Cognitive effects of prolonged continuous human-machine interaction: The case for mental state-based adaptive interfaces

Hinss, Marcel F.; Brock, Anke; Roy, Raphaëlle N. · 2022 · OpenAlex-citations

DOI: 10.3389/fnrgo.2022.935092

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Summary

This review paper addresses the safety and efficiency risks associated with prolonged continuous human-machine interaction (HMI) in complex systems such as aviation, automotive, and nuclear power industries. The authors argue that extended operation leads to mental fatigue, which degrades critical cognitive functions including attention, cognitive flexibility, and situational awareness. To mitigate these risks, the paper advocates for mental state-based adaptive interfaces that dynamically adjust system behavior based on real-time estimates of the operator’s mental state, rather than relying solely on operator-independent metrics or manual adjustments. The authors conducted a non-systematic literature review using Google Scholar, ACM, and IEEE databases, prioritizing recent, peer-reviewed articles in English. The review synthesizes existing research to answer three key questions: the cognitive effects of prolonged use, methods for inferring operator mental states, and strategies for adaptive interface design. The analysis covers experimental studies on Time on Task (TOT) and mental fatigue, as well as theoretical frameworks for adaptive automation and physiological computing. The findings indicate that prolonged continuous use significantly impairs top-down (voluntary) attention while leaving bottom-up (involuntary) attention largely unaffected. Mental fatigue also increases task-switching costs, particularly when working memory is involved, and reduces situational awareness by impairing planning capabilities, systematic exploration, and the ability to adapt to changing rules. Additionally, fatigue leads to increased errors of omission and commission, as well as alert fatigue. The review highlights that adaptive interfaces must carefully manage operator trust to avoid both mistrust and over-reliance. Effective design requires transparency regarding the system’s performance, process, and purpose, along with mechanisms for operator override and accommodation of individual differences. The significance of this work lies in its comprehensive synthesis of the cognitive costs of prolonged HMI and the design requirements for adaptive systems. The authors conclude that mental state-based adaptive interfaces, utilizing physiological and behavioral metrics, offer a viable solution to maintain safety and efficiency during long-duration operations. However, they emphasize that successful implementation requires rigorous evaluation of secondary effects, such as potential decreases in situational awareness despite improved behavioral performance, and careful calibration to ensure calibrated trust. The paper calls for further research into trust dynamics in adaptive systems and the development of ecologically valid evaluation methods for complex, real-world applications.

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