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技术依赖性与高山滑雪中局部滑雪弯曲曲率、滚转角度和径向力的关系。

Technique-Dependent Relationship between Local Ski Bending Curvature, Roll Angle and Radial Force in Alpine Skiing.

机构信息

Department of Sport and Exercise Science, University of Salzburg, Schlossallee 49, 5400 Hallein/Rif, Austria.

Joanneum Research Forschungsgesellschaft mbH-MATERIALS, Franz-Pichler-Straße 30, 8160 Weiz, Austria.

出版信息

Sensors (Basel). 2023 Apr 14;23(8):3997. doi: 10.3390/s23083997.

Abstract

Skiing technique, and performance are impacted by the interplay between ski and snow. The resulting deformation characteristics of the ski, both temporally and segmentally, are indicative of the unique multi-faceted nature of this process. Recently, a PyzoFlex ski prototype was presented for measuring the local ski curvature (w″), demonstrating high reliability and validity. The value of w″ increases as a result of enlargement of the roll angle (RA) and the radial force (RF) and consequently minimizes the radius of the turn, preventing skidding. This study aims to analyze segmental w″ differences along the ski, as well as to investigate the relationship among segmental w″, RA, and RF for both the inner and outer skis and for different skiing techniques (carving and parallel ski steering). A skier performed 24 carving and 24 parallel ski steering turns, during which a sensor insole was placed in the boot to determine RA and RF, and six PyzoFlex sensors were used to measure the w″ progression along the left ski (w1-6″). All data were time normalized over a left-right turn combination. Correlation analysis using Pearson's correlation coefficient (r) was conducted on the mean values of RA, RF, and segmental w1-6″ for different turn phases [initiation, center of mass direction change I (COM DC I), center of mass direction change II (COM DC II), completion]. The results of the study indicate that, regardless of the skiing technique, the correlation between the two rear sensors (L2 vs. L3) and the three front sensors (L4 vs. L5, L4 vs. L6, L5 vs. L6) was mostly high (r > 0.50) to very high (r > 0.70). During carving turns, the correlation between w″ of the rear (w1-3″) and that of front sensors (w4-6″) of the outer ski was low (ranging between -0.21 and 0.22) with the exception of high correlations during COM DC II (r = 0.51-0.54). In contrast, for parallel ski steering, the r between the w″ of the front and rear sensors was mostly high to very high, especially for COM DC I and II (r = 0.48-0.85). Further, a high to very high correlation (r ranging between 0.55 and 0.83) among RF, RA, and w″ of the two sensors located behind the binding (w2″,w3″) in COM DC I and II for the outer ski during carving was found. However, the values of r were low to moderate (r = 0.04-0.47) during parallel ski steering. It can be concluded that homogeneous ski deflection along the ski is an oversimplified picture, as the w″ pattern differs not only temporally but also segmentally, depending on the employed technique and turn phase. In carving, the rear segment of the outer ski is considered to have a pivotal role for creating a clean and precise turn on the edge.

摘要

滑雪技术和表现受到滑雪板和雪之间相互作用的影响。滑雪板的瞬时和分段变形特征表明了这个过程的独特多面性。最近,提出了一种 PyzoFlex 滑雪原型来测量局部滑雪曲率(w″),显示出较高的可靠性和有效性。w″值随着滚转角(RA)和径向力(RF)的增大而增大,从而最小化转弯半径,防止侧滑。本研究旨在分析滑雪板上的分段 w″差异,并研究内外滑雪板在不同滑雪技术(刻滑和平行滑雪转向)下的分段 w″、RA 和 RF 之间的关系。一名滑雪者进行了 24 次刻滑和 24 次平行滑雪转向,在此期间,在靴子中放置一个传感器鞋垫来确定 RA 和 RF,使用六个 PyzoFlex 传感器来测量左滑雪板(w1-6″)上的 w″进展。所有数据均在左右转弯组合上进行时间归一化。使用 Pearson 相关系数(r)对不同转弯阶段[启动、质心方向变化 I(COM DC I)、质心方向变化 II(COM DC II)、完成]的 RA、RF 和分段 w1-6″的平均值进行相关分析。研究结果表明,无论采用何种滑雪技术,后部两个传感器(L2 与 L3)和前部三个传感器(L4 与 L5、L4 与 L6、L5 与 L6)之间的相关性主要是高度相关(r > 0.50)到非常高相关(r > 0.70)。在刻滑转弯时,外滑雪板后部(w1-3″)的 w″与前部传感器(w4-6″)之间的相关性较低(r 在-0.21 到 0.22 之间),但在 COM DC II 期间存在高相关性(r = 0.51-0.54)。相比之下,在平行滑雪转向时,前、后传感器之间的 r 主要是高度相关到非常高相关,尤其是在 COM DC I 和 II 期间(r = 0.48-0.85)。此外,在外滑雪板的 COM DC I 和 II 期间,位于绑定后面的两个传感器(w2″、w3″)的 RF、RA 和 w″之间存在高度相关到非常高相关(r 范围为 0.55 到 0.83)。然而,在平行滑雪转向时,r 的值较低到中等(r = 0.04-0.47)。可以得出结论,滑雪板沿滑雪板的均匀变形是一种过于简化的说法,因为 w″模式不仅在时间上而且在分段上都有所不同,具体取决于所采用的技术和转弯阶段。在外滑雪板的刻滑中,后部被认为在外滑雪板的边缘清洁和精确转弯中起着关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a9a/10141132/9488c08fe4a6/sensors-23-03997-g0A1.jpg

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