iPhone over other models.1 With
nearly 75,000 pediatricians in the US alone3, that leaves just over 31,000 pediatricians who
currently own iPhones. This leaves an untapped, and essentially unchallenged (with the
numerous benefits of our device over the current caliper) market with an earning potential of
nearly $185,000.
Sources Cited
1) http://www.knowabouthealth.com/smartphone-use-among-us-physicians-acceleratingrapidly/4502/
2) http://www.apple.com/iphone/specs.html
3) http://www.aap.org/workforce/
4) JA, P. (2008). MOC-PS(SM) CME article: managemetn consideratins in the treatment of
craniosynostosis. Plast Reconstr Surg, 1-11.
5) McGarry, D. G. (2008). Head shape measurement standards and cranial orthoses in the
treatment of infants with deformational plagiocephaly. Dev Med Child Neurol, 568-76.