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)

ContentsAbstract..........................................................................................................................................................1

Introduction....................................................................................................................................................3

Current Methods for Cranial Measurement...........................................................................................3

Operational Scenario..................................................................................................................................5

Initial Design Concept...............................................................................................................................6

iOS Concept for Image Based Craniometer...............................................................................................7

Methodology

Results

Conclusion

Recommendations

Table of Figures/TablesFigure 1. Malformations of Infant Cranium..................................................................................................3Figure 2. Normal (left) vs. Supported Sleeping positions.............................................................................4Figure 3. Plagiocephaly Diagnosis vs. Age for treatment with positional modification...............................4Figure 4. Aggressive treatment method using corrective band......................................................................5Figure 5. Initial Design Concept Digital Caliper...........................................................................................6Figure 6. Requirements Hierarchy.................................................................................................................7Figure 7. Offset marker................................................................................................................................13Figure 8. Splash Screen and Menu Screen...................................................................................................14Figure 9. Measurement Screen....................................................................................................................15Table 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 semi-

automated 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 (midlin e y , midlin ex )−atan2(ear−lin e y , ear−lin ex) 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=(x¿¿ old−intersectionPoin t x)∗cos (α)−( yold−intersectionPoint y )∗sin (α)+intersectionPoint x¿

eq. #2

ynew=(x¿¿old−intersectionPoint x)∗sin (α )+( y old−intersectionPoint y)∗cos (α )+intersectionPoint y ¿

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 y-

value of white marker and x-value is automatically calculated using the slope and y-

intercept 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 14 1 0.99731 0.27%13.3 14 0.95 0.94128 0.92%12.6 14 0.9 0.8834 1.84%11.9 14 0.85 0.84107 1.05%11.2 14 0.8 0.79119 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-accelerating- rapidly/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.