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Eye-tracking to Distinguish Comprehension-based and Oculomotor-based Regressive Eye Movements During Reading
Published on: October 18, 2018
Software for the automatic correction of recorded eye fixation locations in reading experiments
1Department of Psychology, University of Massachusetts, 135 Hicks Way, Amherst, MA 01003-7710, USA. acohen@psych.umass.edu
Behavior Research Methods
|December 15, 2012
Summary
Manual correction of eyetracking data is time-consuming and subjective. This study introduces R software to automate the adjustment of fixation locations, improving efficiency and objectivity in reading experiments.
Area of Science:
- Cognitive Science
- Psychology
- Computer Science
Background:
- Eyetracking fixation locations require adjustment for accurate analysis.
- Manual correction is labor-intensive and introduces subjectivity.
- Automating this process can enhance research efficiency and reliability.
Purpose of the Study:
- Introduce novel software to automate eyetracking fixation correction.
- Focus on vertical location adjustment, outlier removal, and ambiguous fixation identification.
- Improve objectivity and reduce time in analyzing reading experiment data.
Main Methods:
- Development of an R function for automated eyetracking data correction.
- Utilizing linear regression to assign fixations to text lines.
- Implementing outlier and ambiguous fixation detection algorithms.
Main Results:
- The developed R function automates key aspects of fixation correction.
- The software assists in identifying and removing erroneous fixation data.
- Provides a more objective and efficient method for data preprocessing.
Conclusions:
- Automated correction of eyetracking data offers significant advantages over manual methods.
- The R software provides a valuable tool for researchers in reading experiments.
- Enhances the reliability and efficiency of eyetracking data analysis.
