Laboratory of Biomedical Engineering - Biolab3, Department of Engineering, University Roma TRE Volterra, Rome, Italy.
Front Physiol. 2013 May 21;4:116. doi: 10.3389/fphys.2013.00116. eCollection 2013.
Finding an optimum for the cycling performance is not a trivial matter, since the literature shows the presence of many controversial aspects. In order to quantify different levels of performance, several indexes have been defined and used in many studies, reflecting variations in physiological and biomechanical factors. In particular, indexes such as Gross Efficiency (GE), Net Efficiency (NE) and Delta Efficiency (DE) have been referred to changes in metabolic efficiency (EffMet), while the Indexes of Effectiveness (IE), defined over the complete crank revolution or over part of it, have been referred to variations in mechanical effectiveness (EffMech). All these indicators quantify the variations of different factors [i.e., muscle fibers type distribution, pedaling cadence, setup of the bicycle frame, muscular fatigue (MFat), environmental variables, ergogenic aids, psychological traits (PsychTr)], which, moreover, show high mutual correlation. In the attempt of assessing cycling performance, most studies in the literature keep all these factors separated. This may bring to misleading results, leaving unanswered the question of how to improve cycling performance. This work provides an overview on the studies involving indexes and factors usually related to performance monitoring and assessment in cycling. In particular, in order to clarify all those aspects, the mutual interactions among these factors are highlighted, in view of a global performance assessment. Moreover, a proposal is presented advocating for a model-based approach that considers all factors mentioned in the survey, including the mutual interaction effects, for the definition of an objective function E representing the overall effectiveness of a training program in terms of both EffMet and EffMech.
寻找最佳的循环性能并非易事,因为文献表明存在许多有争议的方面。为了量化不同水平的性能,已经定义了几个指标,并在许多研究中使用,反映了生理和生物力学因素的变化。特别是,像总效率(GE)、净效率(NE)和效率差(DE)这样的指标被用来反映代谢效率(EffMet)的变化,而在整个曲柄旋转或其部分上定义的有效性指数(IE)则被用来反映机械效率(EffMech)的变化。所有这些指标都量化了不同因素的变化[即肌肉纤维类型分布、踏频、自行车车架设置、肌肉疲劳(MFat)、环境变量、运动补剂、心理特征(PsychTr)],而且这些因素之间存在高度的相互关联。在评估自行车性能的尝试中,文献中的大多数研究都将所有这些因素分开考虑。这可能会导致误导性的结果,使如何提高自行车性能的问题得不到解答。本工作综述了涉及到与自行车性能监测和评估相关的指标和因素的研究。特别是,为了澄清所有这些方面,突出了这些因素之间的相互作用,以便对整体性能进行评估。此外,还提出了一个建议,主张采用基于模型的方法,考虑调查中提到的所有因素,包括相互作用效应,为定义一个客观函数 E 提供依据,该函数 E 代表训练计划在 EffMet 和 EffMech 方面的整体有效性。