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The Need for Data-driven Bike Fitting: Data Study of Subjective Expert Fitting

机译:需要数据驱动的自行车配件:主观专家配件的数据研究

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摘要

The number of cyclists is growing rapidly, for commuting but also as a sport. With this growth, there has been an increasing interest in cycling position. Trainers, athletes and bike vendors acknowledged this and started to perform bike fits. As these experts have different backgrounds and varying levels of expertise, it was hypothesised that this could have an influence on the outcome in terms of the advised position. In this research three cyclists were bike fitted by nine different bike fitting studios. It was hypothesised that, as different bike fitters use varying techniques and have different experience levels, the cyclist would be advised a different optimal position by these different bike fitters. The preconceived hypothesis was confirmed as the range of advised positions in both saddle height and setback was up to 3 cm. Data-driven bike fitting can help bring down these considerable differences amongst fitters and will be discussed in the last chapter.
机译:骑自行车者的数量正在迅速增长,即通勤,但也是一项运动。凭借这种增长,对骑自行车位置的兴趣越来越令人兴趣。培训师,运动员和自行车供应商承认这一点并开始执行自行车。由于这些专家有不同的背景和不同程度的专业知识,因此假设这可能会对所建议的职位方面的结果产生影响。在这项研究中,三名骑自行车的人被九个不同的自行车配件工作室骑自行车。正如不同的自行车配件使用不同的技术并且具有不同的体验水平,那样,骑自行车者将被这些不同的自行车架件建议不同的最佳位置。先入为主假设被证实为鞍座高度和挫折中的建议位置的范围高达3厘米。数据驱动的自行车拟合可以帮助降低折叠的这些相当大的差异,并将在最后一章中讨论。

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