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.

翻译：自适应训练程序对于中风后康复至关重要。然而，开发自动调整的程序取决于量化特定个体在康复特定阶段的任务难度。本研究提出了一种方法，该方法能基于个体表现自动生成不同任务难度水平的区域。我们证明，与先前估计任务难度的方法相比，该技术能更好地解释用户在执行伸手任务时的表现差异。