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

2024-03-06Code Available0· sign in to hype

Nathaniel Dennler, Stefanos Nikolaidis, Maja Matarić

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Abstract

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.

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