使用统计参数映射（SPM）评估不同跑鞋对跑步机跑步力学和肌肉活动的影响。
The effect of different running shoes on treadmill running mechanics and muscle activity assessed using statistical parametric mapping (SPM).
机构信息
Department of Orthopaedics and Traumatology, University Hospital Basel, Spitalstrasse 21, 4031, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Gewerbestrasse 14, 4123, Allschwil, Switzerland; Department of Clinical Research, University of Basel, Schanzenstrasse 55, 4031, Basel, Switzerland.
Department of Orthopaedics and Traumatology, University Hospital Basel, Spitalstrasse 21, 4031, Basel, Switzerland.
出版信息
Gait Posture. 2019 Mar;69:1-7. doi: 10.1016/j.gaitpost.2019.01.013. Epub 2019 Jan 10.
BACKGROUND
Differences in joint mechanics between running shoes are commonly assessed using discrete parameters, yet statistically significant differences in these parameters between shoes are often scarce with small effect sizes. Statistical parametric mapping (SPM) has been suggested as suitable method for analyzing one-dimensional data such as kinematic, kinetic or muscle intensity time series.
RESEARCH QUESTION
The purpose of this study was to determine differences in treadmill running mechanics between novel running shoes using SPM.
METHODS
Joint kinematics, muscle activity and ground reaction force were assessed in 19 rearfoot runners in their own shoes and in two test shoes during treadmill running (test shoe 1: 13 distinct rubber elements in the outer sole, springboard within EVA midsole with posterior elements shifted anteriorly by approximately 1.5 cm; test shoe 2: 17 distinct EVA elements with conventional heel geometry). Joint kinematics were measured using an inertial sensor system, and ground reaction force was measured using an instrumented treadmill.
RESULTS
SPM analysis with repeated measures ANOVA revealed significant reductions in the ankle angle and in tibialis anterior, peroneus longus, vastus medialis and lateralis muscle activity during weight acceptance and in peroneus longus muscle activity during early and late swing and in semitendinosus muscle activity during late swing for the test shoes. Significant differences in muscle activity were observed in the interval of the main activity of the respective muscle. SPM on individual data revealed statistically significant and relevant within-subject differences between conditions in kinematic, muscle activity and ground reaction force patterns.
SIGNIFICANCE
Inertial sensor systems and SPM may provide an efficient way of detecting changes in joint mechanics between running shoes within runners. Detecting within-subject differences in running mechanics between conditions not only requires statistical criteria but also criteria on the relevance of the magnitude of differences.
背景
跑鞋之间的关节力学差异通常使用离散参数进行评估，但这些参数之间的统计学显著差异通常很少，且效应量较小。统计参数映射（SPM）已被提议作为分析运动学、动力学或肌肉强度时间序列等一维数据的合适方法。
研究问题
本研究的目的是使用 SPM 确定新型跑鞋在跑步机跑步时的跑步力学差异。
方法
19 名后足跑步者在自己的鞋子和两种测试鞋子（测试鞋 1：外底有 13 个不同的橡胶元件，EVA 中底内有跳板，后部元件向前移动约 1.5 厘米；测试鞋 2：17 个具有传统后跟几何形状的 EVA 元件）中进行跑步机跑步时，评估关节运动学、肌肉活动和地面反作用力。关节运动学使用惯性传感器系统进行测量，地面反作用力使用仪器化跑步机进行测量。
结果
使用重复测量方差分析的 SPM 分析显示，在测试鞋中，踝关节角度以及胫骨前肌、腓骨长肌、股四头肌内侧和外侧肌在负重期的肌肉活动以及腓骨长肌在早期和晚期摆动期以及半腱肌在晚期摆动期的肌肉活动显著降低。在各自肌肉的主要活动期间观察到肌肉活动的显著差异。对个体数据的 SPM 显示，在运动学、肌肉活动和地面反作用力模式方面，条件之间存在统计学上显著且与个体相关的差异。
意义
惯性传感器系统和 SPM 可能为检测跑步者之间跑鞋关节力学的变化提供一种有效的方法。在不同条件下检测跑步力学的个体差异不仅需要统计学标准，还需要差异幅度的相关性标准。
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