Ottawa Hospital Research Institute, Ottawa, Canada.
University of Ottawa, Department of Human Kinetics, University of Ottawa, Ottawa, Canada.
PLoS One. 2018 Sep 17;13(9):e0203934. doi: 10.1371/journal.pone.0203934. eCollection 2018.
Lower extremity powered exoskeletons (LEPE) are an emerging technology that assists people with lower-limb paralysis. LEPE for people with complete spinal cord injury walk at very slow speeds, below 0.5m/s. For the able-bodied population, very slow walking uses different neuromuscular, locomotor, postural, and dynamic balance control. Speed dependent kinetic and kinematic regression equations in the literature could be used for very slow walking LEPE trajectory scaling; however, kinematic and kinetic information at walking speeds below 0.5 m/s is lacking. Scaling LEPE trajectories using current reference equations may be inaccurate because these equations were produced from faster than real-world LEPE walking speeds. An improved understanding of how able-bodied people biomechanically adapt to very slow walking will provide LEPE developers with more accurate models to predict and scale LEPE gait trajectories. Full body motion capture data were collected from 30 healthy adults while walking on an instrumented self-paced treadmill, within a CAREN-Extended virtual reality environment. Kinematic and kinetic data were collected for 0.2 m/s-0.8 m/s, and self-selected walking speed. Thirty-three common sagittal kinematic and kinetic gait parameters were identified from motion capture data and inverse dynamics. Gait parameter relationships to walking speed, cadence, and stride length were determined with linear and quadratic (second and third order) regression. For parameters with a non-linear relationship with speed, cadence, or stride-length, linear regressions were used to determine if a consistent inflection occurred for faster and slower walking speeds. Group mean equations were applied to each participant's data to determine the best performing equations for calculating important peak sagittal kinematic and kinetic gait parameters. Quadratic models based on walking speed had the strongest correlations with sagittal kinematic and kinetic gait parameters, with kinetic parameters having the better results. The lack of a consistent inflection point indicated that the kinematic and kinetic gait strategies did not change at very slow gait speeds. This research showed stronger associations with speed and gait parameters then previous studies, and provided more accurate regression equations for gait parameters at very slow walking speeds that can be used for LEPE joint trajectory development.
下肢助力外骨骼（LEPE）是一种新兴技术，可帮助下肢瘫痪的人。完全性脊髓损伤患者使用 LEPE 行走的速度非常慢，低于 0.5m/s。对于健全人来说，非常慢的行走使用不同的神经肌肉、运动、姿势和动态平衡控制。文献中的速度相关动力学和运动学回归方程可用于 LEPE 轨迹缩放；然而，缺乏 0.5m/s 以下行走的运动学和动力学信息。使用当前参考方程缩放 LEPE 轨迹可能不准确，因为这些方程是由快于现实世界的 LEPE 行走速度产生的。更好地了解健全人如何适应非常慢的行走，将为 LEPE 开发人员提供更准确的模型，以预测和缩放 LEPE 步态轨迹。从 30 名健康成年人在 CAREN-Extended 虚拟现实环境中使用仪器化自步跑步机行走时收集了全身运动捕捉数据。在 0.2m/s-0.8m/s 和自我选择的行走速度范围内收集了运动学和动力学数据。从运动捕捉数据和逆动力学中识别了 33 个常见矢状面运动学和动力学步态参数。使用线性和二次（二阶和三阶）回归确定步态参数与行走速度、步频和步长的关系。对于与速度、步频或步长呈非线性关系的参数，使用线性回归确定更快和更慢行走速度是否存在一致的拐点。将组平均值方程应用于每个参与者的数据，以确定计算重要矢状面运动学和动力学步态参数的最佳方程。基于行走速度的二次模型与矢状面运动学和动力学步态参数具有最强的相关性，动力学参数的结果更好。缺乏一致的拐点表明，在非常慢的步态速度下，运动学和动力学步态策略没有改变。与之前的研究相比，这项研究显示出与速度和步态参数更强的关联，并提供了更准确的非常慢行走速度下步态参数的回归方程，可用于 LEPE 关节轨迹开发。
