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<p>Mental state monitoring methods are particularly promising for Human-Robot Interaction (HRI). Indeed, evaluating users’ mental states in real-time using portable acquisition devices would help to build a better model of the ongoing interaction. Yet, the study of human mental state requires standardized inductive tasks in order to produce a robust ground truth for baseline measurements. Hence cognitive effort is often induced using dual-task paradigms, where the robot has a limited impact in the inductive process and that do not allow to modulate human mental state using the robot’s behavior. To address such an issue, this study proposes to validate three inductive tasks adapted from neuropsychology to HRI: the N-Back Task, the Sternberg Task, and the Cognitive Shifting Task. Each task was designed to induce cognitive effort using the robot’s behavior only, avoiding the need for dual-task paradigms. The validation involved 24 participants per task, performing both the original letter-based version and the robotic one with robot video clips. Expected outcomes included a decreased accuracy, as well as increased response times and subjective effort at higher difficulty levels. Results confirmed that the robotic tasks effectively induce cognitive effort, though they also introduce stronger cognitive demands than traditional letter-based tasks. The validated tasks provide novel robust tools for HRI research, with all resources and data openly accessible for community use, therefore paving the way for promoting reproducibility and replicability of HRI research.</p>

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A Set of Robotic Inductive Tasks to Monitor Human Cognitive Effort

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月27日

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  • Mathias Rihet,
  • Aurélie Clodic,
  • Guillaume Sarthou,
  • Anouk Sanmarti-Decool,
  • Raphaëlle N. Roy

摘要

Mental state monitoring methods are particularly promising for Human-Robot Interaction (HRI). Indeed, evaluating users’ mental states in real-time using portable acquisition devices would help to build a better model of the ongoing interaction. Yet, the study of human mental state requires standardized inductive tasks in order to produce a robust ground truth for baseline measurements. Hence cognitive effort is often induced using dual-task paradigms, where the robot has a limited impact in the inductive process and that do not allow to modulate human mental state using the robot’s behavior. To address such an issue, this study proposes to validate three inductive tasks adapted from neuropsychology to HRI: the N-Back Task, the Sternberg Task, and the Cognitive Shifting Task. Each task was designed to induce cognitive effort using the robot’s behavior only, avoiding the need for dual-task paradigms. The validation involved 24 participants per task, performing both the original letter-based version and the robotic one with robot video clips. Expected outcomes included a decreased accuracy, as well as increased response times and subjective effort at higher difficulty levels. Results confirmed that the robotic tasks effectively induce cognitive effort, though they also introduce stronger cognitive demands than traditional letter-based tasks. The validated tasks provide novel robust tools for HRI research, with all resources and data openly accessible for community use, therefore paving the way for promoting reproducibility and replicability of HRI research.