Park Eunse, Reimann Hendrik, Schöner Gregor
Biomechanics and Movement Science, Univeristy of Delaware, Newark, DE, USA.
School of Applied Physiology, Georgia Institution of Technology, 555 14th St NW, Atlanta, GA, 30332, USA.
Exp Brain Res. 2016 Jun;234(6):1757-67. doi: 10.1007/s00221-016-4576-x. Epub 2016 Feb 15.
The control of upright stance is commonly explained on the basis of the single inverted pendulum model (ankle strategy) or the double inverted pendulum model (combination of ankle and hip strategy). Kinematic analysis using the uncontrolled manifold (UCM) approach suggests, however, that stability in upright standing results from coordinated movement of multiple joints. This is based on evidence that postural sway induces more variance in joint configurations that leave the body position in space invariant than in joint configurations that move the body in space. But does this UCM structure of kinematic variance truly reflect coordination at the level of the neural control strategy or could it result from passive biomechanical factors? To address this question, we applied the UCM approach at the level of muscle torques rather than joint angles. Participants stood on the floor or on a narrow base of support. We estimated torques at the ankle, knee, and hip joints using a model of the body dynamics. We then partitioned the joint torques into contributions from net, motion-dependent, gravitational, and generalized muscle torques. A UCM analysis of the structure of variance of the muscle torque revealed that postural sway induced substantially more variance in directions in muscle torque space that leave the Center of Mass (COM) force invariant than in directions that affect the force acting on the COM. This difference decreased when we decorrelated the muscle torque data by randomizing across time. Our findings show that the UCM structure of variance exists at the level of muscle torques and is thus not merely a by-product of biomechanical coupling. Because muscle torques reflect neural control signals more directly than joint angles do, our results suggest that the control strategy for upright stance involves the task-specific coordination of multiple degrees of freedom.
直立姿势的控制通常基于单摆倒立模型（踝关节策略）或双摆倒立模型（踝关节和髋关节策略的组合）来解释。然而，使用非受控流形（UCM）方法进行的运动学分析表明，直立站立时的稳定性源于多个关节的协调运动。这是基于这样的证据：与使身体在空间中移动的关节配置相比，姿势摇摆在使身体在空间中的位置不变的关节配置中引起的变化更大。但是，这种运动学方差的UCM结构真的反映了神经控制策略层面的协调吗？还是它可能由被动生物力学因素导致？为了解决这个问题，我们在肌肉扭矩层面而非关节角度层面应用了UCM方法。参与者站在地面或狭窄的支撑面上。我们使用身体动力学模型估计踝关节、膝关节和髋关节的扭矩。然后，我们将关节扭矩划分为净扭矩、运动相关扭矩、重力扭矩和广义肌肉扭矩的贡献。对肌肉扭矩方差结构的UCM分析表明，与影响作用于质心（COM）的力的方向相比，姿势摇摆在使质心力不变的肌肉扭矩空间方向上引起的方差要大得多。当我们通过随时间随机化来消除肌肉扭矩数据的相关性时，这种差异减小了。我们的研究结果表明，方差的UCM结构存在于肌肉扭矩层面，因此不仅仅是生物力学耦合的副产品。由于肌肉扭矩比关节角度更直接地反映神经控制信号，我们的结果表明，直立姿势的控制策略涉及多个自由度的任务特定协调。
