Learning, not adaptation, characterizes stroke motor recovery: evidence from kinematic changes induced by robot-assisted therapy in trained and untrained task in the same workspace.
Learning, not adaptation, characterizes stroke motor recovery: evidence from kinematic changes induced by robot-assisted therapy in trained and untrained task in the same workspace.
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学习而不是适应性的是中风运动恢复的特征：在同一工作空间中，机器人辅助治疗在训练有素和未经训练的任务中引起的运动学变化的证据。
DOI：
10.1109/tnsre.2011.2175008
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发表时间：
2012-01
期刊：
影响因子：
--
通讯作者：
Hogan N
中科院分区：
文献类型：
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作者：
Dipietro L;Krebs HI;Volpe BT;Stein J;Bever C;Mernoff ST;Fasoli SE;Hogan N
美国心脏协会和VA/DoD都支持上肢机器人介导的中风康复治疗。然而，我们还不知道如何针对特定患者的需求优化治疗。在这里，我们探讨我们是否必须训练患者的每一个功能任务，他们必须在他们的日常生活活动中执行，或者使患者能够执行一类任务，并有治疗师帮助他们以后在翻译观察到的收益到日常生活活动。前者意味着运动适应是运动恢复的更好模式。后者意味着运动学习（允许泛化）是运动恢复的更好模型。我们通过13个指标量化了158名恢复中的中风患者进行的训练和未训练的运动，包括运动平滑度和子运动。在训练和未经训练的运动中都观察到了改善，这表明泛化发生了。我们的研究结果表明，随着运动恢复的进展，大脑在一个更像运动学习而不是运动适应的过程中重建了任务的内部表征。我们的研究结果强调了治疗算法设计的可能改进，表明稀疏活动集训练应该足以超过详尽的任务特定训练集。
Both the American Heart Association and the VA/DoD endorse upper-extremity robot-mediated rehabilitation therapy for stroke care. However, we do not know yet how to optimize therapy for a particular patient’s needs. Here, we explore whether we must train patients for each functional task that they must perform during their activities of daily living or alternatively capacitate patients to perform a class of tasks and have therapists assist them later in translating the observed gains into activities of daily living. The former implies that motor adaptation is a better model for motor recovery. The latter implies that motor learning (which allows for generalization) is a better model for motor recovery. We quantified trained and untrained movements performed by 158 recovering stroke patients via 13 metrics, including movement smoothness and submovements. Improvements were observed both in trained and untrained movements suggesting that generalization occurred. Our findings suggest that, as motor recovery progresses, an internal representation of the task is rebuilt by the brain in a process that better resembles motor learning than motor adaptation. Our findings highlight possible improvements for therapeutic algorithms design, suggesting sparse-activity-set training should suffice over exhaustive sets of task specific training.