Electronic versions

DOI

  • Germano Gallicchio (Developer)
  • Donghyun Ryu (Other)
    Loughborough University
  • Mudit Krishnani (Other)
    Loughborough University
  • Guy Tasker (Other)
    Loughborough University
  • Alessandra Pecunioso (Other)
    University of Padova
  • Robin Jackson (Other)
    Loughborough University
This study aimed to evaluate the utility and applicability of electrooculography (EOG) when studying ocular activity during complex motor behavior. Due to its lower spatial resolution relative to eye tracking (ET), it is unclear whether EOG can provide valid and accurate temporal measurements such as the duration of the Quiet Eye (QE), that is the uninterrupted dwell time on the visual target prior to and during action. However, because of its greater temporal resolution, EOG is better suited for temporal-spectral decomposition, a technique that allows us to distinguish between lower and higher frequency activity as a function of time. Sixteen golfers of varying expertise (novices to experts) putted 60 balls to a 4-m distant target on a flat surface while we recorded EOG, ET, performance accuracy, and putter kinematics. Correlational and discrepancy analyses confirmed that EOG yielded valid and accurate QE measurements, but only when using certain processing parameters. Nested cross-validation indicated that, among a set of ET and EOG temporal and spectral oculomotor features, EOG power was the most useful when predicting performance accuracy through robust regression. Follow-up cross-validation and correlational analyses revealed that more accurate performance was preceded by diminished lower-frequency activity immediately before movement initiation and elevated higher-frequency activity during movement recorded from the horizontal channel. This higher-frequency activity was also found to accompany a smoother movement execution. This study validates EOG algorithms (code provided) for measuring temporal parameters and presents a novel approach to extracting temporal and spectral oculomotor features during complex motor behavior.

Keywords

  • Electrooculography (EOG), Quiet Eye (QE), MATLAB
Original languageEnglish
PublisherZENODO
DOIs
Publication statusPublished - Oct 2023

Research outputs (2)

View all

Prof. activities and awards (1)

View all

Accolades (1)

View all

View graph of relations