Enhancing Trust Examinations with Neural Measures during Human–Robot Collaboration under Cognitive Fatigue
Trust in human–robot collaboration (HRC) is influenced by situational factors, such as human states of fatigue and robot performance (e.g., reliability). In industrial settings, operators are often fatigued which increases attentional demands. This sustained mental demand may potentially alter the trusting behaviors of the operator. Whether this happens, and why, are currently unexplored. While most studies have relied on self-reports, recent advancements in neuroergonomics have enabled the assessment of neural signatures of trust. We hypothesize that shedding light on the neural mechanisms during HRC, under varying trust states, may provide additional insights (beyond trust perceptions) into the subconscious cognitive or affective states associated with trust under cognitive fatigue. To test this hypothesis, we conducted an HRC experiment on 16 sex-balanced participants in which trust was manipulated via robot reliability at two sessions (fatigue session and no-fatigue session). We monitored brain activity, heart rate variability (HRV), performances, and subjective experiences to investigate the effect of cognitive fatigue and robot reliability on trust metrics in HRC. A significant main effect of cognitive fatigue and reliability was observed on brain activations, functional and effective connectivity, HRV, subjective response, and performance. While most measures were sensitive to changes in cognitive fatigue and reliability, only neural responses revealed interactions between reliability, cognitive fatigue, and sex. Anterior prefrontal cortex (APFC)–left dorsolateral prefrontal cortex (LDLPFC) connection strength decreased with unreliable robot behavior in non-fatigued states but unexpectedly increased when fatigue was present. This suggests a neural strategy shift involving greater top-down influence from executive to motivational regions to exert more mental effort in challenging HRC conditions. Insights from this investigation can advance objective trust measures under cognitive fatigue states and help design better collaborations.
Authors
- Sarah K. Hopko (ORCID: https://orcid.org/0000-0003-4713-4455)
- Prabhakar R. Pagilla (ORCID: https://orcid.org/0000-0001-8553-4658)
- Ranjana K. Mehta (ORCID: https://orcid.org/0000-0002-8254-8365)
- Aakash Yadav (ORCID: https://orcid.org/0000-0003-2712-5615)
Institutions
- University of Wisconsin System (US)
- University of Wisconsin–Madison (US)
- Texas A&M University (US)
Publication Details
- Journal
- ACM Transactions on Human-Robot Interaction
- Published
- 2025-10-31
- DOI
- https://doi.org/10.1145/3773905
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00