Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China.
School of Future Science and Engineering, Soochow University, Suzhou 215299, China.
Sensors (Basel). 2024 Aug 15;24(16):5291. doi: 10.3390/s24165291.
In cross-country skiing, ski poles play a crucial role in technique, propulsion, and overall performance. The kinematic parameters of ski poles can provide valuable information about the skier's technique, which is of great significance for coaches and athletes seeking to improve their skiing performance. In this work, a new smart ski pole is proposed, which combines the uniaxial load cell and the inertial measurement unit (IMU), aiming to provide comprehensive data measurement functions more easily and to play an auxiliary role in training. The ski pole can collect data directly related to skiing technical actions, such as the skier's pole force, pole angle, inertia data, etc., and the system's design, based on wireless transmission, makes the system more convenient to provide comprehensive data acquisition functions, in order to achieve a more simple and efficient use experience. In this experiment, the characteristic data obtained from the ski poles during the Double Poling of three skiers were extracted and the sample -test was conducted. The results showed that the three skiers had significant differences in pole force, pole angle, and pole time. Spearman correlation analysis was used to analyze the sports data of the people with good performance, and the results showed that the pole force and speed ( = 0.71) and pole support angle ( = 0.76) were significantly correlated. In addition, this study adopted the commonly used inertial sensor data for action recognition, combined with the load cell data as the input of the ski technical action recognition algorithm, and the recognition accuracy of five kinds of cross-country skiing technical actions (Diagonal Stride (DS), Double Poling (DP), Kick Double Poling (KDP), Two-stroke Glide (G2) and Five-stroke Glide (G5)) reached 99.5%, and the accuracy was significantly improved compared with similar recognition systems. Therefore, the equipment is expected to be a valuable training tool for coaches and athletes, helping them to better understand and improve their ski maneuver technique.
在越野滑雪中，滑雪杖在技术、推进和整体表现方面起着至关重要的作用。滑雪杖的运动学参数可以提供有关滑雪者技术的有价值信息，这对于寻求提高滑雪表现的教练和运动员来说非常重要。在这项工作中，提出了一种新的智能滑雪杖，它将单轴力传感器和惯性测量单元（IMU）结合在一起，旨在更轻松地提供全面的数据测量功能，并在训练中发挥辅助作用。滑雪杖可以收集与滑雪技术动作直接相关的数据，例如滑雪者的杖力、杖角、惯性数据等，而基于无线传输的系统设计使系统更加方便，提供全面的数据采集功能，以实现更简单、更高效的使用体验。在这项实验中，从三位滑雪者的双杖推进中提取了滑雪杖的特征数据并进行了样本测试。结果表明，三位滑雪者的杖力、杖角和杖时均存在显著差异。采用 Spearman 相关分析对表现良好的运动员的运动数据进行分析，结果表明杖力与速度（=0.71）和杖支撑角（=0.76）呈显著相关。此外，本研究采用常用的惯性传感器数据进行动作识别，结合力传感器数据作为滑雪技术动作识别算法的输入，五种越野滑雪技术动作（对角跨步（DS）、双杖推进（DP）、踢双杖推进（KDP）、二步滑行（G2）和五步滑行（G5））的识别准确率达到 99.5%，与类似的识别系统相比，准确率有显著提高。因此，该设备有望成为教练和运动员的有价值的训练工具，帮助他们更好地了解和改进滑雪动作技术。
