Nonlinear Measures for Biomechanical Assessment of Movement Health and Postural Complexity

Abstract

The focus of this dissertation is on using nonlinear dynamics to analyze traditional biomechanical movements. The benefit of this approach is that nonlinear dynamics may be used in the future to help athletes avoid injury and rehabilitate more effectively than they could with current protocols. The local dynamic stability (LDS) is a robust nonlinear metric which has been used previously to understand a mechanical system’s ability to adapt to small perturbations. Although the LDS has a history of use in mechanical systems, recent biomechanical studies have suggested that the LDS can also be used effectively to assess human movement patterns. Due to the relatively recent emergence of the LDS in the field of biomechanics, this dissertation aims to broaden the limited scope of understanding by analyzing younger athletes with different movement patterns to build the foundation for future nonlinear dynamics studies in biomechanics. The studies comprised in this dissertation involve two basic experimental approaches: 1) motion capture to gather kinematic profiles of the lower extremity, 2) verbal semantic fluency tests to place greater cognitive load on participants. The first of the three studies in this dissertation gathers data from elite level collegiate women’s athletes during a maximum vertical hopping task and makes group comparison between participants with previous ACL injury and participants without previous ACL injury. This study showed that lower extremity LDS can be used to effectively categorize individuals based on prior injury status in a post-hoc screening, and that lower extremity LDS can be measured in non-gait movements. Additionally, this study did not find evidence that there was a relationship between lower extremity LDS variables and variables measured at MKF during a jump. These findings suggest that LDS measures unique movement information which could allow for more accurate injury screenings, and that lower extremity LDS should be further analyzed in future studies. The second study used semantic fluency to investigate the impact of cognitive load on motor control. This study found that lower extremity LDS decreases by a larger magnitude during a dual-task as the speed of the dual-task increases, and that subjects compensate during gait by both increasing and decreasing LDS in different degrees of freedom of the lower extremity. This study did not find evidence of limb dominance affecting the change in LDS during a dual-task while walking or jogging. These findings reveal where healthy adults compensate for simple movement patterns while multitasking. It has been demonstrated that different tasks evoke different, movement-specific compensations and that the difficulty of these tasks can impact the degree of compensation required by the user to complete both a movement and cognitive task. Finally, the third study measured the relationship between lower extremity motor control (as quantified using LDS) and balance control (as quantified using multiscale entropy (MSE)). Multilevel modeling was used to find a relationship between MSE during a single legged balance and lower extremity LDS during various movement tasks. This study showed that postural complexity does not appear to be directly related to lower extremity neuromuscular control. Additionally, there were significant interaction effects in lower extremity LDS variables, which suggests that lower extremity LDS is prone to significant changes depending on movement task, lower extremity joint, and movement plane. Finally, the normality of LDS residuals was improved by the design variables included in this study, although future studies could aim to further improve normality by the inclusion of other explanatory variables such as limb dominance, gender, or injury history.