Abstract:
This study assesses the efficacy of various cognitive workload metrics in human-robot collaborative assembly tasks using a systematic review and meta-analysis of literatu...Show MoreMetadata
Abstract:
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.
Published in: 2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
Date of Conference: 15-18 December 2024
Date Added to IEEE Xplore: 04 February 2025
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