Abstract
Although reliable automation can reduce a lot of the mental workload from humans, unreliable automation can increase cognitive workload and physiological changes. The objective of this study is to quantify the relationships between cognitive workload and electrodermal activities (EDA) in reliable and unreliable auto-proofreading tasks. Nineteen native English speakers participated in sentence correction tasks under a reliable or unreliable auto-proofreading support. During the tasks, the participants’ EDA signals were measured by using Empatica E4 wrist band and cognitive workload were evaluated by NASA-TLX indices including mental demand, effort, performance, and frustration level with 21-point scale. Overall, significant Pearson’s correlation coefficients were observed between the slope of EDA signal and mental demand (r = 0.477, p = 0.039), effort (r = 0.428, p = 0.068), performance (r = −0.500, p = 0.029), and frustration (r = 0.474, p = 0.040). Detailed analysis results are described in the paper. To our best knowledge, the linear relationships between physiological responses and cognitive workload are quantified in reliable and unreliable automation for the first time. The findings of this study can be applied to guide future research to understand human behavior in unreliable automation.
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Acknowledgements
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2015R1C1A1A01054148). We thank our undergraduate students at Texas A&M University – Corpus Christi who contributed significantly to this work, Tri Vo who developed the custom-build auto-proofreading system for this study and Celeste Branstrom who led the data collection and literature review.
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Park, J., Jeong, H., Park, J., Lee, B.C. (2019). Relationships Between Cognitive Workload and Physiological Response Under Reliable and Unreliable Automation. In: Nunes, I. (eds) Advances in Human Factors and Systems Interaction. AHFE 2018. Advances in Intelligent Systems and Computing, vol 781. Springer, Cham. https://doi.org/10.1007/978-3-319-94334-3_1
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DOI: https://doi.org/10.1007/978-3-319-94334-3_1
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