长时间连续的人机交互的认知影响:基于心理状态的自适应接口的案例
Marcel F Hinss1,2, Anke M Brock2, Raphaëlle N Roy1
1Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO), Toulouse, France.
Frontiers in neuroergonomics
|January 18, 2024
概括
基于心理状态的自适应系统可以减轻操作员在长时间工作期间的疲劳和认知衰退. 通过监控操作员指标,这些系统调整交互,以确保复杂的操作环境中的安全和效率.
科学领域:
- 神经机能学是指神经机能学.
- 人类因素 人类因素
- 人与计算机的交互
背景情况:
- 复杂系统 (航空,汽车,核) 的长时间运行会导致操作员精神疲劳,认知灵活性,注意力和情境意识下降.
- 这些认知退化损害了关键操作的安全性和效率.
- 基于心理状态的适应性系统为减轻这些风险提供了潜在的解决方案.
研究的目的:
- 为设计基于精神状态的适应性系统提供关键考虑的概述.
- 促进这些系统的应用,以便长时间连续使用.
- 为了提高人机交互的安全性和效率.
主要方法:
- 使用一系列指标推断操作员的心理状态:操作员独立 (天气,时间),行为 (反应时间,车道偏差) 和生理 (EEG,心脏活动).
- 根据检测到的认知状态调整系统交互,利用机器学习估计.
- 修改信息的呈现方式,模式,刺激的突出性和任务安排,作为潜在的适应.
主要成果:
- 适应性系统可以动态调整操作员的认知状态.
- 机器学习可以实现个性化和上下文意识的适应.
- 多种指标的整合提供了对操作员心理状态的全面评估.
结论:
- 基于心理状态的自适应系统对于管理操作员在苛刻,长时间任务中的表现至关重要.
- 需要进一步的研究和仔细的设计来优化这些系统用于现实世界的应用.
- 这些系统对改善各种行业的人机交互的安全性和效率具有显著的前景.
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