NeuroSwift: computer vision-based system to assess the cognitive-motor speed of soccer players-preliminary findings

Abstract

Background: Cognitive-motor speed (CMS) in soccer integrates perceptual-cognitive processing with motor execution, yet many tools lack this integration and have limited ecological validity. NeuroSwift was engineered as a computer vision-based automated analysis platform to standardize tactical stimuli and produce reproducible measurements. Methods: A 3 x 3 interaction surface, front-facing visual stimuli, and HD video were orchestrated by a web application. Twenty-nine players (15 professionals, 14 university athletes) completed 16 scenarios (8 offensive, 8 defensive). Visuomotor reaction speed (VMRS), displacement speed (DS), and response capacity (RC) were obtained, and cognitive-motor speed (CMS = VMRS + DS, in seconds) was computed. Normality and homogeneity were verified using Shapiro-Wilk and Levene's tests. VMRS and DS were compared using independent-samples t-tests (Bonferroni alpha = 0.0167). RC and CMS were assessed using the Mann-Whitney U test. Effect sizes were estimated. All tests were two-tailed, and confidence intervals were estimated where applicable. Results: Professionals showed faster VMRS (0.77 +/- 0.12 vs. 0.96 +/- 0.12 s; p < 0.001; d = 0.79), whereas university players showed faster DS (0.64 +/- 0.06 vs. 0.76 +/- 0.11 s; p < 0.001; d = -0.71). RC favored professionals (median 100.00% vs. 93.75%; Z = 3.13; p < 0.001; r = 0.58). CMS tended to favor professionals (median 1.53 s vs. 1.61 s) without significance (Z = -0.544; p > 0.05; r = 0.10). Conclusion: NeuroSwift enabled standardized stimuli, automated footstep detection, and reproducible in situ laboratory metrics. Expertise was discriminated in perceptual-cognitive and decision components, supporting athlete monitoring, training prescription, and applied research.