Running Parameter Analysis in 400 m Sprint Using Real-Time Kinematic Global Navigation Satellite Systems

Area of Science:

• Biomechanics
• Sports Science
• Navigation Systems

Background:

• Accurate measurement of running parameters (step length, step frequency, velocity) is crucial for optimizing sprint performance.
• Traditional methods like 2D video analysis and inertial measurement units (IMUs) have limitations in precision and practicality for outdoor settings.
• Real-time kinematic global navigation satellite systems (RTK GNSS) present a potential alternative for high-frequency kinematic data acquisition.

Purpose of the Study:

• To introduce and evaluate two novel methods for estimating running parameters using 100 Hz RTK GNSS.
• To compare the accuracy and reliability of these RTK GNSS methods against established 3D video analysis and IMU data.
• To assess the suitability of RTK GNSS for detailed per-step sprint analysis, including curved sections and stride asymmetry detection.

Main Methods:

• Two methods for estimating running parameters were developed using 100 Hz RTK GNSS data.
• Method 1 identified mid-stance via vertical position minima; Method 2 utilized vertical velocity minima aligned with initial contact.
• Measurements were validated against 3D video analysis and IMU data during 400 m sprints by collegiate sprinters.

Main Results:

• Both RTK GNSS methods successfully estimated step frequency, step length, and velocity.
• Method 2 (vertical velocity minima) demonstrated superior accuracy with lower RMSE for SF (0.205 Hz vs. 0.291 Hz) and SL (0.143 m vs. 0.190 m) compared to Method 1.
• Method 2 showed higher correlation with reference data, better performance on curves, and more consistent detection of stride asymmetries.

Conclusions:

• RTK GNSS, particularly the velocity minima approach (Method 2), provides a robust, drift-free, single-sensor solution for per-step sprint analysis.
• This RTK GNSS method offers a practical and accurate alternative to IMU-based systems for outdoor running analysis.
• The findings support the use of RTK GNSS for enhanced training optimization and performance evaluation in track and field athletes.