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

Validation and Development of Digital Anthropometry Methodologies.

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.

Study Overview

• Status: Recruiting
• Conditions: Body Composition

Detailed Description

Anthropometric measurements are commonly used to assess body composition, morphology, and health-related parameters in diverse populations. Although it is an economical and practical method in the field, the COVID-19 pandemic has propelled worldwide research on digital anthropometry. Machine learning, a fusion of artificial intelligence and data mining, promises to enhance the collection and analysis of data in applications that rely on cineanthropometric data.

Instead of replacing traditional methods, digital anthropometry represents a significant opportunity to improve the precision, validity, practicality, and implementation of self-monitoring procedures under professional supervision. The CyberMetron Project by DBSS aims to conduct additional research and increase scientific literacy among professionals to raise awareness about digital anthropometry.

Data will be collected from residents of both genders and with different levels of physical activity. The population sample will be obtained through internal calls to both students and administrative staff at participating universities and through an open call. Anthropometric variables of restricted and complete profiles established by ISAK will be measured, along with digital images taken at different distances from the lens. Regarding the sample size, it will be conducted by convenience (non-probabilistic), primarily considering university students, administrative staff, and other potentially eligible adults who respond to the study announcement and sign the informed consent.

Finally, all statistical analyses will be performed within the statistical computing environment R v4.2.3, with a statistical significance of P<0.05. Pearson's correlation coefficient (r), adjusted determination coefficient (aR²), and Lin's concordance correlation coefficient (ρc) will be used for comparative analysis between main variables taken by conventional anthropometry and digital anthropometry. The coefficient of repeated measures correlation (rrm) will be employed to assess the strength of the linear association between variables, while the intraclass correlation coefficient (ICC), with its corresponding 95% confidence interval (95% CI), and Finn's coefficient (rF) will be used to evaluate reliability between evaluators. Additionally, the Bland-Altman analysis will be applied for the concordance analysis between conventional and digital anthropometry.

• Study Type: Observational
• Enrollment (Estimated): 130

Contacts and Locations

• Study Contact: Name: Diego A Bonilla; Phone Number: +573203352050; Email: dabonilla@dbss.pro

Study Locations

• Colombia
  • Bogota, Colombia, 111221
    • Recruiting
    • Fundación Universitaria del Area Andina
    • Contact: Luis A. Cardozo, MSc; Phone Number: +573133270327; Email: lcardozo11@areandina.edu.co
  • Antioquia
    • Medellin, Antioquia, Colombia, 050021
      • Recruiting
      • Universidad CES
      • Contact: Katherine Franco-Hoyos, MSc; Phone Number: +573002719536; Email: kfranco@ces.edu.co
  • Risaralda
    • Pereira, Risaralda, Colombia, 110231
      • Recruiting
      • Fundación Universitaria del Area Andina
      • Contact: Juan C Granados, MSc; Phone Number: +573174609496; Email: jcgranados@dbss.pro

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: No

• 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.

Description

Inclusion Criteria:

• 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.

Exclusion Criteria:

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

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort
Sedentary; It will be obtained by open call for both students and administrative staff at the CES University.
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.
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
Measurements of dual-energy X-ray absorptiometry	Estimation of fat mass and fat-free mass by DXA will be used as the reference method.	10 Minutes

Collaborators and Investigators

• Sponsor: Dynamical Business and Science Society - DBSS International SAS
• Collaborators: Universidad de Córdoba; CES University; ARTHROS Centro de Fisioterapia y Ejercicio
• Investigators: Principal Investigator: Diego A Bonilla, PhD, Research Division, DBSS International SAS.; Study Chair: Jorge L Petro, PhD, Research Division, DBSS International SAS

Publications and helpful links

Helpful 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 record dates

Study Major Dates

• Study Start (Actual): January 11, 2025
• Primary Completion (Estimated): June 1, 2025
• Study Completion (Estimated): December 1, 2025

Study Registration Dates

• First Submitted: February 21, 2025
• First Submitted That Met QC Criteria: June 2, 2025
• First Posted (Actual): June 4, 2025

Study Record Updates

• Last Update Posted (Actual): June 4, 2025
• Last Update Submitted That Met QC Criteria: June 2, 2025
• Last Verified: June 1, 2025

More Information

Terms related to this study

• Keywords: Artificial intelligence; Data mining; Machine learning; Mobile Applications; Kinanthropometry; 3D Image
• Other Study ID Numbers: CyberMetron_DBSS

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No