Department of Mechanical Engineering, Temple University, 1947 N. 12th Street, Philadelphia, PA, 19122, USA.
J Neuroeng Rehabil. 2021 Feb 5;18(1):27. doi: 10.1186/s12984-021-00825-3.
Self-paced treadmills (SPT) can provide an engaging setting for gait rehabilitation by responding directly to the user's intent to modulate the external environment and internal effort. They also can improve gait analyses by allowing scientists and clinicians to directly measure the effect of an intervention on walking velocity. Unfortunately, many common SPT algorithms are not suitable for individuals with gait impairment because they are designed for symmetric gait patterns. When the user's gait is asymmetric due to paresis or if it contains large accelerations, the performance is diminished. Creating and validating an SPT that is suitable for asymmetric gait will improve our ability to study rehabilitation interventions in populations with gait impairment. The objective of this study was to test and validate a novel self-paced treadmill on both symmetric and asymmetric gait patterns and evaluate differences in gait kinematics, kinetics, and muscle activity between fixed-speed and self-paced treadmill walking.
We collected motion capture, ground reaction force data, and muscle activity from 6 muscles in the dominant leg during walking from 8 unimpaired subjects. In the baseline condition, the subjects walked at 3 fixed-speeds normalized to their leg length as Froude numbers. We developed a novel kinematic method for increasing the accuracy of the user's estimated walking velocity and compared our method against other published algorithms at each speed. Afterward, subjects walked on the SPT while matching their walking speed to a given target velocity using visual feedback of the treadmill speed. We evaluated the SPT by measuring steady-state error and the number of steps to reach the desired speed. We split the gait cycle into 7 phases and compared the kinematic, kinetic, and muscle activity between the fixed speed and self-paced mode in each phase. Then, we validated the performance of the SPT for asymmetric gait by having subjects walk on the SPT while wearing a locked-knee brace set to 0° on the non-dominant leg.
Our SPT enabled controlled walking for both symmetric and asymmetric gait patterns. Starting from rest, subjects were able to control the SPT to reach the targeted speeds using visual feedback in 13-21 steps. With the locked knee brace, subjects controlled the treadmill with substantial step length and step velocity asymmetry. One subject was able to execute a step-to gait and halt the treadmill on heel-strikes with the braced leg. Our kinematic correction for step-length outperformed the competing algorithms by significantly reducing the velocity estimation error at the tested velocities. The joint kinematics, joint torques, and muscle activity were generally similar between fixed-speed and self-paced walking. Statistically significant differences were found in 5 of 63 tests for joint kinematics, 2 of 63 tests for joint torques, and 9 of 126 tests for muscle activity. The differences that were statistically significant were not found across all speeds and were generally small enough to be of limited clinical relevance.
We present a validated method for implementing a self-paced treadmill for asymmetric and symmetric gaits. As a result of the increased accuracy of our estimation algorithm, our SPT produced controlled walking without including a position feedback controller, thereby reducing the influence of the controller on measurements of the user's true walking speed. Our method relies only on a kinematic correction to step length and step time which can support transfer to systems outside of the laboratory for symmetric and asymmetric gaits in clinical populations.
自步式跑步机（SPT）可以通过直接响应用户调节外部环境和内部努力的意图，为步态康复提供一个吸引人的环境。它们还可以通过允许科学家和临床医生直接测量干预对步行速度的影响来改善步态分析。不幸的是，许多常见的 SPT 算法不适合步态受损的个体，因为它们是为对称步态模式设计的。当用户的步态由于麻痹而不对称，或者如果它包含较大的加速度时，性能就会下降。创建和验证适合不对称步态的 SPT 将提高我们在步态受损人群中研究康复干预的能力。本研究的目的是测试和验证一种新的自步式跑步机在对称和不对称步态模式下的性能，并评估固定速度和自步式跑步机行走之间的步态运动学、动力学和肌肉活动的差异。
我们从 8 名未受损的受试者的优势腿收集运动捕捉、地面反力数据和 6 块肌肉的肌肉活动，在基线条件下，受试者以 3 种固定速度行走，以腿长归一化为弗劳德数。我们开发了一种新的运动学方法来提高用户估计的步行速度的准确性，并在每个速度下将我们的方法与其他已发表的算法进行了比较。之后，受试者在 SPT 上行走，同时使用跑步机速度的视觉反馈将他们的行走速度匹配到给定的目标速度。我们通过测量稳态误差和达到所需速度的步数来评估 SPT。我们将步态周期分为 7 个阶段，并在每个阶段比较固定速度和自步模式之间的运动学、动力学和肌肉活动。然后，我们通过让受试者在非优势腿上佩戴锁定膝关节支具（设定为 0°）在 SPT 上行走来验证 SPT 对不对称步态的性能。
我们的 SPT 能够为对称和不对称步态模式提供受控行走。受试者从静止状态开始，能够通过视觉反馈在 13-21 步内控制 SPT 达到目标速度。使用锁定膝关节支具，受试者可以使用大幅的步长和步速不对称来控制跑步机。一名受试者能够执行一步走，并在支撑腿的脚跟触地时用支具停止跑步机。我们的步长运动学校正算法在测试速度下显著降低了速度估计误差，优于竞争算法。关节运动学、关节扭矩和肌肉活动在固定速度和自步行走之间通常相似。在 63 个关节运动学测试中有 5 个、63 个关节扭矩测试中有 2 个和 126 个肌肉活动测试中有 9 个存在统计学上的显著差异。这些统计学上显著的差异并非在所有速度下都存在，且通常足够小，临床意义有限。
我们提出了一种经过验证的方法，用于实现对称和不对称步态的自步式跑步机。由于我们的估计算法的准确性提高，我们的 SPT 无需包含位置反馈控制器即可实现受控行走，从而减少控制器对用户真实行走速度测量的影响。我们的方法仅依赖于步长和步时的运动学校正，这可以支持将其转移到实验室外的系统中，以在临床人群中进行对称和不对称步态的应用。
