Granata Kevin P, England Scott A
Musculoskeletal Biomechanics Laboratories, Department of Engineering Science & Mechanics, School of Biomedical Engineering & Science, Virginia Polytechnic Institute & State University, Blacksburg, VA 24061, USA.
Spine (Phila Pa 1976). 2006 May 1;31(10):E271-6. doi: 10.1097/01.brs.0000216445.28943.d1.
Nonlinear systems analyses of trunk kinematics were performed to estimate control of dynamic stability during repetitive flexion and extension movements.
Determine whether movement pace and movement direction of dynamic trunk flexion and extension influence control of local dynamic stability.
Spinal stability has been previously characterized in static, but not in dynamic movements. Biomechanical models make inferences about static spinal stability, but existing analyses provide limited insight into stability of dynamic movement. Stability during dynamic movements can be estimated from Lyapunov analyses of empirical data.
There were 20 healthy subjects who performed repetitive trunk flexion and extension movements at 20 and 40 cycles per minute. Maximum Lyapunov exponents describing the expansion of the kinematic state-space were calculated from the measured trunk kinematics to estimate stability of the dynamic system.
The complexity of torso movement dynamics required at least 5 embedded dimensions, which suggests that stability components of lumbar lordosis may be empirically measurable in addition to global stability of trunk dynamics. Repeated trajectories from fast paced movements diverged more quickly than slower movement, indicating that local dynamic stability is limited in fast movements. Movements in the midsagittal plane showed higher multidimensional kinematic divergence than asymmetric movements.
Nonlinear dynamic systems analyses were successfully applied to empirically measured data, which were used to characterize the neuromuscular control of stability during repetitive dynamic trunk movements. Movement pace and movement direction influenced the control of spinal stability. These stability assessment techniques are recommended for improved workplace design and the clinical assessment of spinal stability in patients with low back pain.
对躯干运动学进行非线性系统分析，以评估重复屈伸运动过程中动态稳定性的控制情况。
确定动态躯干屈伸的运动速度和运动方向是否会影响局部动态稳定性的控制。
脊柱稳定性此前已在静态状态下进行了特征描述，但尚未涉及动态运动。生物力学模型对静态脊柱稳定性进行了推断，但现有分析对动态运动稳定性的洞察有限。动态运动期间的稳定性可通过对经验数据的李雅普诺夫分析来估计。
20名健康受试者以每分钟20次和40次的频率进行重复的躯干屈伸运动。根据测量得到的躯干运动学数据计算描述运动状态空间扩展的最大李雅普诺夫指数，以评估动态系统的稳定性。
躯干运动动力学的复杂性至少需要5个嵌入维度，这表明除了躯干动力学的整体稳定性外，腰椎前凸的稳定性成分可能可以通过经验测量得到。快节奏运动的重复轨迹比慢节奏运动发散得更快，这表明快速运动中局部动态稳定性受到限制。矢状面内的运动比不对称运动表现出更高的多维运动发散。
非线性动态系统分析成功应用于经验测量数据，这些数据用于表征重复动态躯干运动期间稳定性的神经肌肉控制。运动速度和运动方向影响脊柱稳定性的控制。建议采用这些稳定性评估技术来改进工作场所设计以及对腰痛患者脊柱稳定性进行临床评估。
