ArticleSensors (Basel, Switzerland)2024
Radar Sensor Data Fitting for Accurate Linear Sprint Modelling.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Does Placement of Timing Sensors and Sprinting Model Alter Force-Velocity Metrics? A GNSS Simulation Study.Sensors (Basel, Switzerland) · 2026Article
- Assessment of asymmetry and trajectory during repeated twenty-meter sprints in court sports wheelchair athletes.Frontiers in sports and active living · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAccurate linear sprint modelling is essential for evaluating athletes' performance, particularly in terms of force, power, and velocity capabilities. Radar sensors have emerged as a critical tool in capturing precise velocity data, which is fundamental for generating reliable force-velocity (FV) profiles. This study focuses on the fitting of radar sensor data to various sprint modelling techniques to enhance the accuracy of these profiles. Forty-seven university-level athletes (M = 23, F = 24; 1.75 ± 0.1 m; 79.55 ± 12.64 kg) participated in two 40 m sprint trials, with radar sensors collecting detailed velocity measurements. This study evaluated five different modelling approaches, including three established methods, a third-degree polynomial, and a sigmoid function, assessing their goodness-of-fit through the root mean square error (RMSE) and coefficient of determination (r
resultsSignificant differences (
conclusionsThe results suggest that radar sensors, combined with appropriate modelling techniques, can significantly improve the accuracy of sprint performance analysis, offering valuable insights for both researchers and coaches. Care should be taken when comparing results across studies employing different modelling approaches, as variations in model fitting can impact the derived metrics.
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Registered trials
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