首页 /研究 /Evaluating Mental Workload Measures in Human-robot Collaborative Assembly
HRI

Evaluating Mental Workload Measures in Human-robot Collaborative Assembly

Xiranai Dai, Gaia Vitrano

发表年份
2024
引用次数
2

摘要

This study assesses the efficacy of various cognitive workload metrics in human-robot collaborative assembly tasks using a systematic review and meta-analysis of literature from Scopus and Web of Science. Key metrics evaluated include physiological (EEG, GSR, HRV), subjective (NASA-TLX), and behavioral measures. Findings reveal that physiological measures, notably EEG and GSR (e.g., EEG with $\mathrm{p}\lt \mathrm{0. 0 1}$ and GSR with $\mathrm{p}\lt \mathrm{0. 0 1}$), are highly sensitive to changes in cognitive workload but are constrained by technical challenges. Subjective assessments, particularly NASA-TLX, provide valuable perceptual insights ($\mathrm{p}\lt0.05$), while behavioral metrics reflect task performance impacts. Integrating these metrics is essential for accurate cognitive workload assessments in industrial settings, enhancing both the understanding and management of cognitive demands.

关键词

WorkloadComputer scienceHuman–robot interactionRobotHuman–computer interactionMeasure (data warehouse)Artificial intelligenceOperating systemData mining

相关论文

查看 HRI 分类全部论文