An active machine learning framework for automatic boxing punch recognition and classification using upper limb kinematics.

ABSTRACT: Boxing punch type classification and kinematic analysis are essential for coaches and athletes, providing critical insights into punch variety and effectiveness, which are vital for performance improvement. Existing methods for punch recognition and classification typically rely on wearable sensor data or video data; however, no fully automated system currently exists. While coaches prefer video-based analysis for its ability to easily visualize punch action errors and refine technique, video-based classification suffers from lower accuracy compared to sensor-based methods due to limitations such as motion blur. Current classification approaches typically employ supervised learning, requiring experts to annotate 70-80% of the data for model training. However, the high sampling frequency of

SUBMITTER: Manoharan S 

PROVIDER: S-EPMC12061147 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature