Evidence map›Paper›PMID 41675556›Full record

ArticleFrontiers in sports and active living2025

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

Fabián Moya-Vergara, Ignacio Barrera-Gutiérrez, Pablo Arriaza-Marholz, Eduardo Piñones-Zuleta, Teresa Valverde-Esteve, Juan García-Manso, Enrique Arriaza-Ardiles, Marcos Zúñiga-Barraza

Abstract read
In one paragraph

Article in Frontiers in sports and active living, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Fabián Moya-VergaraDoctoral Program in Physical Activity and Sport, Faculty of Physical Activity and Sport Sciences, University of Valencia, Valencia, Spain.
Ignacio Barrera-GutiérrezElectronics Department, Universidad Técnica Federico Santa María, Valparaíso, Chile.
Pablo Arriaza-MarholzPhysical Activity and Sports Research Laboratory, Universidad de Playa Ancha, Valparaíso, Chile.
Eduardo Piñones-ZuletaDepartment of Engineering Design, Universidad Técnica Federico Santa María, Valparaíso, Chile.
Teresa Valverde-EsteveDepartment of Physical Education, Art and Music Teaching, University of Valencia, Valencia, Spain.
Juan García-MansoPhysical Activity and Sports Research Laboratory, Universidad de Playa Ancha, Valparaíso, Chile.
Enrique Arriaza-ArdilesPhysical Activity and Sports Research Laboratory, Universidad de Playa Ancha, Valparaíso, Chile.
Marcos Zúñiga-BarrazaElectronics Department, Universidad Técnica Federico Santa María, Valparaíso, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 × 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 Results: Professionals showed faster VMRS (0.77 ± 0.12 vs. 0.96 ± 0.12 s; Conclusion: NeuroSwift enabled standardized stimuli, automated footstep detection, and reproducible

Indexed as

athletic performancecomputer visiondecision-makingmotor skillspsychomotor performancereaction timesocceruser–computer interface

Identifiers

PMID41675556
PMCPMC12887892

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.