Validation of Artificial Intelligence-based Digital Anthropometry Applications for Estimating Body Composition.
NCT ID: NCT07003516
Last Updated: 2025-06-04
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
130 participants
OBSERVATIONAL
2025-01-11
2025-12-31
Brief Summary
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Detailed Description
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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.
Conditions
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Study Design
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OTHER
CROSS_SECTIONAL
Study Groups
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Sedentary
It will be obtained by open call for both students and administrative staff at the CES University.
No interventions assigned to this group
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.
No interventions assigned to this group
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.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Persons born and living in the cities of the participating universities
* Signed informed consent to undergo evaluation of anthropometric measurements.
Exclusion Criteria
* Amputations
* Pregnant women.
* People with implants or prostheses.
18 Years
60 Years
ALL
No
Sponsors
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CES University
OTHER
Universidad de Córdoba
OTHER
ARTHROS Centro de Fisioterapia y Ejercicio
UNKNOWN
Dynamical Business and Science Society - DBSS International SAS
NETWORK
Responsible Party
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Principal Investigators
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Diego A Bonilla, PhD
Role: PRINCIPAL_INVESTIGATOR
Research Division, DBSS International SAS.
Jorge L Petro, PhD
Role: STUDY_CHAIR
Research Division, DBSS International SAS
Locations
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Universidad CES
Medellín, Antioquia, Colombia
Fundación Universitaria del Área Andina
Bogotá, Bogota D.C., Colombia
Fundación Universitaria del Área Andina
Pereira, Risaralda Department, Colombia
Countries
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Central Contacts
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Facility Contacts
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Related Links
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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.
Other Identifiers
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CyberMetron_DBSS
Identifier Type: -
Identifier Source: org_study_id
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