检索结果-内蒙古大学图书馆

Posture detection of athletes in sports based on posture solving algorithms

SYSTEMS AND SOFT COMPUTING 2024年 6卷

作者： Zhang, Huan Henan Coll Transportat Arts & Sports Dept Zhengzhou 450000 Peoples R China

With the rapid development of science and technology, the field of sports is constantly exploring and applying new technical means to improve the training effect and competitive level of athletes. Among them, the athletes' posture detection technology based on the attitude solving algorithm has been widely concerned in recent years. However, the current attitude solving algorithm has the limitation of low precision and low efficiency. Aiming at this, a new attitude solving algorithm is proposed. Firstly, the coordinate system is determined according to the theory of inertial navigation, and the attitude Angle is obtained by calculating the acceleration and magnetic induction intensity. Then the current attitude matrix is calculated according to the obtained attitude Angle. The initializing quaternion based on the attitude matrix is studied. Then, according to the advantages and defects of the three sensors, a complementary filtering algorithm is proposed for data fusion, so as to reduce the error of the final attitude solution. In order to further improve the accuracy of attitude detection, the complementary filter algorithm and double-layer Kalman filter algorithm are combined to process the data, and finally the quaternion is updated. It can be seen that the detection error of the research constructed model is only 9.94%, and its three attitude angle errors are mainly concentrated between -0.5 degrees and 0.5 degrees The model constructed by the research can realize high-precision posture detection, which can provide more scientific and reliable training aids for gymnastics, which has very strict requirements for movements in sports. It has positive significance for the development of sports.

关键词： Sports training complementary filtering algorithm Kalman filtering algorithm Attitude solving Inertial navigation

来源：评论

学校读者我要写书评

暂无评论

A Wireless Self-Powered Sensor Network Based on Dual-Model Convolutional Neural Network algorithm for Tennis Sports

引用

IEEE SENSORS JOURNAL 2023年第18期23卷 20745-20755页

作者： Li, Yulei Wu, Li Pingdingshan Univ Sch Phys Educ Pingdingshan 467000 Peoples R China Guangzhou Sport Univ Sch Phys Educ Guangzhou 510500 Peoples R China

More and more scholars turn their attention to the use of digital and systematic management methods to further improve the safety and effectiveness of tennis. At present, most of these systems are based on video monitoring technology, their actual operation process is limited by the deployment environment, and the cost is very high. In order to obtain the track of tennis players, this article uses the sensor array in the intelligent insole to collect the original data. A dual-model convolutional neural network (DMCNN) structure is designed to further improve the computational efficiency and accuracy of tennis players' gait recognition. Combined with a quaternion and complementary filtering algorithm, the rotation matrix is established to convert the data in the sensor coordinate system to the reference coordinate system. Use multiple sensors in the smart insole to collect linear and curve track data from tennis players. After the unit conversion and normalization of the original data, the acceleration and angular velocity data in the sensor coordinate system are converted to the reference coordinate system by using quaternions to represent the rotation matrix and using a complementary filtering algorithm to update the quaternions. The experimental results show that the displacement error of the scheme is small and the performance is good when the track tracking of tennis players is realized. The error between the estimated distance and the actual distance is within 6%, which proves the accuracy of the linear trajectory experiment.

关键词： complementary filtering algorithm dual-model convolutional neural network (DMCNN) inertial sensor step recognition trajectory tracking

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：