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Using Causal Trees to Estimate Personalized Task Difficulty in Post-Stroke Individuals

Dennler, Nathaniel, Nikolaidis, Stefanos, Matarić, Maja

arXiv.org Artificial Intelligence

Adaptive training programs are crucial for recovery post stroke. However, developing programs that automatically adapt depends on quantifying how difficult a task is for a specific individual at a particular stage of their recovery. In this work, we propose a method that automatically generates regions of different task difficulty levels based on an individual's performance. We show that this technique explains the variance in user performance for a reaching task better than previous approaches to estimating task difficulty.

  estimate personalized task difficulty, participant, task difficulty, (13 more...)
2403.04109
  Genre: Research Report (0.83)
  Industry: Education (0.69)