Happee Riender, de Vlugt Erwin, van Vliet Bart
Department of Biomechanical Engineering, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands,
Exp Brain Res. 2015 Jan;233(1):39-52. doi: 10.1007/s00221-014-4083-x. Epub 2014 Sep 17.
Ample evidence exists regarding the nonlinearity of the neuromuscular system but linear models are widely applied to capture postural dynamics. This study quantifies the nonlinearity of human arm postural dynamics applying 2D continuous force perturbations (0.2-40 Hz) inducing three levels of hand displacement (5, 15, 45 mm RMS) followed by force-pulse perturbations inducing large hand displacements (up to 250 mm) in a position task (PT) and a relax task (RT) recording activity of eight shoulder and elbow muscles. The continuous perturbation data were used to analyze the 2D endpoint dynamics in the frequency domain and to identify reflexive and intrinsic parameters of a linear neuromuscular shoulder-elbow model. Subsequently, it was assessed to what extent the large displacements in response to force pulses could be predicted from the 'small amplitude' linear neuromuscular model. Continuous and pulse perturbation responses with varying amplitudes disclosed highly nonlinear effects. In PT, a larger continuous perturbation induced stiffening with a factor of 1.5 attributed to task adaptation evidenced by increased co-contraction and reflexive activity. This task adaptation was even more profound in the pulse responses where reflexes and displacements were strongly affected by the presence and amplitude of preceding continuous perturbations. In RT, a larger continuous perturbation resulted in yielding with a factor of 3.8 attributed to nonlinear mechanical properties as no significant reflexive activity was found. Pulse perturbations always resulted in yielding where a model fitted to the preceding 5-mm continuous perturbations predicted only 37% of the recorded peak displacements in RT and 79% in PT. This demonstrates that linear neuromuscular models, identified using continuous perturbations with small amplitudes, strongly underestimate displacements in pulse-shaped (e.g., impact) loading conditions. The data will be used to validate neuromuscular models including nonlinear muscular (e.g., Hill and Huxley) and reflexive components.
关于神经肌肉系统的非线性存在大量证据,但线性模型仍被广泛应用于捕捉姿势动力学。本研究通过施加二维连续力扰动(0.2 - 40 Hz)来量化人体手臂姿势动力学的非线性,该扰动会引起三种手部位移水平(均方根值为5、15、45 mm),随后施加力脉冲扰动以引起大手部位移(最大达250 mm),在一个位置任务(PT)和一个放松任务(RT)中记录八块肩部和肘部肌肉的活动。连续扰动数据用于在频域分析二维端点动力学,并识别线性神经肌肉肩 - 肘模型的反射和固有参数。随后,评估了从“小幅度”线性神经肌肉模型预测力脉冲引起的大位移的程度。不同幅度的连续和脉冲扰动响应揭示出高度非线性效应。在PT中,更大的连续扰动会导致刚度增加1.5倍,这归因于任务适应性,表现为协同收缩和反射活动增加。这种任务适应性在脉冲响应中更为显著,其中反射和位移受到先前连续扰动的存在和幅度的强烈影响。在RT中,更大的连续扰动会导致屈服,屈服系数为3.8,这归因于非线性力学特性,因为未发现明显的反射活动。脉冲扰动总是导致屈服,其中一个拟合先前5 mm连续扰动的模型仅预测了RT中记录的峰值位移的37%和PT中的79%。这表明,使用小幅度连续扰动识别的线性神经肌肉模型在脉冲状(例如冲击)加载条件下会严重低估位移。这些数据将用于验证包括非线性肌肉(例如希尔和赫胥黎)和反射成分的神经肌肉模型。