Department of Information Technology and Biorobotics, Institute of Mathematics and Informatics, Faculty of Sciences, University of Pecs, Pecs, Hungary.
Neurorehabilitation and Motor Control Research Group, Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary.
J Neurophysiol. 2021 Apr 1;125(4):1367-1381. doi: 10.1152/jn.00415.2020. Epub 2021 Feb 3.
Arm cycling is a bimanual motor task used in medical rehabilitation and in sports training. Understanding how muscle coordination changes across different biomechanical constraints in arm cycling is a step toward improved rehabilitation approaches. This exploratory study aims to get new insights on motor control during arm cycling. To achieve our main goal, we used the muscle synergies analysis to test three hypotheses: ) body position with respect to gravity (sitting and supine) has an effect on muscle synergies; ) the movement size (crank length) has an effect on the synergistic behavior; ) the bimanual cranking mode (asynchronous and synchronous) requires different synergistic control. Thirteen able-bodied volunteers performed arm cranking on a custom-made device with unconnected cranks, which allowed testing three different conditions: body position (sitting vs. supine), crank length (10 cm vs. 15 cm), and cranking mode (synchronous vs. asynchronous). For each of the eight possible combinations, subjects cycled for 30 s while electromyography of eight muscles (four from each arm) were recorded: biceps brachii, triceps brachii, anterior deltoid, and posterior deltoid. Muscle synergies in this eight-dimensional muscle space were extracted by nonnegative matrix factorization. Four synergies accounted for over 90% of muscle activation variances in all conditions. Results showed that synergies were affected by body position and cranking mode but practically unaffected by movement size. These results suggest that the central nervous system may employ different motor control strategies in response to external constraints such as cranking mode and body position during arm cycling. Recent studies analyzed muscle synergies in lower limb cycling. Here, we examine upper limb cycling and specifically the effect of body position with respect to gravity, movement size, and cranking mode on muscle coordination during arm cranking tasks. We show that altered body position and cranking mode affects modular organization of muscle activities. To our knowledge, this is the first study assessing motor control through muscle synergies framework during upper limb cycling with different constraints.
手臂划动是一种用于医学康复和运动训练的双手运动任务。了解手臂划动在不同生物力学约束下肌肉协调的变化，是实现改进康复方法的一步。这项探索性研究旨在深入了解手臂划动时的运动控制。为了实现我们的主要目标，我们使用肌肉协同分析来检验三个假设：1. 相对于重力的身体姿势（坐姿和仰卧位）对肌肉协同有影响；2. 运动幅度（曲柄长度）对协同行为有影响；3. 双手划动模式（异步和同步）需要不同的协同控制。13 名健康志愿者在一个定制的设备上进行手臂划动，该设备的曲柄是相互独立的，可以测试三种不同的条件：身体姿势（坐姿与仰卧位）、曲柄长度（10 厘米与 15 厘米）和划动模式（异步与同步）。对于 8 种可能的组合中的每一种，被试者以 30 秒的速度划动，同时记录 8 块肌肉（每只手臂 4 块）的肌电图：肱二头肌、肱三头肌、三角肌前束和三角肌后束。在这个 8 维肌肉空间中，通过非负矩阵分解提取肌肉协同。在所有条件下，前四个协同解释了超过 90%的肌肉激活方差。结果表明，协同作用受到身体姿势和划动模式的影响，但实际上不受运动幅度的影响。这些结果表明，中枢神经系统可能会根据外部约束（如划动模式和手臂相对于重力的位置），采用不同的运动控制策略来应对手臂划动。最近的研究分析了下肢划动中的肌肉协同。在这里，我们检查上肢划动，特别是手臂划动时，相对于重力的身体姿势、运动幅度和划动模式对肌肉协调的影响。我们表明，改变身体姿势和划动模式会影响肌肉活动的模块化组织。据我们所知，这是第一项使用不同约束条件评估上肢划动时通过肌肉协同框架进行的运动控制的研究。
