Error Based Learning for Restoring Gait Symmetry Post-Stroke

描述(申请人提供)：中风后行走的特征是步速减慢和肢体间存在时空不对称。这些步长和站立时间的不对称可能会降低能量效率，挑战平衡控制，增加跌倒和受伤的风险，并限制功能活动。目前改善步态的康复是基于两种相互竞争的运动学习策略之一：减少或增加训练中的对称误差。传统的康复治疗通常需要在跑步机上行走，而治疗师则试图在训练过程中尽量减少对称性误差。虽然这种方法可以成功地提高步态速度，但它不会产生对称性的长期变化。相反，在分体式皮带跑步机上行走，皮带设置在不同的固定速度上，会产生扩大或放大对称误差。虽然这种方法产生了导致短时间步长对称的后效，尽管有一些证据表明中风患者的长期学习，但它对站立时间不对称没有影响。我们认为，患者需要对对称误差进行实时本体感觉反馈，以便他们积极参与学习过程。在这个项目中，我们开发并验证了一种新颖的、响应迅速的“闭环”控制系统，它使用分体式皮带仪表式跑步机，不断调整皮带速度的差异，使之与患者当前的不对称性成比例。使用这个系统，我们可以在逐步的基础上增加或减少不对称性，以确定哪种运动学习策略在地面时空对称性方面产生最大的变化。采用随机对照设计，54名有站立时间和/或步长不对称的慢性中风患者将在跑步机上接受6周(18节)的运动训练，其中包括：1)不对称增强，2)不对称最小化，或3)控制条件(传统的跑步机训练)。我们将使用GAITRite垫子测量地面行走过程中的时空对称性，在基线、训练3周和6周以及4周随访时测量，以确定每种策略6周训练的累积效果。此外，我们还将展示改进的时空对称性对慢性中风患者的步态效率、平衡性、步速、耐力、生活质量和体力活动的影响。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周的运动训练后和4周的跟踪观察地面步态对称性来衡量。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，增加体力活动，并在训练后改善生活质量。 与公共健康相关：每年有78万人受到中风影响，其中许多人留下了缓慢、不对称的步行模式。拟议的项目将评估两种相互竞争的运动学习方法的有效性，以恢复对称步态，以实现更快、更有效和更安全的行走。

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.