Empirical quantification and computational modeling of spine stability and neuromuscular function during dynamic movements.

动态运动过程中脊柱稳定性和神经肌肉功能的经验量化和计算建模。

• 批准号: RGPIN-2014-05560
• 负责人: Graham, Ryan
• 金额: $ 2.11万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=652298
• 关键词: Empirical; quantification; computational; modeling; spine

The global objective of my research program is to utilize novel techniques to better understand which factors contribute mechanistically to spine injury and impairment. The goal of this grant cycle is to focus specifically on stability, since stability is a fundamental concept that can be used to characterize and evaluate the functioning of a system. **A key feature to stability and appropriate neuromuscular function is the ability to effectively respond to internal and external mechanical perturbations, in order to restore an equilibrium posture or movement trajectory during motion. Spine stability is the result of a complex interaction between the osteoligamentous spine, the trunk musculature, and the neural control system; with impairment to any one subsystem, small perturbations can result in the unsuccessful transmission of compressive and shear forces and tissue strain and/or injury. However, despite the knowledge that spine stability is important, its quantification is difficult using presently available imaging, manual testing, and biomechanical modeling techniques. Moreover, to date no empirical method allows measuring stability in static and all the more in dynamic conditions.**One promising method assessing spine stability and neuromuscular function during dynamic movements is to calculate local dynamic spine stability from trunk motion data using a nonlinear dynamical systems approach. During repetitive trunk movements it is reasonable to assume that each movement cycle would be similar to every other cycle and the target kinematic trajectory or attractor. Naturally-occurring variance observed in empirical data is thus attributable to mechanical disturbances or control errors that are attenuated in time by the musculoskeletal and nervous systems. Thus, it is logical to calculate stability from the time-dependent growth or attenuation of kinematic variability in state space using the maximum Lyapunov exponent. The proposed research program will build on my previous work and has two overarching objectives: 1) to continue to improve the ability to empirically quantify and model spine stability and neuromuscular function in humans, and 2) to apply these techniques to a variety of movement scenarios to better understand how instability and impaired functioning may act as a biological or biomechanical mechanism of tissue failure and injury. **As part of objective 1, we will carry out a series of modeling-based studies that are aimed at: i) further elucidating the relationship between local dynamic spine stability and other stability measures, ii) understanding the relationship between local spine stability and global trunk stability, and iii) beginning the process of modeling the entire Lyapunov spectrum from empirical data. With the knowledge gained, objective 2 will involve applying these advanced stability assessment techniques to various movement tasks to gain a greater understanding of how mechanical loading and tissue altering properties affect (in) stability and neuromuscular function, and vice versa. Lastly, we will assess the relationship between stability and other measures of neuromuscular function (e.g. coordination), in order to fully understand its contributions to healthy movement.**As a whole, this combination of novel basic science and computational modeling has the potential to greatly benefit the Canadian natural sciences and engineering fields, as the empirical quantification of spine stability and neuromuscular function during dynamic movement will now be possible; providing us a better biological and mechanical understanding of how many anatomical, physiological, and biomechanical factors contribute mechanistically to tissue strain and/or injury during a variety of movement tasks and conditions.

我的研究计划的全球目标是利用新颖的技术来更好地了解哪些因素对脊柱损伤和损害的机械造成了贡献。这个赠款周期的目的是专门关注稳定性，因为稳定性是一个基本概念，可用于表征和评估系统的功能。 **稳定性和适当的神经肌肉功能的关键特征是能够有效响应内部和外部机械扰动，以便在运动过程中恢复平衡姿势或运动轨迹。脊柱稳定性是骨脊柱，躯干肌肉和神经控制系统之间复杂相互作用的结果。由于对任何一个子系统的损害，小扰动可能导致压缩力和剪切力以及组织应变和/或损伤的传播不成功。然而，尽管知道脊柱稳定性很重要，但使用目前可用的成像，手动测试和生物力学建模技术很难进行定量。此外，迄今为止，没有经验方法允许在动态条件下测量静态的稳定性。在重复的中继运动中，可以合理地假设每个运动周期都将与其他每个周期和目标运动轨迹或吸引子相似。因此，在经验数据中观察到的自然存在差异归因于机械扰动或控制误差，这些障碍会被肌肉骨骼和神经系统及时减弱。因此，使用最大lyapunov指数来计算状态空间中运动学变异性的稳定性是合乎逻辑的。拟议的研究计划将基于我以前的工作，并具有两个总体目标：1）继续提高人类实证量化和建模脊柱稳定性和神经肌肉功能的能力，以及2）将这些技术应用于各种运动方案，以更好地理解不稳定和受损的功能可能是一种生物机械或生物机械的机构机构和生物机械的机构。 **作为目标1的一部分，我们将进行一系列基于建模的研究，其目的是：i）进一步阐明局部动态脊柱稳定性与其他稳定性测量方法之间的关系，ii）ii）理解局部脊柱稳定性与全球躯干稳定性以及III之间的关系，以及III），开始对整个Lyapunov Spectrum from Empirical数据进行建模的过程。随着知识的获得，目标2将涉及将这些高级稳定评估技术应用于各种运动任务，以便对机械负载和组织改变性质如何影响（IN）稳定性和神经肌肉功能有更深入的了解，反之亦然。最后，我们将评估稳定性与神经肌肉功能的其他度量（例如协调）之间的关系，以充分了解其对健康运动的贡献。为我们提供更好的生物学和机械理解，了解在各种运动任务和条件下，有多少解剖，生理和生物力学因素会导致组织应变和/或损伤。