基于负荷逐渐增大的蹬车效率指标,建立了评价蹬车技术的新指标。

Acta of bioengineering and biomechanics Pub Date : 2025-03-18 Print Date: 2024-12-01 DOI:10.37190/abb-02546-2024-02
Tomoki Kitawaki, Masahiro Fukuda
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引用次数: 0

摘要

目的:测量自行车踩踏板时的踏板力矢量最近变得容易了,人们利用机械效率(有效驱动力与总踏板力的比值)进行了研究;然而,没有考虑这些力量之间的关系。本研究旨在表明,在逐渐增加的载荷条件下,这些力之间的关系可以线性回归,并提出坡度参数可以作为评价踩踏技能的新指标。方法:28名参与者进行每分钟增加负荷的实验,直到施加最大负荷。利用安装在两曲柄上的传感器,将踏板力矢量分为切向分量和径向分量,确定每分钟的总踏板力和有效驱动力。计算了最大载荷力和效率指标。结果:试验结果表明,总踏板数与有效驱动力之间存在较强的线性关系(决定系数为0.982,95% CI为0.909 ~ 0.996)。该回归的坡度参数与最大负荷力和最大负荷时的效率指数分别呈显著相关(-0.560和-0.674)。这些相关性突出了斜坡参数捕捉踏板特性的潜力。结论:由总蹬力与有效驱动力线性回归得到的坡度参数反映了个体蹬力特征。该参数作为评估蹬车运动的一个有前途的新指标脱颖而出,为参与者特定的蹬车行为提供了见解。因此,这一新的指标可以用于评估和分析踏板技能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New index for evaluating pedaling techniques using the pedaling efficiency index with gradually increasing load.

Purpose: Measuring the pedal force vector during bicycle pedaling has recently become easy, and research have been conducted using mechanical efficiency (the ratio of an effective driving force to total pedaling force); however, the relationships between these forces were not considered. This study aimed to show that the relationship between these forces can be linearly regressed under gradually increasing load conditions and propose that the slope parameter can serve as a new index for evaluating pedaling skills. Methods: Twenty-eight participants performed the experiment in which the load was increased every minute until the maximum load was exerted. Using sensors installed on both bicycle cranks, the pedaling force vector was divided into tangential and radial components to determine the total pedaling and effective driving forces per minute. The maximum load force and efficiency index were calculated. Results: Our results showed a strong linear relationship (coefficient of determination: 0.982, 95% CI 0.909-0.996) between the total pedaling and effective driving force. The slope parameters from this regression exhibited significant correlations (-0.560 and -0.674) with the maximum load force and efficiency index during maximum exertion, respectively. These correlations highlight the slope parameter potential for capturing pedaling characteristics. Conclusions: The slope parameter derived from the linear regression between the total pedaling force and effective driving force reflects individual pedaling characteristics. This parameter stands out as a promising new index for evaluating pedaling motion, offering insights into participant-specific pedaling behaviors. Consequently, this novel index could be instrumental in assessing and analyzing pedaling skills.

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