Gabriel Maglione
Pronouns: He/Him
Research Mentor(s): Zhenyang Zhao
Research Mentor School/College/Department: Kellogg Eye Center / Other
Program:
Authors: Gabriel Maglione, Andrew Seamone
Session: Session 7: 4:40 pm – 5:30 pm
Poster: 77
Abstract
This study presents a novel technique to analyze motion data measured on the surface of the eyelid during the blinking process. A point tracking analysis technique known as digital image correlation was performed using GOM Correlate as the analysis software. A Matlab script was developed to analyze the data and to characterize the displacements, velocities, and accelerations associated with eyelid motion. A robust method for measuring the time duration of each blink was also developed. Data from both spontaneous and reflex blinks were studied. Due to noise in the data generated during the collection and analysis procedures, a variety of data manipulation strategies were studied for filtering, smoothing, and generalizing the data. Visualization of the data using the developed code allows for clear understanding of the blink characteristics and provides insight to numerical differences between blink types. This algorithm is an efficient and consistent analysis method for the study of eyelid kinematics during blinking.
