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
基本信息
- 批准号:8243120
- 负责人:
- 金额:$ 21.87万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-01-15 至 2013-12-31
- 项目状态:已结题
- 来源:
- 关键词:AffectClinicalControl GroupsCuesDataEducational InterventionEffectivenessEquilibriumFeedbackGaitImpairmentIndividualInjuryKnowledgeLearningLeftLengthLimb structureLocomotionMeasuresMetabolicMethodsMovementOutcome MeasurePatientsPatternPerformancePersonsPhysical activityProcessProtocols documentationQuality of lifeRandomizedRehabilitation therapyRelative (related person)RoleSeveritiesSpeedStrokeSystemTactileTestingTimeTrainingVisualWalkingWorkbasechronic strokecohortcostdesignexperiencefall riskfollow-upimprovedinnovationinstrumentmotor learningnovelpost strokespatiotemporaltreatment effect
项目摘要
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.
描述(由申请人提供):中风后行走的特点是步态速度减慢和肢间时空不对称的存在。这些步长和站姿时间的不对称可能会导致能量效率低下,挑战平衡控制,增加跌倒和受伤的风险,并限制功能性活动。目前改善步态的康复是基于两种相互竞争的运动学习策略之一:在训练过程中最小化或增加对称误差。传统的康复通常包括在跑步机上行走,而治疗师试图在训练过程中尽量减少对称误差。虽然这种方法可以成功地提高步态速度,但它不会对对称性产生长期的改变。相反,在分离式皮带跑步机上行走,皮带设置在不同的固定速度,会增加或放大对称误差。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,但它对站立时间不对称没有影响。我们建议患者需要对称误差的实时本体感觉反馈,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、反应灵敏的“闭环”控制系统,该系统使用分离式皮带设备跑步机,该跑步机可以不断调整皮带速度的差异,使其与患者当前的不对称性成正比。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在地上时空对称性方面产生最大的变化。采用随机对照设计,54例站立时间和/或步长不对称的慢性中风患者将在跑步机上接受6周(18次)的运动训练,其中包括:1)增强不对称,2)最小化不对称,或3)控制条件(传统跑步机训练)。我们将测量使用GAITRite垫地行走时的时空对称性,在基线、3周和6周的训练以及4周的随访中,以确定每种策略6周训练的累积效果。此外,我们将展示改善时空对称性对慢性中风患者的步态效率、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,误差增强策略将产生最大的运动学习,通过6周运动训练和4周随访后的地面步态对称性来衡量。此外,我们期望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,并在训练后改善生活质量。
项目成果
期刊论文数量(0)
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MICHAEL D LEWEK其他文献
MICHAEL D LEWEK的其他文献
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{{ truncateString('MICHAEL D LEWEK', 18)}}的其他基金
Online Prediction of Gait Related Trips Post-Stroke
中风后步态相关行程的在线预测
- 批准号:
10022146 - 财政年份:2019
- 资助金额:
$ 21.87万 - 项目类别:
Online Prediction of Gait Related Trips Post-Stroke
中风后步态相关行程的在线预测
- 批准号:
9895282 - 财政年份:2019
- 资助金额:
$ 21.87万 - 项目类别:
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:
8410559 - 财政年份:2012
- 资助金额:
$ 21.87万 - 项目类别:
Hip Angle and Limb Load Affect Reflexes Post-Stroke
髋部角度和肢体负荷影响中风后的反射
- 批准号:
7054264 - 财政年份:2006
- 资助金额:
$ 21.87万 - 项目类别:
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