在地震模拟中将人格特征与急性压力反应相关联:HRV和RESP分析
Jing Li1, Jingzheng Zhu1, Cheng Guan2
1School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing, China.
概括
这项研究表明,人格在模拟地震期间显著影响急性压力反应 (ASR). 结合CNN和LSTM的深度学习模型有效地根据人格特征预测ASR,帮助应对灾害的准备.
科学领域:
- 心理学 心理学 心理学
- 灾害管理 灾害管理
- 生物医学工程 生物医学工程
背景情况:
- 准确的地震预测仍然是难以捉摸的,而急性应激反应 (ASR) 可以在早期警告期间阻碍有效的疏散.
- 了解个体个性与ASR之间的联系对于改善灾害应对策略至关重要.
研究的目的:
- 在模拟地震期间调查人格特征和急性压力反应 (ASR) 之间的相关性.
- 开发基于人格特征的ASR预测模型.
- 通过基于人格的压力洞察来加强灾害管理和疏散规划.
主要方法:
- 使用陈慧-60气质尺度和DISC人格清单进行人格评估.
- 在体验厅中模拟地震,以收集生理数据 (心率变化,呼吸).
- 应用多变量方差分析 (MANOVA),集群方法和深度学习模型 (CNN-LSTM) 来进行数据分析和预测.
主要成果:
- 在不同的人格群体和不同地震阶段观察到ASR的显著差异.
- 聚类方法成功量化了时间应激反应,并标记了不同人格的ASR水平.
- 根据CNN-LSTM模型,基于人格的ASR预测的AUC为0.795,超过了基于个体的预测 (AUC为0.72).
结论:
- 人格是影响地震期间急性压力反应的重要因素.
- 基于个性的深度学习方法提供了一个有前途的方法来预测和管理地震相关的压力.
- 这项研究为个性化灾害准备和更有效的公共疏散策略提供了基础.
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