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Error Based Learning for Restoring Gait Symmetry Post-Stroke

Error Based Learning for Restoring Gait Symmetry Post-Stroke
基于误差的学习用于恢复中风后的步态对称性
批准号:
8243120
负责人:
MICHAEL D LEWEK
金额:
$21.87万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-01-15 至 2013-12-31

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项目成果

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中文摘要
翻译
描述(由申请人提供):卒中后行走的特征是步态速度降低和存在肢体间时空不对称。这些步长和站立时间的不对称可能是能量效率低下的,挑战平衡控制,增加福尔斯和受伤的风险,并限制功能性活动。目前改善步态的康复是基于两种竞争的运动学习策略之一:最大限度地减少或增加训练过程中的对称性错误。传统的康复通常涉及在跑步机上行走,而治疗师试图在训练过程中尽量减少对称性错误。虽然这种方法可以成功地提高步态速度,但它不会产生长期的对称性变化。相反,增加或放大的对称性误差已产生的分裂带跑步机上行走的皮带设置在不同的固定速度。虽然这种方法产生了“后效”,导致短时间内步长对称,但有证据表明中风患者长期学习,它对站立时间不对称没有影响。我们建议患者需要对称性错误的实时本体感受反馈,以便他们积极参与学习过程。对于这个项目,我们开发并验证了一种新颖的,响应,“闭环”控制系统,使用分裂带仪表跑步机,不断调整带速度的差异成比例的病人的电流不对称。使用这个系统,我们可以逐步增加或减少不对称性,以确定哪种运动学习策略产生最大的地上时空对称性的变化。采用随机对照设计,54名站立时间和/或步长不对称的慢性卒中患者将在跑步机上接受6周(18次)运动训练,其中包括:1)不对称增强,2)不对称最小化,或3)对照条件(传统跑步机训练)。我们将在基线、训练3周和6周以及4周随访时使用GAITRite垫测量地上行走期间的时空对称性,以确定每种策略6周训练的累积效果。此外,我们将证明改善时空对称性对慢性卒中患者的步态效率、平衡、步态速度、耐力、生活质量和身体活动的影响。根据我们的初步数据和其他人的工作,我们的中心假设是,错误增强策略将产生最大的运动学习,通过6周运动训练后和4周随访时的地上步态对称性来测量。此外,我们预计这种创新的运动训练方法将改善中风患者的对称步态,从而提高步态效率,速度和耐力,改善平衡,增加身体活动,以及训练后更好的生活质量。 公共卫生相关性:每年有780,000人中风,其中许多人留下缓慢,不对称的步行模式。该项目将评估两种竞争性运动学习方法的有效性,以恢复对称步态,从而更快,更有效,更安全地行走。
英文摘要
DESCRIPTION (provided by applicant): Walking after stroke is characterized by reduced gait speed and the presence of interlimb spatiotemporal asymmetry. These step length and stance time asymmetries can be energy inefficient, challenge balance control, increase the risk of falls and injury, and limit functional mobility. Current rehabilitation to improve gait is based on one of two competing motor learning strategies: minimizing or augmenting symmetry errors during training. Conventional rehabilitation often involves walking on a treadmill while therapists attempt to minimize symmetry errors during training. Although this approach can successfully improve gait speed, it does not produce long-term changes in symmetry. Conversely, augmenting or amplifying symmetry errors has been produced by walking on a split belt treadmill with the belts set at different fixed speeds. While this approach produced an 'after-effect' resulting in step length symmetry for short periods of time, with some evidence of long term learning in people with stroke, it had no influence on stance time asymmetry. We propose that patients need real-time proprioceptive feedback of symmetry errors so that they are actively engaged in the learning process. For this project, we developed and validated a novel, responsive, 'closed loop' control system, using a split-belt instrumented treadmill that continuously adjusts the difference in belt speeds to be proportional to the patient's current asymmetry. Using this system, we can either augment or minimize asymmetry on a step-by-step basis to determine which motor learning strategy produces the largest change in overground spatiotemporal symmetry. Using a randomized controlled design, 54 persons with chronic stroke who have stance time and/or step length asymmetry will receive 6 weeks (18 sessions) of locomotor training on a treadmill with either: 1) Asymmetry Augmentation, 2) Asymmetry Minimization, or 3) a Control condition (conventional treadmill training). We will measure spatiotemporal symmetry during overground walking using a GAITRite mat, at baseline, at 3 and 6 weeks of training, and at a 4-week follow-up to ascertain the cumulative effect of 6 weeks of training with each strategy. Additionally, we will demonstrate the effect of improved spatiotemporal symmetry on gait efficiency, balance, gait speed, endurance, quality of life, and physical activity in people with chronic stroke. Based on our preliminary data and the work of others, our central hypothesis is that the error augmentation strategy will produce the greatest motor learning, measured by overground gait symmetry after 6-weeks of locomotor training and at 4-week follow-up. Further, we expect that this innovative locomotor training approach will improve symmetric gait for people with stroke leading to increased gait efficiency, speed, and endurance, improved balance, greater physical activity, and better quality of life measures after training. PUBLIC HEALTH RELEVANCE: Many of the 780,000 people affected by stroke each year are left with slow, asymmetric walking patterns. The proposed project will evaluate the effectiveness of two competing motor learning approaches to restore symmetric gait for faster, more efficient, and safer walking.
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会议论文
Online Prediction of Gait Related Trips Post-Stroke
Online Prediction of Gait Related Trips Post-Stroke
Error Based Learning for Restoring Gait Symmetry Post-Stroke
Hip Angle and Limb Load Affect Reflexes Post-Stroke
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