University of Belgrade - School of Electrical Engineering, Bulevar kralja Aleksandra 73, 11000, Belgrade, Serbia.
Faculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000, Ljubljana, Slovenia.
Behav Res Methods. 2024 Aug;56(5):4277-4292. doi: 10.3758/s13428-023-02177-3. Epub 2023 Jul 24.
We present a method to automatically calculate time to fixate (TTF) from the eye-tracker data in subjects with neurological impairment using a driving simulator. TTF presents the time interval for a person to notice the stimulus from its first occurrence. Precisely, we measured the time since the children started to cross the street until the drivers directed their look to the children. From 108 neurological patients recruited for the study, the analysis of TTF was performed in 56 patients to assess fit-, unfit-, and conditionally-fit-to-drive patients. The results showed that the proposed method based on the YOLO (you only look once) object detector is efficient for computing TTFs from the eye-tracker data. We obtained discriminative results for fit-to-drive patients by application of Tukey's honest significant difference post hoc test (p < 0.01), while no difference was observed between conditionally-fit and unfit-to-drive groups (p = 0.542). Moreover, we show that time-to-collision (TTC), initial gaze distance (IGD) from pedestrians, and speed at the hazard onset did not influence the result, while the only significant interaction is among fitness, IGD, and TTC on TTF. Obtained TTFs are also compared with the perception response times (PRT) calculated independently from eye-tracker data and YOLO. Although we reached statistically significant results that speak in favor of possible method application for assessment of fitness to drive, we provide detailed directions for future driving simulation-based evaluation and propose processing workflow to secure reliable TTF calculation and its possible application in for example psychology and neuroscience.
我们提出了一种使用驾驶模拟器从神经损伤患者的眼动追踪数据中自动计算注视时间（TTF）的方法。TTF 表示人从首次出现刺激到注意到刺激的时间间隔。具体来说，我们测量了儿童开始过马路到驾驶员将目光转向儿童的时间间隔。在为该研究招募的 108 名神经患者中，对 56 名患者进行了 TTF 分析，以评估适合、不适合和有条件适合驾驶的患者。结果表明，基于 YOLO（你只需看一次）目标探测器的提出方法可有效地从眼动追踪数据中计算 TTF。通过应用 Tukey 的诚实显著差异事后检验（p < 0.01），我们获得了适合驾驶患者的有区别的结果，而在有条件适合和不适合驾驶的患者之间没有观察到差异（p = 0.542）。此外，我们表明，碰撞时间（TTC）、行人初始注视距离（IGD）和危险发生时的速度不会影响结果，而唯一的显著交互作用是在 TTF 中存在 FIT、IGD 和 TTC 之间的交互作用。获得的 TTF 还与独立于眼动追踪数据和 YOLO 计算的感知反应时间（PRT）进行了比较。尽管我们取得了具有统计学意义的结果，表明该方法可能适用于评估驾驶能力，但我们提供了详细的驾驶模拟评估方向，并提出了处理工作流程，以确保可靠的 TTF 计算及其在心理学和神经科学等领域的可能应用。
