身体姿势控制的线性和非线性评价
Linear and Nonlinear Evaluation on Postural Control

摘要：目的：非线性分析法 (比如wavelet 分析) 已经被认为是能够更好的描述姿势摇摆下潜在的运动控制机制的方法。作者通过探讨传统线性分析和非线性（wavelet）分析法的关系，为姿势控制研究最大化解释提供参考。方法：6名大学棒球男运动员和6名无任何运动经验的男大学生，分别在睁眼和闭眼条件下，赤脚静止站立在测力台上10 s。结果：两种分析方法结果显示，视觉信息的屏蔽会引起两组人群大范围的姿势摇摆；其中wavelet分析法发现，棒球运动员较于普通人在前后方向上更多依赖脊髓反射通路、肌肉活动和小脑来调整姿势，在左右方向上更多地依赖小脑和前庭系统来维持姿势平衡; 而传统线性分析结果显示，两组人群对姿势调整的神经控制系统反应在两个方向上均未发现显著性差异。wavelet分析下的自变量能够更加全面地解释因变量。结论：运用wavelet分析法研究姿势控制，能够得到有效的生理学参数，发现更多神经肌肉控制层面的信息。
Abstract: Nonlinear analysis, such as wavelet analysis, has been considered a better description on motor control mechanism of underlying postural sway. Purpose: The purpose of this study was to examine relationship between traditional linear analysis and nonlinear analysis for providing references for optimal description of research in postural control. Methods: Six male college baseball players and six male normal college students who had no sport training experience were asked to maintain standing balance with barefoot on forceplate for 10 seconds under the conditions of eyes-open and eyes-closed. Results: Linear and nonlinear center of pressure calculations revealed that when vision was removed, both groups demonstrated larger postural sway; wavelet analysis observed that the baseball players utilized great sensory information from spinal reflective loop, muscle activity and cerebellar with respect to ordinary in the anterior-posterior direction and from cerebellar and vestibular system in the media-lateral direction. However, traditional linear analysis revealed that there was no significant relationship of neuromuscular response between two groups. Independent variables from wavelet analysis had more comprehensive explanation to dependent variables. Conclusion: Using wavelet analysis to analyze postural control can get effective physiological parameters and find more neuromuscular information