Towards a robot-based multimodal framework to assess the impact of fatigue on user behavior and performance: a pilot study

Akilesh Rajavenkatanarayanan, Varun Kanal, K. Tsiakas, J. Brady, Diane Calderon, G. Wylie, F. Makedon
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引用次数: 6

Abstract

Objective: In this paper, we present a multimodal robot-based framework to investigate how physical and mental fatigue affect task performance, and how it relates to subjective self-reports. Methodology: In this pilot study, seven healthy participants underwent the robot-based assessment. In each session, the participants performed a series of reaching tasks, including a task with cognitive demands, by moving the end effector of the Barrett WAM arm in the direction of the virtual targets displayed on a computer screen. Multimodal data, including EEG, EMG and user performance data like reaction time, number of targets, trajectory of the robot path, were recorded for further analysis. Results: Based on the analysis of subjective user self-report and objective task performance metrics, we observe that the user's perceived level of task difficulty increased over time while objective task performance also improved over time. We speculate that this might be due to the effect of fatigue on the user's perception of task difficulty. Conclusion: Further studies are required, with a more diverse population, to understand the impact of fatigue on the user's cognitive and physical ability. We must also evaluate how contextual parameters may affect task performance and fatigue.
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迈向基于机器人的多模态框架,以评估疲劳对用户行为和性能的影响:一项试点研究
目的:在本文中,我们提出了一个基于多模态机器人的框架来研究身心疲劳如何影响任务表现,以及它与主观自我报告的关系。方法:在这项初步研究中,7名健康参与者接受了基于机器人的评估。在每一个环节中,参与者都要完成一系列的伸手任务,其中包括一项有认知需求的任务,他们需要将巴雷特WAM手臂的末端执行器朝电脑屏幕上显示的虚拟目标的方向移动。记录多模态数据,包括脑电图、肌电图和反应时间、目标数量、机器人路径轨迹等用户性能数据,以便进一步分析。结果:基于主观用户自我报告和客观任务绩效指标的分析,我们观察到用户的任务难度感知水平随着时间的推移而增加,客观任务绩效也随着时间的推移而提高。我们推测这可能是由于疲劳对用户任务难度感知的影响。结论:要了解疲劳对使用者认知和身体能力的影响,还需要进一步的研究,需要更多样化的人群。我们还必须评估上下文参数如何影响任务表现和疲劳。
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