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Advancing Construction Hazard Recognition through Neuroscience: Measuring Cognitive Response to Hazards Using Functional Near Infrared Spectroscopy

机译:通过神经科学推进对建筑危害的识别:使用功能性近红外光谱仪测量对危害的认知反应

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Robust hazard recognition is critical to reducing the estimated 1,000 fatalities and 230,000 injuries in the U.S. construction industry each year. By adopting methods from neuroscience, this research develops a more accurate method to measure and differentiate cognitive response during hazard recognition tasks. The hypothesis is that the temporal response and cognitive load are influenced by hazard energy source and severity. In a pilot study, engineering students (n = 14) were shown 24 images total in varying (low to high) severity and hazard type (i.e., gradational, mechanical, electrical, and chemical). The results find that the time to peak cognitive activation (i.e., response time) increases as hazard severity decreases. The type of hazardous energy (gravitational, electrical, mechanical, and chemical) also significantly influences the time to peak response. Participants were found to respond more quickly to gravitational hazards while most slowly to chemical hazards. The cognitive energy (i.e., peak or mean cognitive effort) associated with specific regions in the brain such as attention, working memory, topographic memory, and emotional stimuli varied significantly based on hazard type. Most notably, images with severity of gravitational hazards produced a significant increase in activation in the part of the brain associated with topographic memory and motor initiation. Unexpectedly, high severity chemical hazards, were observed to have higher mean activation in the area of the brain associated with unpleasant emotion processing and odor detection. These results serve as a proof of concept that both hazard severity and type are processed using distinctly different regions of the brain. Measuring cognitive demand and localization of brain activation can provide more detailed understanding of the hazard recognition time and neural processing patterns. Future research can begin to test interventions, such as training and mnemonics, to increase hazard recognition response time, attention, and working memory.
机译:强大的危险承认对于减少每年美国建筑业的估计的1,000个死亡率和23万次伤害至关重要。通过采用神经科学的方法,这项研究开发了一种更准确的方法来测量和区分危险识别任务期间的认知响应。假设是时间响应和认知载荷受到危害能源和严重程度的影响。在试验研究中,工程学生(n = 14)被示出了24张图像,变化(低至高)严重程度和危险型(即,渐进式,机械,电气和化学)。结果发现,随着危险严重程度降低,峰值认知激活(即响应时间)的时间增加。危险能量(引力,电气,机械和化学)的类型也显着影响了峰值响应的时间。参与者被发现更快地反应引力危害,同时最慢地避免化学危害。与大脑中的特定区域相关的认知能量(即峰值或平均认知努力),如注意,工作记忆,地形记忆和情绪刺激,基于危险型显着变化。最值得注意的是,具有引力危害严重程度的图像在与地形记忆和电动机启动相关的大脑中产生的显着增加。出乎意料地,观察到高度严重的化学危害,在与令人难闻的情绪加工和气味检测相关的大脑中具有更高的平均活化。这些结果作为概念证据,即使用脑的明显不同区域处理危险严重程度和类型。测量脑激活的认知需求和本地化可以提供更详细的理解危险识别时间和神经处理模式。未来的研究可以开始测试干预措施,例如培训和助记符,以增加危险识别响应时间,关注和工作记忆。

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