School of Psychology and Sport Science, Bangor University, Bangor, UK.
School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK.
Psychophysiology. 2024 Mar;61(3):e14461. doi: 10.1111/psyp.14461. Epub 2023 Oct 19.
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.
本研究旨在评估眼电图（EOG）在研究复杂运动行为期间眼球活动时的效用和适用性。由于其空间分辨率相对眼动追踪（ET）较低，因此尚不清楚 EOG 是否可以提供像 Quiet Eye（QE）持续时间这样的有效和准确的时间测量，即在动作之前和期间在视觉目标上不间断停留的时间。然而，由于其更高的时间分辨率，EOG 更适合时间-频谱分解，这是一种可以根据时间区分低频和高频活动的技术。16 名不同专业水平（从新手到专家）的高尔夫球手在平面上将 60 个球击向 4 米远的目标，同时我们记录了 EOG、ET、表现准确性和推杆运动学。相关和差异分析证实，EOG 可以提供有效和准确的 QE 测量值，但仅在使用某些处理参数时才可以。嵌套交叉验证表明，在一组 ET 和 EOG 时间和光谱眼动特征中，EOG 功率在通过稳健回归预测表现准确性时最有用。后续交叉验证和相关分析表明，在运动开始前，较低频率活动减少，运动期间较高频率活动增加，这与更准确的表现有关，这些活动都是从水平通道记录的。还发现这种较高频率的活动伴随着更平稳的运动执行。本研究验证了 EOG 算法（提供代码）用于测量时间参数，并提出了一种在复杂运动行为期间提取时间和光谱眼动特征的新方法。
