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Reliability and validity of the "XingXun" system for measuring punch acceleration and velocity in elite boxers
Ji Qi1, Rangxi Jin2, Tongling Wang3
1College of Physical Education, Harbin Normal University, Harbin, Heilongjiang, China.
Introduction:
Punching velocity-related indicators are crucial in boxing, and accurately quantifying these metrics is significant for evaluating athletes' performance. This study aims to assess the reliability and validity of a commercial inertial sensor-based boxing training monitoring system ("XingXun") for measuring punch acceleration and velocity.
Methods:
Nine male boxers from the Shanghai University of Sport (age: 24.8 ± 3.1 years) with national-level competitive experience participated in the study. Participants wore "XingXun" sensors on both hands and performed maximum-effort tests involving six single punches (jabs, hooks, and uppercuts) and a 3-minute combination punch test. Concurrent validity was established by comparing the "XingXun" measurements against a 3D motion capture system (Qualisys) as the gold standard. Reliability was assessed using the Intraclass Correlation Coefficient (ICC) and Coefficient of Variation (CV). Validity was determined through Pearson correlation analysis, paired t-tests, Mean Deviation (MD), and Mean Absolute Error (MAE). Bland-Altman plots were used to visualize the agreement between the two systems.
Results:
The "XingXun" system demonstrated acceptable to excellent reliability for all punch types, with ICC values ranging from 0.883 to 0.950 and CV from 2.27% to 7.67% for acceleration and velocity. Validity analysis showed a strong correlation between the "XingXun" and Qualisys systems for both punch acceleration (r = 0.836-0.911) and velocity (r = 0.785-0.854). The measurement errors were small and not statistically significant (P > 0.05 or ES < 0.2), and Bland-Altman plots confirmed a high level of agreement between the two devices.
Conclusion:
The "XingXun" boxing training monitoring system is a reliable and valid tool for quantifying punch acceleration and velocity, offering a practical alternative to laboratory-based 3D motion capture for athlete performance monitoring.

