Department of Sport Science, University of Innsbruck, Fürstenweg 185, A-6020 Innsbruck, Austria; Department of Physical Therapy, School of Allied Health Sciences, University of Phayao, 19 Moo 2 Maeka, Muang, Phayao 56000, Thailand; Unit of Excellence in Well-Being and Health Innovation, School of Allied Health Sciences, University of Phayao, 19 Moo2 Maeka, Muang, Phayao 56000, Thailand.
Department of Sport Science, University of Innsbruck, Fürstenweg 185, A-6020 Innsbruck, Austria.
Hum Mov Sci. 2021 Jun;77:102792. doi: 10.1016/j.humov.2021.102792. Epub 2021 Apr 13.
One approach to investigating sensorimotor control is to assess the accelerations that produce changes in the kinematic state of the system. When assessing complex whole-body movements, structuring the multi-segmental accelerations is important. A useful structuring can be achieved through a principal component analysis (PCA) performed on segment positions followed by double-differentiation to obtain "principal accelerations" (PAs). In past research PAs have proven sensitive to altered motor control strategies, however, the interrelationship between PAs and muscle activation (surface electromyography, sEMG) have never been determined. The purpose of the current study was therefore to assess the relationship between PAs and sEMG signals recorded from muscles controlling the ankle joint during one-leg standing trials. It was hypothesized that medium correlation should be observed when accounting for neurophysiologic latencies (electro-mechanical delay). Unipedal balancing on a level-rigid ground was performed by 25 volunteers. sEMG activities were recorded from the tibialis anterior, peroneus longus, gastrocnemius medialis, and soleus muscles of the stance leg. The first eight PA-time series were determined from kinematic marker data. Then, a cross-correlation analysis was performed between sEMG and PA time series. We found that peak correlation coefficients for many participants aligned at time delays between 0.116 and 0.362 s and were typically in the range small to medium (|r| = 0.1 to 0.6). Thus, the current study confirmed a direct association between many principal accelerations PA(t) and muscle activation signals recorded from four muscles crossing the ankle joint complex. The combined analysis of PA and sEMG signals allowed exploring the neuromuscular function of each muscle in different postural movement components.
一种研究感觉运动控制的方法是评估产生系统运动状态变化的加速度。在评估复杂的全身运动时,对多节段加速度进行结构分析很重要。通过对节段位置进行主成分分析(PCA),然后进行双重微分,可以获得“主加速度”(PA),从而实现有用的结构分析。在过去的研究中,PA 已被证明对改变运动控制策略敏感,但是,PA 与肌肉激活(表面肌电图,sEMG)之间的相互关系从未确定过。因此,本研究的目的是评估在单腿站立试验中记录的控制踝关节的肌肉的 PA 和 sEMG 信号之间的关系。假设在考虑神经生理潜伏期(机电延迟)时,应该观察到中等相关性。25 名志愿者在水平刚性地面上进行单足平衡。从支撑腿的胫骨前肌、腓骨长肌、比目鱼肌和腓肠肌记录 sEMG 活动。从运动学标记数据中确定前 8 个 PA 时间序列。然后,对 sEMG 和 PA 时间序列进行了互相关分析。我们发现,许多参与者的峰值相关系数在 0.116 到 0.362 秒之间对齐,并且通常在小到中等范围(|r|=0.1 到 0.6)内。因此,本研究证实了许多主加速度 PA(t)与记录自穿过踝关节复合体的四个肌肉的肌肉激活信号之间存在直接关联。PA 和 sEMG 信号的联合分析可以探索每个肌肉在不同姿势运动成分中的神经肌肉功能。