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

NCT07003516 | Recruiting

• 1 other identifier: CyberMetron_DBSS
• Study Type: observational
• Target: 130
• Locations: 1 country
• Sites: 3

Brief 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

Keywords

Kinanthropometry; Artificial intelligence; Data mining; Machine learning; Mobile Applications; 3D Image

Outcome Measures

Primary Outcomes (2)

• Anthropometric measurements

  Anthropometric measurements of restricted and complete profile established by ISAK will be taken, specifically the basic measurements, perimeters (cm), lengths (cm) and diameters (cm).

  40 Minutes

• Body composition and morphology by digital anthropometry

  The evaluation will be performed using a mobile application that processes standardized frontal and lateral photographs as input. Participants will assume the ISAK anatomical position, which corresponds to standing upright with relaxed arms at sides (hands in neutral position) and feet positioned at biacromial width (aligned with the application's frame markers). After sufficient processing time for automated report generation, we will export data to the participant's designated file and store the generated 3D avatar.

  15 Minutes

Secondary Outcomes (1)

• Measurements of dual-energy X-ray absorptiometry

  10 Minutes

Study Arms (3)

Sedentary

It will be obtained by open call for both students and administrative staff at the CES University.

Physically active

DBSS will open a call for participation to get a sample of personal trainers and physically active population that want to be involved as sample participants.

Athletes

Under the collaboration framework between DBSS international SAS and ARTHROS Physiotherapy and Exercise Center, a sample of professional athletes from different sports disciplines will be invited to participate.

Eligibility Criteria

• Age: 18 Years - 60 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

The population sample is obtained through internal calls to both students and administrative staff of the participating universities, as well as through an open call, taking advantage of the collaboration agreement between DBSS International and Smart Fit.

You may qualify if:

• People over 18 years of age (under 60 years of age)
• Persons born and living in the cities of the participating universities
• Signed informed consent to undergo evaluation of anthropometric measurements.

You may not qualify if:

• Body mass ≥ 160 kg
• Amputations
• Pregnant women.
• People with implants or prostheses.

Sponsors & Collaborators

• Dynamical Business and Science Society - DBSS International SAS: lead
• CES University: collaborator
• Universidad de Córdoba: collaborator
• ARTHROS Centro de Fisioterapia y Ejercicio: collaborator

Study Sites (3)

Universidad CES

Medellín, Antioquia, 050021, Colombia

RECRUITING

Fundación Universitaria del Área Andina

Bogotá, Bogota D.C., 111221, Colombia

RECRUITING

Fundación Universitaria del Área Andina

Pereira, Risaralda Department, 110231, Colombia

RECRUITING

Related Links

• Interrelationships between body mass to waist circumference ratio, body mass index, and total body muscularity in older women
• Relative fat mass is a better tool to diagnose high adiposity when compared to body mass index in young male adults: A cross-section study.

Study Officials

• Diego A Bonilla, PhD

  Research Division, DBSS International SAS.

  PRINCIPAL INVESTIGATOR

• Jorge L Petro, PhD

  Research Division, DBSS International SAS

  STUDY CHAIR

Central Study Contacts

Diego A Bonilla

CONTACT

+573203352050; dabonilla@dbss.pro

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: NETWORK
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: February 21, 2025
• First Posted: June 4, 2025
• Study Start: January 11, 2025
• Primary Completion: June 1, 2025
• Study Completion: December 1, 2025
• Last Updated: June 4, 2025

Record last verified: 2025-06

Locations

CO (3)