Confirming Hardware Accuracy in Eye Tracking Research
Description/Abstract/Artist Statement
In the field of Radiology, diagnoses depend on the subjective interpretation of content in medical images like X-Rays. This involves rigorous visual examination and the perception of these images with the goal to come to a definitive conclusion on a person's health. Eye tracking techniques have been used to track and analyze the search patterns of radiologists when they diagnose a patient in this fashion. These techniques include table-mounted or wearable eye-trackers that gather information about a user's pupillary activity to compare interreader search patterns and provide feedback pertaining to the regions the reader had previously gazed upon. These trackers are typically associated with an accuracy depicting the angle formed between the user's pupil, the place they are intending to gaze, and the position at which the hardware predicts they are gazing. Accurate tracker data could provide researchers and readers alike a better understanding of the reader, the stimulus, and the relationship between the two. Without proper procedure and accurate data supplied from the eye-tracking hardware, the discoveries based on the data would be rendered untrustworthy. Our system confirmed the accuracy stated by the GazePoint GP3 manufacturer by designing an experiment in which a user would calibrate and utilize the tracker to store and analyze the captured data in a systematic fashion. This experiment yielded an accuracy similar to that stated in the documentation and serves as a precursor to future conclusions to be drawn from accurate, reliable tracker data.
Faculty Advisor/Mentor
Desh Ranjan
College Affiliation
College of Sciences
Presentation Type
Poster
Disciplines
Cognition and Perception | Hardware Systems | Health Information Technology
Session Title
Monarchs Maximizing Access to Research Careers #2
Location
Zoom Room I
Start Date
3-20-2021 10:00 AM
End Date
3-20-2021 10:55 AM
Confirming Hardware Accuracy in Eye Tracking Research
Zoom Room I
In the field of Radiology, diagnoses depend on the subjective interpretation of content in medical images like X-Rays. This involves rigorous visual examination and the perception of these images with the goal to come to a definitive conclusion on a person's health. Eye tracking techniques have been used to track and analyze the search patterns of radiologists when they diagnose a patient in this fashion. These techniques include table-mounted or wearable eye-trackers that gather information about a user's pupillary activity to compare interreader search patterns and provide feedback pertaining to the regions the reader had previously gazed upon. These trackers are typically associated with an accuracy depicting the angle formed between the user's pupil, the place they are intending to gaze, and the position at which the hardware predicts they are gazing. Accurate tracker data could provide researchers and readers alike a better understanding of the reader, the stimulus, and the relationship between the two. Without proper procedure and accurate data supplied from the eye-tracking hardware, the discoveries based on the data would be rendered untrustworthy. Our system confirmed the accuracy stated by the GazePoint GP3 manufacturer by designing an experiment in which a user would calibrate and utilize the tracker to store and analyze the captured data in a systematic fashion. This experiment yielded an accuracy similar to that stated in the documentation and serves as a precursor to future conclusions to be drawn from accurate, reliable tracker data.