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Validation of Artificial Intelligence-based Digital Anthropometry Applications for Estimating Body Composition.

NCT07003516 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 130

Last updated 2025-06-04

No results posted yet for this study

Summary

Anthropometric measurements are commonly employed to evaluate body composition, morphology, and health-related parameters across diverse populations. While a cost-effective and field-friendly method, the COVID-19 pandemic has spurred research on digital anthropometry worldwide. Machine learning, a fusion of artificial intelligence and data mining, holds promise for enhancing data collection and analysis in Kinanthropometry applications. Rather than replacing traditional methods, digital anthropometry presents a significant opportunity to enhance accuracy, validity, practicality, and the implementation of self-monitoring procedures under professional guidance. The CyberMetron Project by DBSS aims to perform additional research and increase scientific literacy among practitioners for public awareness of digital anthropometry.

Conditions

  • Body Composition

Sponsors & Collaborators

  • CES University

    collaborator OTHER

  • Universidad de Córdoba

    collaborator OTHER

  • ARTHROS Centro de Fisioterapia y Ejercicio

    collaborator UNKNOWN

  • Dynamical Business and Science Society - DBSS International SAS

    lead NETWORK

Principal Investigators

  • Diego A Bonilla, PhD · Research Division, DBSS International SAS.

  • Jorge L Petro, PhD · Research Division, DBSS International SAS

Eligibility

Min Age
18 Years
Max Age
60 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-01-11
Primary Completion
2025-06-30
Completion
2025-12-31

Countries

  • Colombia

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 NCT07003516 on ClinicalTrials.gov