论文标题
沉浸式虚拟环境中的危害识别：同时分析视觉搜索和脑电图模式的框架
Hazard recognition in an immersive virtual environment: Framework for the simultaneous analysis of visual search and EEG patterns
论文作者
论文摘要
事实证明，在危险的建筑环境中，不受管理的危害是伤害和事故的主要来源之一。危害识别对于实现有效的安全管理和减少危险工作场所的伤害和死亡至关重要。尽管如此，缺乏努力可以有效地帮助工人提高其危害识别能力。这项研究介绍了沉浸式虚拟环境（IVE）中的虚拟安全培训，以增强工人的危险识别能力。配备有眼线的工人（VR）设备的工人实际上识别出模拟的施工站点上的危害，而脑电波设备记录了大脑活动。该平台可以在视觉危害识别任务中分析工人的整体绩效，并确定需要为每个工人进行额外干预的危害。这项研究提供了有关在视觉危害识别过程中工人的大脑和眼睛如何同时起作用的新见解。提出的方法可以通过向工人提供个性化的反馈来将当前的安全培训计划纳入另一个水平。
Unmanaged hazards in dangerous construction environments proved to be one of the main sources of injuries and accidents. Hazard recognition is crucial to achieve effective safety management and reduce injuries and fatalities in hazardous job sites. Still, there has been lack of effort that can efficiently assist workers in improving their hazard recognition skills. This study presents virtual safety training in an Immersive Virtual Environment (IVE) to enhance worker's hazard recognition skills. A worker wearing a Virtual Reality (VR) device, that is equipped with an eye-tracker, virtually recognizes hazards on simulated construction sites while a brainwave-sensing device records brain activities. This platform can analyze the overall performance of the workers in a visual hazard recognition task and identify hazards that need additional intervention for each worker. This study provides novel insights on how a worker's brain and eye act simultaneously during a visual hazard recognition process. The presented method can take current safety training programs into another level by providing personalized feedback to the workers.
