李向洲,任嘉炜.基于出错认知模型的矿山救援AR头盔界面交互设计研究[J].包装工程,2024,(16):463-470. |
基于出错认知模型的矿山救援AR头盔界面交互设计研究 |
AR Helmet Interface Interaction Design for Mine Rescue Based on Error Cognition Models |
投稿时间:2024-03-16 |
DOI:10.19554/j.cnki.1001-3563.2024.16.051 |
中文关键词: AR头盔 矿山救援 出错认知模型 生理反应实验 界面交互 |
英文关键词: AR helmet mine rescue error cognition model physiological reaction experiment interface interaction |
基金项目: |
|
摘要点击次数: |
全文下载次数: |
中文摘要: |
目的 为更好地减少矿山救援过程中的出错行为,提高矿山救援的成效。方法 从出错认知理论出发,分析救援场景下对任务中相关信息的视觉认知行为,从认知加工的四个过程分析得出矿山救援场景下的出错因子,以矿山救援场景AR交互信息为研究对象进行出错因子认知模拟实验,获得矿山救援场景相较于其他场景具有特殊性的AR头盔交互界面信息设计影响要素。结论 依据实验结论,对矿山救援AR头盔交互界面开展信息设计,以提高救援效率,最终输出初步的交互设计方案,通过降低交互界面的认知难度,提高救援人员的反应速度和准确度,保证该系统可以有效降低任务失败率。 |
英文摘要: |
The work aims to reduce operational errors and improve the effectiveness of mine rescue operations. Based on the error cognition theory, visual cognitive behaviors associated with different types of information in rescue tasks were analyzed. By examining the four cognitive processing stages, error factors specific to mine rescue scenarios were identified. Error factor cognitive simulation experiments were conducted with AR interactive information in mine rescue settings to determine the design elements that were particularly influential for AR helmet interfaces in these scenarios. Based on the experimental results, information design for the AR helmet interface is developed to output the preliminary interactive design scheme, so as to reduce cognitive difficulty, enhance response speed and accuracy, and ensure that the system effectively lowers the task failure rate. |
查看全文
查看/发表评论 下载PDF阅读器 |
关闭 |