LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Tracking of Gymnast's Limb Movement Trajectory Based on MEMS Inertial Sensor

Photo from wikipedia

In order to track the limb movement trajectory of gymnasts, a method based on MEMS inertial sensor is proposed. The system mainly collects the acceleration and angular velocity data of… Click to show full abstract

In order to track the limb movement trajectory of gymnasts, a method based on MEMS inertial sensor is proposed. The system mainly collects the acceleration and angular velocity data of 11 positions during gymnastics by constructing sensor network. Based on the two kinds of preprocessed data, the parameters such as sample mean, standard deviation, information entropy, and mean square error are calculated as classification features, the support vector machine (SVM) classification model is established, and the movements of six kinds of gymnastics are effectively recognized. The experimental results show that when the human body is doing gymnastics, the measured three-axis acceleration values are between -0.5 g~2.2 g, -1 g~2.8 g, and -1.8 g~1 g, respectively, and the static error range accounts for only 1.6%~2% of the actual measured data range. Therefore, it is considered that such static error has little effect on the accuracy of data feature extraction and action recognition, which can be ignored. It is proved that MEMS inertial sensor can effectively track the movement trajectory of gymnasts' limbs.

Keywords: movement trajectory; inertial sensor; sensor; mems inertial

Journal Title: Applied Bionics and Biomechanics
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.