Oliveira Anderson Souza, Gizzi Leonardo, Ketabi Shahin, Farina Dario, Kersting Uwe Gustav
Department of Mechanical and Manufacturing Engineering, Aalborg University, Aalborg, Denmark.
Institute of Neurorehabilitation Systems, Bernstein Focus Neurotechnology Göttingen, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen, Georg-August University, Göttingen, Germany.
PLoS One. 2016 Apr 11;11(4):e0153307. doi: 10.1371/journal.pone.0153307. eCollection 2016.
Motorized treadmills have been widely used in locomotion studies, although a debate remains concerning the extrapolation of results obtained from treadmill experiments to overground locomotion. Slight differences between treadmill (TRD) and overground running (OVG) kinematics and muscle activity have previously been reported. However, little is known about differences in the modular control of muscle activation in these two conditions. Therefore, we aimed at investigating differences between motor modules extracted from TRD and OVG by factorization of multi-muscle electromyographic (EMG) signals. Twelve healthy men ran on a treadmill and overground at their preferred speed while we recorded tibial acceleration and surface EMG from 11 ipsilateral lower limb muscles. We extracted motor modules representing relative weightings of synergistic muscle activations by non-negative matrix factorization from 20 consecutive gait cycles. Four motor modules were sufficient to accurately reconstruct the EMG signals in both TRD and OVG (average reconstruction quality = 92±3%). Furthermore, a good reconstruction quality (80±7%) was obtained also when muscle weightings of one condition (either OVG or TRD) were used to reconstruct the EMG data from the other condition. The peak amplitudes of activation signals showed a similar timing (pattern) across conditions. The magnitude of peak activation for the module related to initial contact was significantly greater for OVG, whereas peak activation for modules related to leg swing and preparation to landing were greater for TRD. We conclude that TRD and OVG share similar muscle weightings throughout motion. In addition, modular control for TRD and OVG is achieved with minimal temporal adjustments, which were dependent on the phase of the running cycle.
电动跑步机已广泛应用于运动研究中，尽管对于将跑步机实验所得结果外推至地面运动仍存在争议。先前已有报道称跑步机（TRD）跑步和地面跑步（OVG）的运动学及肌肉活动存在细微差异。然而，对于这两种情况下肌肉激活的模块化控制差异却知之甚少。因此，我们旨在通过对多块肌肉肌电图（EMG）信号进行分解，研究从TRD和OVG中提取的运动模块之间的差异。12名健康男性以其偏好的速度在跑步机上和地面上跑步，同时我们记录了11块同侧下肢肌肉的胫骨加速度和表面肌电图。我们通过非负矩阵分解从连续20个步态周期中提取了代表协同肌肉激活相对权重的运动模块。四个运动模块足以准确重建TRD和OVG中的肌电图信号（平均重建质量 = 92±3%）。此外，当用一种情况（OVG或TRD）的肌肉权重来重建另一种情况的肌电图数据时，也获得了良好的重建质量（80±7%）。激活信号的峰值幅度在不同情况下显示出相似的时间（模式）。与初始接触相关模块的峰值激活幅度在OVG中显著更大，而与腿部摆动和准备着地相关模块的峰值激活在TRD中更大。我们得出结论，TRD和OVG在整个运动过程中共享相似的肌肉权重。此外，TRD和OVG的模块化控制通过最小的时间调整来实现，这些调整取决于跑步周期的阶段。
