Rauter G, Baumgartner L, Denoth J, Riener R, Wolf P
Sensory-Motor Systems Lab, ETH Zurich, and Medical Faculty, University of Zurich, Zurich, Switzerland.
Comput Methods Biomech Biomed Engin. 2012;15(8):815-24. doi: 10.1080/10255842.2011.561794. Epub 2011 May 24.
In rowing, motor learning may be facilitated by augmented feedback that displays the ratio between actual mean boat velocity and maximal achievable mean boat velocity. To provide this ratio, the aim of this work was to develop and evaluate an algorithm calculating an individual maximal mean boat velocity. The algorithm optimised the horizontal oar movement under constraints such as the individual range of the horizontal oar displacement, individual timing of catch and release and an individual power-angle relation. Immersion and turning of the oar were simplified, and the seat movement of a professional rower was implemented. The feasibility of the algorithm, and of the associated ratio between actual boat velocity and optimised boat velocity, was confirmed by a study on four subjects: as expected, advanced rowing skills resulted in higher ratios, and the maximal mean boat velocity depended on the range of the horizontal oar displacement.
在赛艇运动中,通过显示实际平均艇速与最大可实现平均艇速之间比率的增强反馈,可能有助于运动学习。为了提供该比率,本研究的目的是开发并评估一种计算个体最大平均艇速的算法。该算法在诸如水平桨位移的个体范围、抓水和回桨的个体时机以及个体功率-角度关系等约束条件下,优化水平桨的运动。桨的入水和转动被简化,并模拟了专业赛艇运动员的座位移动。通过对四名受试者的研究,证实了该算法以及实际艇速与优化艇速之间相关比率的可行性:正如预期的那样,先进的赛艇技术导致更高的比率,并且最大平均艇速取决于水平桨位移的范围。