: Prolonged operation of construction equipment could lead to mental fatigue, which can increase the chances of human error-related accidents as well as operators’ ill-health. The objective detection of operators' mental fatigue is crucial for reducing accident risk and ensuring operator health. Electroencephalography, photoplethysmography, electrodermal activity, and eye-tracking technology have been used to mitigate this issue. These technologies are invasive and wearable sensors that can cause irritation and discomfort. Geometric measurements of facial features can serve as a noninvasive alternative approach. Its application in detecting mental fatigue of construction equipment operators has not been reported in the literature. Although the application of facial features has been widespread in other domains, such as drivers and other occupation scenarios, their ecological validity for construction excavator operators remains a knowledge gap. This study proposed employing geometric measurements of facial features to detect mental fatigue in construction equipment operators' facial features. In this study, seventeen operators performed excavation operations. Mental fatigue was labeled subjectively and objectively using NASA-TLX scores and EDA values. Based on geometric measurements, facial features (eyebrow, mouth outer, mouth corners, head motion, eye area, and face area) were extracted. : The results showed that there was significant difference in the measured metrics for high fatigue compared to low fatigue. Specifically, the most noteworthy variation was for the eye and face area metrics, with mean differences of 45.88% and 26.9%, respectively. The findings showed that geometrical measurements of facial features are a useful, noninvasive approach for detecting the mental fatigue of construction equipment operators.

中文翻译：

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通过面部特征的几何测量无创检测建筑设备操作员的精神疲劳

：施工设备长时间运行可能会导致精神疲劳，从而增加发生人为失误相关事故的机会以及操作人员的健康状况不佳。客观检测操作人员的精神疲劳对于降低事故风险、保障操作人员健康至关重要。脑电图、光电体积描记法、皮肤电活动和眼球追踪技术已被用来缓解这个问题。这些技术是侵入式可穿戴传感器，可能会引起刺激和不适。面部特征的几何测量可以作为一种非侵入性的替代方法。其在检测建筑设备操作人员精神疲劳中的应用尚未见文献报道。尽管面部特征的应用已广泛应用于其他领域，例如驾驶员和其他职业场景，但其对于建筑挖掘机操作员的生态有效性仍然存在知识差距。本研究提出采用面部特征的几何测量来检测建筑设备操作员面部特征的精神疲劳。在这项研究中，十七名操作员进行了挖掘作业。使用 NASA-TLX 评分和 EDA 值主观和客观地标记精神疲劳。基于几何测量，提取面部特征（眉毛、嘴巴外侧、嘴角、头部运动、眼睛区域和面部区域）。 ：结果表明，与低度疲劳相比，高度疲劳的测量指标存在显着差异。具体来说，最值得注意的变化是眼睛和面部面积指标，平均差异分别为 45.88% 和 26.9%。研究结果表明，面部特征的几何测量是检测建筑设备操作员精神疲劳的一种有用的、非侵入性的方法。