Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care. Study 1

NCT06646120 | Withdrawn

• 1 other identifier: 1791994(1)
• Study Type: observational
• Target: N/A
• Locations: 0 countries
• Sites: N/A

Brief Summary

The goal of this observational study is to train and validate an AI-driven 3D camera system to estimate total body weight, ideal body weight and lean body weight in male and female adult volunteers of all ages. The main questions this study aims to answer are:

• What degree of accuracy of weight estimation can we achieve with an AI-driven 3D camera weight estimation system?
• Is this accuracy the same in adults of both sexes, all ages, and all body types (underweight, normal weight, overweight)? Participants will undergo some anthropometric measurements (height, mid-arm circumference, weight circumference, hip circumference, measured weight), a DXA scan (to measure lean body weight), and 3D imaging using a 3D camera. There will be no interventions.

Conditions

Body Weights and Measures; Body Weight in the Overweight and Obese Class - I Population

Keywords

3D camera weight estimation; computer vision weight estimation

Outcome Measures

Primary Outcomes (3)

• TBW estimation

  Accuracy of TBW estimation using 3D camera system

  Baseline

• IBW estimation

  Accuracy of IBW estimation using 3D camera system

  Baseline

• LBW estimation

  Accuracy of LBW estimation using 3D camera system

  Baseline

Secondary Outcomes (3)

• Sex-related accuracy

  Baseline

• Age-related accuracy

  Baseline

• BMI-related accuracy

  Baseline

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Students, staff and faculty at the Boca Raton campus of Florida Atlantic University.

You may qualify if:

• Any willing volunteer.

You may not qualify if:

• Participants with a body weight exceeding the DXA machine capacity \>204kg (450lbs);
• Pregnant participants;
• Participants with medical conditions that could confound the study;
• Participants with any metallic surgical implants;
• Participants who have had an x-ray with contrast in the past week;
• Participants who have taken calcium supplements in the 24 hours prior to the study.

Sponsors & Collaborators

• Florida Atlantic University: lead

Related Publications (7)

• Sonar VG, Jan MT, Wells M, Pandya A, Engstrom G, Shih R, Furht B. Estimating Body Volume and Height Using 3D Data. arxiv. 2024 September; 2410.02800

  BACKGROUND

• Jan MT, Kumar A, Wells M, Pandya A, Engstrom G, Shih R, Furht B. Comprehensive Survey of Body Weight Estimation: Techniques, Datasets and Applications. Multimedia Tools and Applications. 2024 October

  BACKGROUND

• Wells M, Goldstein L. Appropriate Statistical Analysis and Data Reporting for Weight Estimation Studies. Pediatr Emerg Care. 2023 Jan 1;39(1):62-63. doi: 10.1097/PEC.0000000000002862. Epub 2022 Oct 1. No abstract available.

  PMID: 36190388 BACKGROUND

• Wells M, Goldstein LN, Cattermole G. Development and Validation of a Length- and Habitus-Based Method of Ideal and Lean Body Weight Estimation for Adults Requiring Urgent Weight-Based Medical Intervention. Eur J Drug Metab Pharmacokinet. 2022 Nov;47(6):841-853. doi: 10.1007/s13318-022-00796-3. Epub 2022 Sep 19.

  PMID: 36123560 BACKGROUND

• Wells M, Goldstein LN. Estimating Lean Body Weight in Adults With the PAWPER XL-MAC Tape Using Actual Measured Weight as an Input Variable. Cureus. 2022 Sep 17;14(9):e29278. doi: 10.7759/cureus.29278. eCollection 2022 Sep.

  PMID: 36277563 BACKGROUND

• Wells M, Goldstein LN, Alter SM, Solano JJ, Engstrom G, Shih RD. The accuracy of total body weight estimation in adults - A systematic review and meta-analysis. Am J Emerg Med. 2024 Feb;76:123-135. doi: 10.1016/j.ajem.2023.11.037. Epub 2023 Nov 29.

  PMID: 38056057 BACKGROUND

• Wells M, Goldstein LN, Wells T, Ghazi N, Pandya A, Furht B, Engstrom G, Jan MT, Shih R. Total body weight estimation by 3D camera systems: Potential high-tech solutions for emergency medicine applications? A scoping review. J Am Coll Emerg Physicians Open. 2024 Oct 4;5(5):e13320. doi: 10.1002/emp2.13320. eCollection 2024 Oct.

  PMID: 39371964 BACKGROUND

MeSH Terms

Conditions

Body Weight

Condition Hierarchy (Ancestors)

Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Design

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

Study Record Dates

• First Submitted: October 15, 2024
• First Posted: October 17, 2024
• Study Start: July 1, 2025
• Primary Completion (Estimated): June 30, 2026
• Study Completion (Estimated): June 30, 2026
• Last Updated: December 19, 2025

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will share