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1 MATLAB Digest www.mathworks.com

Te test method looks beyond simply mea-

suring the amount o powder delivered

through the mouthpiece by quantiying the

capsules motion inside the inhaler. Since

the capsule moves too quickly to be tracked

by the eye or with a conventional camera, a

high-speed video system was used to cap-

ture the capsules motion. We then used

MALAB to analyze the images rame byrame and summarize the results.

In a joint eort with MathWorks Con-

sulting Services, Alkermes developed avideo capture and ana lysis procedure

that uses MALAB and Image Process-

ing oolbox. he position o the cap-

sule was evaluated in each video rame.

Comparison o adjacent video rames

allowed us to characterize the linear

and rotational motion o the capsule.

Quantities such as the velocity, accel-

eration, and momentum o the capsule

were computed. Series o rames were

analyzed using signal processing. his

approach provided inormation on the

physical actors inluencing the inhalers

perormance.

Setting up the Test

We created inhalers with clear plastic

components so that the capsule would be

visible inside the aerosolization chamber

(Figure 1). o enable the development o

Figure 1. A standard inhaler (bottom) and a test inhaler (top).

MATLAB Digest

Tim Coker, Alkermes, and Paul Fricker, The MathWorks

The AIR pulmonary drug delivery technologybeing developed at Alkermes

provides targeted delivery o small-molecule or macromolecule drug particles

rom an easy-to-use, capsule-based, hand-held inhaler. When the patient inhalesthrough the mouthpiece, air is drawn into the aerosolization chamber, agitating a

capsule and releasing dry-powder medicine or systemic or local delivery to the

lungs. To optimize uture inhaler designs, Alkermes developed a test method to

understand the behavior o the capsule under a range o operating conditions

or example, a range o air fows representing patients o diering age and size.

Analyzing High-Speed Video Images to Quantify thePerformance of Innovative Drug Delivery Technology

Products Used

MATLAB

Image Processing Toolbox

Signal Processing Toolbox

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an a lgorithm or automatically processing

the captured video images, we marked the

capsules with a pattern consisting o two

separate lines: an equatorial line traveling

around the capsules circumerence, and a

slanted line that produces a sawtooth pat-

tern as the capsule is rotated (Figure 2).

Tis design provided a continuous image

or analysis.

Videos were captured in grayscale at a

rate o 10,000 rames per second and resolu-

tion o 256 x 256 pixels using a PhantomMonochrome high-speed video camera

rom Vision Research. o assess the mo-

tion (in 2-D) o the major axis o the cap-

sule inside the inhaler, we determined the

angle o the equatorial line or each video

rame as the capsule was agitated within

the chamber. Te peaks and valleys o the

resulting sinusoidal signal enabled us to de-

termine an amplitude and requency o the

wobbling motion o the capsule. A count o

the number o peaks o the continuous saw-

tooth pattern, captured while the capsule

was rotating, provided inormation on the

rotational angular motion o the capsule.

Processing a Single Image

In the experiments, the capsule and inhaler

were placed in several dierent orienta-

tions, ranging rom horizontal to vertical,

upright and inverted. In the image analysis,

the video rames were always rotated so that

the capsule appeared in a vertical orienta-tion, with the equatorial line positioned be-

low the slanted line. Figure 3 shows a single

rame rom one o the captured high-speed

video les. Regardless o the position o the

inhaler in the video, the analysis was com-pleted in the orientation shown.

Afer reorienting the video data, each

grayscale image was rst thresholded us-

ing the graythresh unction in Image

Processing oolbox to produce a binary, or

Boolean, image (Figure 4).

Along with the white lines o the capsule

pattern, Figure 4 shows several smaller ar-

eas produced by noise and glare rom the

experimental lighting. Tese smaller areas

were identied using the regionprops

unction and then eliminated, leaving just

the equatorial and the sawtooth lines.

Once the objects o interest had been

clearly identied in the image, we used

MALAB to automate the analysis.

We used a least squares tting proce-

dure to compute a straight line through

the equatorial line on the capsule. We then

located the end points and midpoint o that

line. A perpendicular line was then com-

puted rom the midpoint o the equato-

rial line to the midpoint o the slanted line

Figure 2. The capsule markings.

Figure 3. A raw image of the marked capsule inthe inhaler.

Figure 4. Boolean image produced by auto-thresholding the video frame.

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directly above. Tis relationship resulted

in a measure o the distance between the

equatorial and sawtooth lines along themajor axis o the capsule.

As the capsule moved about the aero-

solization chamber, we used the midpoint o

the least squares tted line to track capsule

position. Te angle o the least squares tted

line was used to track capsule wobbling, and

the peaks values in the distance between

the equatorial and slanted line were used

to track capsule rotations. We recorded the

coordinates o the equatorial line midpoint,

the distance between the equatorial and

sawtooth lines, and the angle o the equato-

rial line or each rame (Figure 5), and saved

the data in an Excel spreadsheet.

Analyzing the Data

Using MALAB, we post-processed the

stored data and produced summary results

or each experimental run. A typical run

lasted about 1.5 seconds, with approxi-

mately 15,000 video rames being captured

and analyzed or each test.

Te rame-to-rame displacement o the

equatorial lines midpoint was measured

using the Pythagorean theorem and the

coordinates o the midpoint. Dividing the

displacement by time between rames gave

the velocity o the capsule. Te changes in

velocity between rames provided the ac-

celeration o the capsule. Power, momen-

tum, and impulse were also calculated

based on these values.

We used Signal Processing oolbox to

compute a power spectral density (PSD)

rom the equatorial line orientation data

(Figure 6). Tis allowed or quick identi-

cation o the dominant requencies o the

capsules wobbling motion.

Once the image analysis and output

data post-processing algorithms hadbeen rened, we developed a GUI with

MALAB to streamline the execution o

the processing (Figure 7). Beore begin-

ning each analysis, we used the GUI to

record inormation about the test, such

as who conducted the experiment and

when, as well as the inhaler orientation,

test ow rate, and inhaler type. We added

a eature that makes the application pres-Figure 5. Analyzed video frame.

Figure 7. The MATLAB based GUI for executing

the analysis of the experimental video data.

Figure 6. Power spectrum density on a semi-log scale.

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For More Information

Alkermeswww.alkermes.com

Image Processing with MathWorks Toolswww.mathworks.com/applications/

imageprocessing

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ent the rst rame o the video when the

video processing begins and enables the

user to crop the image so as to remove the

periphery and isolate the aerosolization

chamber and the capsule. Tis cropping

is subsequently applied to all the rames

in the video.

Refining the Algorithm

Te steps outlined in this article were dis-

tilled rom an iterative experimental devel-

opment process in which the image analysis

algorithmsand even the markings used

on the capsuleswere designed, proto-typed, tested, and improved repeatedly. Te

interactive MALAB environment stream-

lined the data analysis algorithm develop-

ment process by making it easy to try new

approaches and techniques and immedi-

ately visualize the results. Tis allowed the

algorithm to be built step by step and then

rened as data was processed rom more

and more experiments.

Alkermes has already gained insight into

how the capsule moves within the inhaler,

and has correlated experimental variables,

such as ow rate, to a variety o quanti-

able eatures o the capsule motion.

Te long-term objective is to identiy

aspects o the capsule motion that determine

the amount, rate, and distribution o powder

delivery. Tis inormation, along with other

test results, will provide a oundation or op-

timizing uture versions o the inhaler.

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