在n-back任务中对并发的认知负荷测量的比较
Prarthana Pillai1, Balakumar Balasingam1, Arunita Jaekel2
1Department of Electrical and Computer Engineering, University of Windsor, 401 Sunset Avenue, Windsor, Ontario, N9G 3P4, Canada.
Applied ergonomics
|February 6, 2024
概括
测量人类的认知负载是具有挑战性的,因为它不是直接可量化的. 这项研究引入了一种新的性能指标,即信号与噪声比,以客观地比较不同的认知负载指标.
科学领域:
- 人与计算机的交互
- 认知心理学 认知心理学
- 性能测量 性能测量 性能测量 性能测量 性能测量
背景情况:
- 认知负载在驾驶,航空和医疗保健等各个领域显著影响人类表现.
- 认知过载和过载都会导致错误,效率下降和安全风险.
- 目前评估认知负载的方法是间接的,依赖于生理,行为,性能或主观数据,缺乏客观的比较标准.
研究的目的:
- 提出一种新的,客观的绩效指标,用于评估和比较各种认知负载指标.
- 为了解决缺乏标准化的方法来评估不同认知负载指标的有效性.
- 为了能够更好地理解和选择适当的认知负载测量技术.
主要方法:
- 基于信号与噪声比的性能指标被开发用于比较认知负载指标.
- 使用这个指标评估了多个认知负载指标.
- 从28名参与者中收集了数据,他们执行了不同难度的n-back任务.
主要成果:
- 拟议的信号噪声比指标提供了一个统一的尺度,用于比较不同的认知负载评估方法.
- 该研究成功地比较了同一尺度上的各种认知负载指标.
- 结果表明,拟议的绩效评估方法对认知负载指标的个别评估具有实用性.
结论:
- 开发的信号噪声比指标提供了一个客观的方法来评估认知负载指标的性能.
- 这种方法可以帮助研究人员和从业人员选择最有效的认知负载评估工具.
- 对认知负载指标的客观比较对于改善复杂系统中的人类性能和安全至关重要.
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