MacLellan Michael J
School of Kinesiology, College of Human Sciences and Education, Louisiana State University, 112 Huey P. Long Field House, Baton Rouge, LA, 70803, USA.
Exp Brain Res. 2017 Jul;235(7):2011-2026. doi: 10.1007/s00221-017-4946-z. Epub 2017 Mar 25.
Human locomotor patterns require precise adjustments to successfully navigate complex environments. Studies suggest that the central nervous system may control such adjustments through supraspinal signals modifying a basic locomotor pattern at the spinal level. To explore this proposed control mechanism in the leading and trailing limbs during obstructed walking, healthy young adults stepped over obstacles measuring 0.1 and 0.2 m in height. Unobstructed walking with no obstacle present was also performed as a baseline. Full body three-dimensional kinematic data were recorded and electromyography (EMG) was collected from 14 lower limb muscles on each side of the body. EMG data were analyzed using two techniques: by mapping the EMG data to the approximate location of the motor neuron pools on the lumbosacral enlargement of the spinal cord and by applying a nonnegative matrix factorization algorithm to unilateral and bilateral muscle activations separately. Results showed that obstacle clearance may be achieved not only with the addition of a new activation pattern in the leading limb, but with a temporal shift of a pattern present during unobstructed walking in both the leading and trailing limbs. An investigation of the inter-limb coordination of these patterns suggested a strong bilateral linkage between lower limbs. These results highlight the modular organization of muscle activation in the leading and trailing limbs, as well as provide a mechanism of control when implementing a locomotor adjustment when stepping over an obstacle.
人类的运动模式需要精确调整,以便在复杂环境中成功导航。研究表明,中枢神经系统可能通过脊髓以上的信号来控制这种调整,这些信号会修改脊髓水平的基本运动模式。为了探究在受阻行走过程中,领先和落后肢体的这种控制机制,健康的年轻成年人跨过了高度为0.1米和0.2米的障碍物。同时也进行了无障碍物的无障碍行走作为基线。记录了全身三维运动学数据,并从身体两侧的14条下肢肌肉收集了肌电图(EMG)。EMG数据使用两种技术进行分析:通过将EMG数据映射到脊髓腰骶膨大处运动神经元池的大致位置,以及分别对单侧和双侧肌肉激活应用非负矩阵分解算法。结果表明,不仅可以通过在领先肢体中添加新的激活模式来实现跨越障碍物,而且领先和落后肢体在无障碍行走时出现的模式的时间偏移也可以实现。对这些模式的肢体间协调性的研究表明下肢之间存在很强的双侧联系。这些结果突出了领先和落后肢体中肌肉激活的模块化组织,同时也为跨越障碍物时进行运动调整提供了一种控制机制。