McGrath Joseph W, Neville Jonathon, Stewart Tom, Lamb Matt, Alway Peter, King Mark, Cronin John
Sports Performance Research Institute New Zealand, AUT University, Auckland, New Zealand.
Manukau Institute of Technology School of Sport, Auckland, New Zealand.
Sports Biomech. 2023 Nov 9:1-13. doi: 10.1080/14763141.2023.2275251.
This study examined whether an inertial measurement unit (IMU) could measure ground reaction force (GRF) during a cricket fast bowling delivery. Eighteen male fast bowlers had IMUs attached to their upper back and bowling wrist. Each participant bowled 36 deliveries, split into three different intensity zones: low = 70% of maximum perceived bowling effort, medium = 85%, and high = 100%. A force plate was embedded into the bowling crease to measure the ground truth GRF. Three machine learning models were used to estimate GRF from the IMU data. The best results from all models showed a mean absolute percentage error of 22.1% body weights (BW) for vertical and horizontal peak force, 24.1% for vertical impulse, 32.6% and 33.6% for vertical and horizontal loading rates, respectively. The linear support vector machine model had the most consistent results. Although results were similar to other papers that have estimated GRF, the error would likely prevent its use in individual monitoring. However, due to the large differences in raw GRFs between participants, researchers may be able to help identify links among GRF, injury, and performance by categorising values into levels (i.e., low and high).
本研究考察了惯性测量单元(IMU)能否在板球快速投球过程中测量地面反作用力(GRF)。18名男性快速投球手在其背部上方和投球手腕处佩戴了IMU。每位参与者投球36次,分为三个不同强度区域:低强度 = 最大感知投球力度的70%,中等强度 = 85%,高强度 = 100%。在投球线处嵌入一个测力板以测量实际的GRF。使用三种机器学习模型从IMU数据估计GRF。所有模型的最佳结果显示,垂直和水平峰值力的平均绝对百分比误差为22.1%体重(BW),垂直冲量为24.1%,垂直和水平加载率分别为32.6%和33.6%。线性支持向量机模型的结果最一致。尽管结果与其他估计GRF的论文相似,但该误差可能会阻碍其在个体监测中的应用。然而,由于参与者之间原始GRF的差异很大,研究人员或许能够通过将数值分类为不同水平(即低水平和高水平)来帮助识别GRF、损伤和表现之间的联系。