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区分健康个体在受限脊柱弯曲任务中典型和非典型运动模式。

Distinguishing between typical and atypical motion patterns amongst healthy individuals during a constrained spine flexion task.

机构信息

Department of Kinesiology & Physical Education, Wilfrid Laurier University, Waterloo, ON, Canada.

Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, ON, Canada.

出版信息

J Biomech. 2019 Mar 27;86:89-95. doi: 10.1016/j.jbiomech.2019.01.047. Epub 2019 Feb 2.

Abstract

Despite 'abnormal' motion being considered a risk factor for low back injury, the current understanding of 'normal' spine motion is limited. Identifying normal motion within an individual is complicated by the considerable variation in movement patterns amongst healthy individuals. Therefore, the purpose of this study was to characterize sources of variation in spine motion among a sample of healthy participants. The second objective of this study was to develop a multivariate model capable of predicting an expected movement pattern for an individual. The kinematic shape of the lower thoracic and lumbar spine was recorded during a constrained dynamic trunk flexion movement; as this is not a normal everyday movement task, movements are considered 'typical' and 'atypical' for this task rather than 'normal' and 'abnormal'. Variations in neutral standing posture accounted for 85% of the variation in spine motion throughout the task. Differences in total spine range of flexion and a regional re-weighting of range of motion between lower thoracic and lumbar regions explained a further 9% of the variance among individuals. The analysis also highlighted a difference in temporal sequencing of motion between lower thoracic and lumbar regions which explained 2% of the total movement variation. These identified sources of variation were used to select independent variables for a multivariate linear model capable of predicting an individuals' expected movement pattern. This was done as a proof-of-concept to demonstrate how the error between predicted and observed motion patterns could be used to differentiate between 'typical' and 'atypical' movement strategies.

摘要

尽管“异常”运动被认为是导致下背部损伤的一个风险因素,但目前对“正常”脊柱运动的理解是有限的。由于健康个体的运动模式存在很大差异,因此确定个体的正常运动是复杂的。因此,本研究的目的是描述健康参与者样本中脊柱运动的变异来源。本研究的第二个目的是开发一个能够预测个体预期运动模式的多变量模型。在受限的动态躯干屈曲运动中记录下胸段和腰段脊柱的运动学形状;由于这不是一种正常的日常运动任务,因此对于这个任务来说,运动被认为是“典型的”和“非典型的”,而不是“正常的”和“异常的”。中立站位姿势的变化解释了整个任务中脊柱运动变化的 85%。总脊柱前屈范围的差异和下胸段和腰段之间运动范围的重新加权解释了个体之间另外 9%的差异。分析还突出了下胸段和腰段之间运动时间顺序的差异,这解释了总运动变化的 2%。这些确定的变异来源被用于选择多元线性模型的自变量,该模型能够预测个体的预期运动模式。这是作为一个概念验证来演示如何使用预测和观察到的运动模式之间的误差来区分“典型”和“非典型”的运动策略。

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