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Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

机译:使用皮带式跑步机评估人体运动适应的一般性

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摘要

Understanding the mechanisms underlying locomotor learning helps researchers and clinicians optimize gait retraining as part of motor rehabilitation. However, studying human locomotor learning can be challenging. During infancy and childhood, the neuromuscular system is quite immature, and it is unlikely that locomotor learning during early stages of development is governed by the same mechanisms as in adulthood. By the time humans reach maturity, they are so proficient at walking that it is difficult to come up with a sufficiently novel task to study de novo locomotor learning. The split-belt treadmill, which has two belts that can drive each leg at a different speed, enables the study of both short- (i.e., immediate) and long-term (i.e., over minutes-days; a form of motor learning) gait modifications in response to a novel change in the walking environment. Individuals can easily be screened for previous exposure to the split-belt treadmill, thus ensuring that all experimental participants have no (or equivalent) prior experience. This paper describes a typical split-belt treadmill adaptation protocol that incorporates testing methods to quantify locomotor learning and generalization of this learning to other walking contexts. A discussion of important considerations for designing split-belt treadmill experiments follows, including factors like treadmill belt speeds, rest breaks, and distractors. Additionally, potential but understudied confounding variables (e.g., arm movements, prior experience) are considered in the discussion.
机译:了解运动学习的潜在机制有助于研究人员和临床医生优化步态再训练,作为运动康复的一部分。但是,研究人类运动学习可能具有挑战性。在婴儿期和儿童时期,神经肌肉系统还很不成熟,在发育的早期,运动学习不太可能受成年时相同的机制支配。当人类成熟时,他们已经非常熟练地行走,以致于很难提出足够新颖的任务来研究从头运动学习。皮带分离式跑步机具有两条皮带,可以以不同的速度驱动每条腿,因此可以研究短期(即即时)和长期(即几分钟内;一种运动学习方式)步态变化以适应步行环境中的新变化。可以很容易地对个体进行筛查,以了解以前是否接触过皮带式跑步机,从而确保所有实验参与者都没有(或同等的)先前经验。本文介绍了一种典型的带式跑步机适应协议,该协议结合了测试方法以量化运动学习并将此学习推广到其他步行环境。接下来讨论设计皮带式跑步机实验的重要考虑因素,包括跑步机皮带速度,休息时间和干扰因素等因素。另外,在讨论中考虑了潜在但未被充分研究的混淆变量(例如,手臂运动,先前的经验)。

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