Quantifying the potential benefits of advanced footwear technology (AFT) track shoes (i.e., “spikes”) in middle-distance events is challenging, because repeated maximal effort trials (as in sprinting) or aerobic running economy trials (as in long-distance running) are not feasible. We introduce a novel approach to assess the benefits of AFT spikes, consisting of a series of 200-m runs at self-perceived middle-distance race pace with 10 min recovery, and conduct 4 experiments to evaluate its validity, sensitivity, reproducibility, and utility. In Experiment 1, participants ran 1.2% slower in spikes with 200 g added mass . control spikes, which is exactly equal to the known effects of shoe mass on running performance. In Experiment 2, participants ran significantly faster in AFT prototype spikes . traditional spikes. In Experiment 3, we compared 2 other AFT prototype spikes against traditional spikes on 3 separate days. Group-level results were consistent across days, but our data indicates that at least 2 separate sessions are needed to evaluate individual responses. In Experiment 4, participants ran significantly faster in 2 AFT spike models . traditional spikes (2.1% and 1.6%). Speed was similar between a third AFT spike model and the traditional spikes. These speed results were mirrored by changes in step length as participants took significantly longer steps in the 2 faster AFT spike models (2.3% and 1.9%), while step length was similar between the other spikes. Our novel, interval-based approach is a valid and reliable method for quantifying differences between spikes at middle-distance running intensity.

中文翻译：

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自我感知的中距离比赛配速在先进的鞋鞋技术中更快


量化先进鞋类技术 (AFT) 履带鞋（即“钉鞋”）在中距离赛事中的潜在优势具有挑战性，因为重复的最大努力试验（如短跑）或有氧跑经济性试验（如长跑） ) 是不可行的。我们引入了一种新方法来评估 AFT 峰值的益处，包括以自我感知的中距离比赛配速进行一系列 200 米跑步，并进行 10 分钟恢复，并进行 4 项实验来评估其有效性、灵敏度、可重复性和公用事业。在实验 1 中，参与者在增加 200 克质量的钉鞋中跑得慢了 1.2%。控制鞋钉，这与已知的鞋质量对跑步性能的影响完全相同。在实验 2 中，参与者在 AFT 原型尖峰中跑得明显更快。传统的尖峰。在实验 3 中，我们在 3 天的时间里将其他 2 个 AFT 原型尖峰与传统尖峰进行了比较。小组层面的结果在几天内保持一致，但我们的数据表明至少需要 2 次单独的会议来评估个人反应。在实验 4 中，参与者在 2 个 AFT 尖峰模型中跑得明显更快。传统尖峰（2.1% 和 1.6%）。第三个 AFT 鞋钉模型和传统鞋钉的速度相似。这些速度结果反映在步长的变化上，因为参与者在 2 个更快的 AFT 尖峰模型中采取了明显更长的步数（2.3% 和 1.9%），而其他尖峰之间的步长相似。我们基于间歇的新颖方法是量化中距离跑步强度峰值之间差异的有效且可靠的方法。