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Model-based Systems for Professional Football Teams, Aimed at Optimizing Health and Performance

NCT05872945 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 54

Last updated 2024-11-13

No results posted yet for this study

Summary

LIST OF PLANNED ORIGINAL PUBLICATIONS

1. T wave inversion detection with machine learning to prevent sudden death in professional football players.
2. Machine learning applied to biological parameters for control and advisory in professional football players (Machine learning applied to biological parameters for control and advisory in professional football players.)
3. Machine learning applied to sport geolocation systems for injury prevention in professional football players.

Conditions

  • Electrocardiogram
  • Arrhythmias, Cardiac

Interventions

DIAGNOSTIC_TEST

Electrocardiogram

Study by Artificial Intelligence the biosignal or biodata from profesional football players

Sponsors & Collaborators

  • RCD Mallorca SAD

    lead OTHER

Principal Investigators

  • Adolfo Munoz Macho, Dr. · RCD Mallorca SAD

Eligibility

Min Age
18 Years
Max Age
45 Years
Sex
MALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-07-01
Primary Completion
2024-06-01
Completion
2024-07-30

Countries

  • Spain

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05872945 on ClinicalTrials.gov