School of Public Education, Suzhou Institute Of Technology, Jiangsu University of Science And Technology，Zhangjiagang, 215600, China.
School of Public Education, Jiangsu University of Science And Technology, Zhangjiagang, 215600, China.
Prev Med. 2023 Aug;173:107582. doi: 10.1016/j.ypmed.2023.107582. Epub 2023 Jun 20.
In the field of sports, coaches have mainly relied on observing the performance of athletes on the spot to formulate suitable training plans for athletes, which has extremely high requirements for the professionalism of coaches. Based on the above requirements, this paper designs a sports action recognition system for sports enthusiasts based on the SVM algorithm optimization model, and for the purpose of verifying the applicability of the system to different sports fields, experiments are carried out on basketball actions and race walking actions. The system uses wearable sensors to capture the motion data of the user, and then analyzes and identifies the user's actions through the SVM algorithm optimization model. By standardizing the user's sports combination training under the system algorithm, the user can improve their training efficiency and reduce the risk of injury. To establish the human body motion model, this paper divides the human skeleton model into five motion branches. The rotation freedom constraints and joint rotation angle range limits are added to the model to ensure the accuracy of the motion analysis. Combining the forward kinematics of the robot and the homogeneous coordinate transformation, the human body joint rotation motion model and the human bone position and posture model are established. In the end, the user can standardize the sports combination training under the system algorithm. In this paper, through the research of wearable sensor technology and sports combined training action recognition, and apply it to practical life, it aims to promote its development and application.
在体育领域，教练主要依靠观察运动员在现场的表现来为运动员制定合适的训练计划，这对教练的专业性要求极高。基于上述要求，本文设计了一种基于 SVM 算法优化模型的体育爱好者运动动作识别系统，并为了验证系统对不同体育领域的适用性，在篮球动作和竞走动作上进行了实验。该系统使用可穿戴传感器来捕捉用户的运动数据，然后通过 SVM 算法优化模型对用户的动作进行分析和识别。通过系统算法对用户的运动组合训练进行标准化，可以提高用户的训练效率，降低受伤风险。为了建立人体运动模型，本文将人体骨骼模型分为五个运动分支。在模型中添加了旋转自由度约束和关节旋转角度范围限制，以确保运动分析的准确性。结合机器人的正运动学和齐次坐标变换，建立了人体关节旋转运动模型和人体骨骼位置与姿态模型。最后，用户可以在系统算法下对运动组合训练进行标准化。本文通过对可穿戴传感器技术和运动组合训练动作识别的研究，并将其应用于实际生活中，旨在促进其发展和应用。
