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Machine Learning-Guided Training for Elite Athletes (MLGT) (MLGT)

27. juni 2026 opdateret af: Dr. Arefayne Mesfen Dessye, Debre Berhan University

A Machine Learning-Guided Training Approach to Reduce Injuries and Enhance Performance in Elite Athletes: A Prospective Cohort Evaluation

Plaintext The purpose of this study is to evaluate whether a personalized training protocol driven by machine learning can successfully reduce time-loss sports injuries and enhance athletic performance in elite athletes.

During a 9-month competitive sports season, a group of elite athletes was divided into two training

Studieoversigt

Status

Afsluttet

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

This study evaluated the efficacy of an adaptive, machine learning-driven training protocol compared to traditional athletic preparation over a full 9-month competitive sports season. The primary objective was to determine if a dynamic, technology-led approach to training load management could minimize time-loss injuries while concurrently optimizing athletic performance markers.

Participants were elite athletes randomly allocated into two parallel groups:

  1. The Experimental Group, which underwent training regimens dynamically adjusted using a machine learning algorithm that analyzed individual biomechanical data and historical workload parameters to optimize training volume and intensity.
  2. The Control Group, which followed standard, predetermined high-performance athletic training protocols typical for competitive season preparation.

Throughout the 9-month intervention period, daily tracking was maintained by technical and coaching staff. Data collection focused on the incidence, severity, and duration of all time-loss sports injuries. Concurrently, sport-specific performance parameters were periodically assessed to evaluate physical conditioning and competitive readiness. Statistical analyses were subsequently conducted to compare cumulative injury rates, total days lost to injury, and net performance adaptations between the two cohorts.

Undersøgelsestype

Interventionel

Tilmelding (Faktiske)

120

Fase

  • Ikke anvendelig

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiesteder

    • Shewa
      • Debre Berhan, Shewa, Etiopien, 445
        • Dr. Arefayne
      • Debre Berhan, Shewa, Etiopien, 445
        • M Dessye

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Voksen

Tager imod sunde frivillige

Ja

Beskrivelse

Inclusion Criteria:

  1. Must be a competitive, elite-level or sub-elite track and field athlete specializing in short-to-mid distance running events.
  2. Aged between 18 and 35 years old.
  3. Actively participating in structured athletic training programs for at least 2 years prior to enrollment.
  4. Free from any acute musculoskeletal injuries or medical conditions that prevent full participation in high-intensity training protocols.
  5. Capable and willing to provide written informed consent to participate in the study.

Exclusion Criteria: 1. Current or recent (within the past 3 months) major lower-limb injury or surgery that restricts maximal sprint or aerobic performance.

2. Concurrent use of performance-enhancing drugs or medications that influence metabolic or cardiovascular responses.

3. Inability to maintain consistent participation in the designated training protocols due to scheduling conflicts or travel.

4. Any underlying cardiovascular, respiratory, or systemic condition that creates a health risk during exhaustive exercise testing.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Forebyggelse
  • Tildeling: Randomiseret
  • Interventionel model: Parallel tildeling
  • Maskning: Ingen (Åben etiket)

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Aktiv komparator: Control Cohort
Elite adolescent sprinters who followed standard, predetermined high-performance athletic training protocols typical for competitive season preparation. This group received structured training volume and intensity matching standard athletic coaching guidelines, without any machine learning interventions or adaptive workload adjustments.
A personalized, data-driven training intervention where athletic workloads are dynamically adjusted based on predictive modeling. The protocol continuously tracks individual physiological markers, biomechanical data, and workload history to optimize training volume and intensity. This adaptive approach aims to maximize performance gains while minimizing the risk of overtraining and injury during the competitive season.
Eksperimentel: Algorithmic Cohort
Elite adolescent sprinters who received a personalized training protocol dynamically optimized by a machine learning algorithm. The framework evaluated individual biomechanical variables, morning heart rate variability (HRV), sleep quality, and physiological fatigue metrics to adjust training volume and intensity.
A personalized, data-driven training intervention where athletic workloads are dynamically adjusted based on predictive modeling. The protocol continuously tracks individual physiological markers, biomechanical data, and workload history to optimize training volume and intensity. This adaptive approach aims to maximize performance gains while minimizing the risk of overtraining and injury during the competitive season.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Changes in Sprint Performance Time
Tidsramme: 12 weeks
Sprint performance will be assessed using electronic timing gates to record running times over a specific distance from a stationary start. Lower times indicate improved sprint performance. Measurements will be taken at baseline and at the conclusion of the training intervention period to evaluate the impact of the workload protocols.
12 weeks

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Efterforskere

  • Ledende efterforsker: Dr. Arefayne M Dessye, PhD, Debre Berhan Univeristy

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

1. januar 2023

Primær færdiggørelse (Faktiske)

30. september 2023

Studieafslutning (Faktiske)

30. september 2023

Datoer for studieregistrering

Først indsendt

27. juni 2026

Først indsendt, der opfyldte QC-kriterier

27. juni 2026

Først opslået (Faktiske)

6. juli 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

6. juli 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

27. juni 2026

Sidst verificeret

1. juni 2026

Mere information

Begreber relateret til denne undersøgelse

Yderligere relevante MeSH-vilkår

Andre undersøgelses-id-numre

  • DBU-SS-2023-008
  • IRB#DBU-SS-2023-008 (Registry Identifier: ClinicalTrials.gov)

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

IPD-planbeskrivelse

Individual participant data (IPD) will not be shared publicly to maintain the confidentiality of the elite athletes involved and to protect proprietary training protocols. Aggregated study results and statistical analyses will be available through academic publication.

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

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Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .

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