Department of Mechanical Systems Engineering, Graduate School, Kookmin University, Seoul 02707, Korea.
Department of Sports and Health Rehabilitation, Kookmin University, Seoul 02707, Korea.
Sensors (Basel). 2022 Mar 28;22(7):2591. doi: 10.3390/s22072591.
In this study, an inertial measurement unit (IMU) sensor module and software algorithm were developed to identify anomalous kicks that should not be given scores in Taekwondo competitions. The IMU sensor module was manufactured with dimensions of 3 cm × 3 cm × 1.5 cm and consists of a high-g sensor for high acceleration measurement, a 9-DOF sensor, and a Wi-Fi module for wireless communication. In the experiment, anomalous kicks and normal kicks were collected by the IMU sensor module, and an AI model was trained. The anomalous kick determination accuracy of the trained AI model was found to be 97.5%. In addition, in order to check whether the strength of a blow can be distinguished using the IMU sensor module, an impact test was performed with a pendulum under the same test conditions as the impact sensor installed in the impact test setup, and the correlation coefficient was 0.99. This study is expected to contribute to improving scoring reliability by suggesting the possibility of discriminating anomalous kicks, which were difficult to judge in Taekwondo competitions, through the analysis of Taekwondo kicks using inertial data and impulses.
本研究开发了一种惯性测量单元(IMU)传感器模块和软件算法,以识别在跆拳道比赛中不应该计分的异常踢腿。IMU 传感器模块的尺寸为 3cm×3cm×1.5cm,由用于高加速度测量的高 g 传感器、9 自由度传感器和用于无线通信的 Wi-Fi 模块组成。在实验中,IMU 传感器模块采集异常踢腿和正常踢腿,并对 AI 模型进行训练。训练后的 AI 模型对异常踢腿的判定准确率达到 97.5%。此外,为了检查 IMU 传感器模块是否可以区分打击力度,在与冲击测试设置中安装的冲击传感器相同的测试条件下,使用摆锤进行了冲击测试,相关系数为 0.99。本研究通过使用惯性数据和冲量分析跆拳道踢腿,提出了区分在跆拳道比赛中难以判断的异常踢腿的可能性,有望提高评分的可靠性。