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

Recruiting

• Conditions: Body Composition

• Registration Number: NCT07003516
• Lead Sponsor: Dynamical Business and Science Society - DBSS International SAS

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.

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 Timeline

• Study Start: 2025-01-11
• Study First Submitted: 2025-02-21
• Status Verified: 2025-06
• Primary Completion: 2025-06
• Study First Submitted QC: 2025-06-02
• Last Update Submitted: 2025-06-02
• Study First Posted: 2025-06-04
• Last Update Posted: 2025-06-04
• Study Completion: 2025-12

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 130

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 & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Anthropometric measurements	40 Minutes	Anthropometric measurements of restricted and complete profile established by ISAK will be taken, specifically the basic measurements, perimeters (cm), lengths (cm) and diameters (cm).
Body composition and morphology by digital anthropometry	15 Minutes	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.

Secondary Outcome Measures

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

Trial Locations

Locations (2)

Universidad CES; 🇨🇴 Medellin, Antioquia, Colombia

Fundación Universitaria del Área Andina; 🇨🇴 Bogota, Colombia