基于骨盆和股骨形态学测量的高内收与低内收跑者分类。
Classification of Runners with High versus Low Hip Adduction Based on Measures of Pelvis and Femur Morphology.
机构信息
Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA.
出版信息
Med Sci Sports Exerc. 2022 Apr 1;54(4):590-597. doi: 10.1249/MSS.0000000000002826.
PURPOSE
To determine the most relevant pelvis and femur morphological characteristics for differentiating runners with high versus low hip adduction during running.
METHODS
Fifteen female and 14 male runners underwent instrumented kinematics analysis of overground running and computed tomography scanning of pelvis and femur. The peak hip adduction angle during the stance phase of running was identified for each participant. Using the cohort average of the peak hip adduction angle as the classifying threshold, participants were categorized into high or low hip adduction groups. To determine the most relevant morphologic features for discriminating high and low hip adduction runners, a feature selection-based support vector machine classification analysis was performed.
RESULTS
Of the 15 morphology variables examined, femoral head anteversion and femur length were shown to be the best discriminant variables for group classification. Together, these variables achieved a prediction accuracy of 0.93, sensitivity of 1.0, and specificity of 0.88.
CONCLUSIONS
Our results highlight the importance of femur morphology in contributing to increased hip adduction during running.
目的
确定最相关的骨盆和股骨形态特征，以区分跑步时髋关节内收角度较高与较低的跑者。
方法
15 名女性和 14 名男性跑步者进行了地面跑步的仪器运动学分析和骨盆及股骨的计算机断层扫描。确定了每位参与者在跑步支撑阶段髋关节内收角度的峰值。使用峰值髋关节内收角度的队列平均值作为分类阈值，将参与者分为高髋关节内收或低髋关节内收组。为了确定区分高髋关节内收和低髋关节内收跑步者的最相关形态特征，进行了基于特征选择的支持向量机分类分析。
结果
在所检查的 15 个体形变量中，股骨头前倾角和股骨长度被证明是最佳的分组分类判别变量。这两个变量结合在一起，预测准确率为 0.93，敏感度为 1.0，特异性为 0.88。
结论
我们的研究结果强调了股骨形态在跑步时增加髋关节内收中的重要性。
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