Body Weights and MeasuresNCT06645548
Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care. Study 3
A study testing Weight estimation using 3D camera in people with Body Weights and Measures and Body Weight in the Overweight and Obese Class - I Population, run by Florida Atlantic University.
Trial summary
The goal of this randomized controlled clinical trial is to compare standard methods of weight estimation and drug dose calculations against weight estimates and dose calculations using a 3D camera weight estimation system in critically ill or injured cohorts of patients presenting to the Emergency Department. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Body Weights and Measures, Body Weight in the Overweight and Obese Class - I Population, Drug Dose
- What is being tested?
- Weight estimation using 3D camera
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 0 participants
- Where
- No sites listed yet
- Study dates
- 1 Jul 2029to 1 Jul 2030
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Any patient presenting to the Emergency Department of the study site, who will require any form of weight-based intravenous drug therapy, and who will be admitted to the hospital.
Who cannot join
- Patients who are unable to provide consent.
- Patients whose medical treatment could be negatively impacted by participation in the study.
About this study
Official title: Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care. Study 3 - Measure the Accuracy of Weight Estimations by The 3D Camera System in Acutely Ill or Injured Emergency Department Patients and Compare This Accuracy Against That of Standard Care.
The goal of this randomized controlled clinical trial is to compare standard methods of weight estimation and drug dose calculations against weight estimates and dose calculations using a 3D camera weight estimation system in critically ill or injured cohorts of patients presenting to the Emergency Department. The main question[s] it aims to answer are:
Are weight estimates from a 3D camera system more accurate than standard methods of weight estimation? Do patients who receive weight estimates with a 3D camera system have fewer drug dosing errors than patients receiving standard care?
Read more
Participants will either receive a weight estimate using a 3D camera system, or standard methods of care.
Researchers will compare the 3D camera group to those with standard care to see if the weight estimates are more accurate, to see if drug dosing is more accurate, and to compare the incidence of adverse events related to medications in each group.
Read the detailed description
Drug dosing errors can have a catastrophic effect in acutely ill patients such as stroke patients needing thrombolytic therapy or patients requiring urgent sedation. In an acutely ill patient, inaccurate weight estimates are a significant cause of dosing errors, and weight estimates that deviate by >10% from actual weight could make treatment itself life threatening. Inaccurate weight estimates lead to inaccurate drug doses, which can result in potentially fatal treatment failure (from subtherapeutic doses) or potentially fatal adverse events (from supratherapeutic doses). Nearly 75% of treatment failures in obese patients may be related to errors in weight estimation. When clinical care is time-sensitive, it may be impossible to obtain a measured weight in >50% of patients. In these circumstances, a rapid, accurate method for estimating weight is critical. One recent innovation is the use of a low-cost 3D camera system to estimate weight. The 3D camera device (e.g., Intel RealSense D415) is used to obtain a point cloud map of the patient's body, from which a weight estimate can be estimated based on algorithms derived using convoluted neural network analysis. Initial studies have been extremely promising in terms of the accuracy achievable by this system in estimating Total Body Weight (TBW).
The primary aim of this study is to measure the accuracy of weight estimations by the 3D camera system in acutely ill or injured ED patients and compare this accuracy against that of standard care. The researchers will compare the performance and downstream effects of weight estimation using the 3D camera system against standard care in a randomized controlled trial of acutely ill or injured adults presenting to the ED.
The key hypothesis is that the 3D camera system will provide real-time estimates of TBW, IBW and LBW in an emergency setting and will exceed the accuracy of existing methods of weight estimation.
Supporting non-clinical trial studies will establish the accuracy of the 3D camera system in laboratory conditions, and in simulated medical emergencies. However, its performance, and its impact on downstream drug dosing accuracy, needs to be established during emergency care in a real clinical setting. This study will provide an essential perspective about the accuracy and functioning of the 3D camera system as well as real-world weight estimation during emergency care. It will also describe the ability to measure weight using in-bed scales and to obtain weight estimations from patients themselves and family members in ED patients. The secondary objective, to determine the accuracy of drug doses in each arm of the study, will provide critical information on the need for alternative weight scalars in obese and morbidly obese patients presenting to the ED. The study will establish the need for standards and policies to guide dose scaling in obese patients in the ED. Information on the actual usage of drugs that should be scaled to TBW and those that should be scaled to LBW will provide useful real-world insight into the magnitude of the problem in the threat to patient safety by using a "one size fits all" approach to drug dose calculations for all patients, irrespective of weight status.
Acutely ill patients presenting to the ED of a large regional hospital, and who require weight-based drug therapy, will be enrolled in the study. They will be randomised to either receive a weight estimation using a 3D camera system (which will provide estimates of TBW, IBW and LBW), or to receive standard care. All other interventions and medical care will be standard care.
These patients will be followed for the first 72 hours of their hospital stay. The accuracy of the weight estimates will be compared between the groups, as will the drug dose accuracy, and any adverse events related to drug therapy.
- Conditions
- Body Weights and Measures, Body Weight in the Overweight and Obese Class - I Population, Drug Dose, Weight Estimate
- Being tested
- Weight estimation using 3D camera
- Keywords
- Weight estimation, Emergency drug dose, 3D camera weight estimate, computer vision
- Medical subject headings
- Body Weight
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Weight estimation using 3D cameraOther
Also called Weight estimation using computer vision
Total body weight, ideal body weight and lean body weight estimates will be obtained using a 3D camera system. This weight will be used for calculation of weight-based drug doses and other weight-based interventions.
| Study group | Role | What they receive |
|---|---|---|
| Control arm (standard care) | No intervention | TBW, LBW and IBW will be estimated using standard care processes. All relevant medical care will be based on this weight for the first 72 hours |
| 3D camera weight estimation | Experimental | TBW, LBW and IBW will be automatically estimated using the 3D camera system. All relevant medical care will be based on this weight for the first 72 hours Receives: Other: Weight estimation using 3D camera |
What is being measured
The primary outcome is the main question the study is designed to answer.
Weight estimation accuracy
Determination of accuracy of estimates of total body weight, ideal body weight and lean body weight against reference standards
Measured: Immediately on enrolment
Time to obtain weight estimate
Measurement of time taken to obtain weight estimate
Measured: Immediately on enrolment
Drug dosing accuracy
Determination of accuracy of drug doses against reference standard
Measured: First 72 hours after enrolment
Correct dosing scalar used
Determination of appropriateness of dosing scalar used for each drug
Measured: First 72 hours after enrolment
Secondary outcomes (1)
Accuracy of in-bed scales
Determination of accuracy of weight estimate from in-bed or in-stretcher scales against reference standard
Measured: First 72 hours after enrolment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Oct 2024
- Study start1 Jul 2029 (estimated)
- Primary completion30 Nov 2029 (estimated)
- Study completion1 Jul 2030 (estimated)
Why it stopped: No funding received.
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (8)Papers the sponsor has linked to this study.
- Other trials for Body Weights and MeasuresStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Intervention cohort (3D camera weight estimation) and control cohort (standard care) will be used
- Masking
- Double blind
- Who is masked
- Investigator, Outcomes assessor
- Enrolment
- 0 participants (actual)
Sponsor and investigators
- Lead sponsor
- Florida Atlantic University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06645548
- Sponsor's protocol ID
- 1791994(3)
- Status last verified
- Dec 2025
- First submitted
- 15 Oct 2024
- Last updated
- 19 Dec 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Data generated during this project will be shared in multiple different forums. Data will be shared locally at Florida Atlantic University through presentations. Results will be made available to the broader scientific community through publications and presentations at national and international meetings. Protocols and/or method(s) developed during the proposed study will be made readily available for educational, research, and non-profit purposes, provided that a data-sharing agreement is signed. Any other important techniques developed from this work will be made available electronically for all non-business purposes described above. The intended date for such availability will be less than 6 months after the fulfillment of the Specific Aims of this proposal. In addition, a dataset containing non-identifiable point cloud data and images, along with ground truth weight data, will be stored in a repository that can be accessed through a data-sharing agreement.
Publications
Wells M, Goldstein LN, Cattermole G. Development and validation of a length- and habitus-based method of total body weight estimation in adults. Am J Emerg Med. 2022 Mar;53:44-53. doi: 10.1016/j.ajem.2021.12.053. Epub 2021 Dec 28.
PubMed 34974251Wells 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.
PubMed 36277563Wells 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.
PubMed 36123560Wells 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.
PubMed 36190388Wells 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.
PubMed 38056057Sonar 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
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.
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.
PubMed 39371964
Study at a glance
From the registry record, last updated by the sponsor on 19 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care. Study 3 - Measure the Accuracy of Weight Estimations by The 3D Camera System in Acutely Ill or Injured Emergency Department Patients and Compare This Accuracy Against That of Standard Care.
- ClinicalTrials.gov ID
- NCT06645548
- Acronym / sponsor ID
- 1791994(3)
- Conditions
- Body Weights and Measures, Body Weight in the Overweight and Obese Class - I Population, Drug Dose, Weight Estimate
- Keywords
- Weight estimation, Emergency drug dose, 3D camera weight estimate, computer vision
- Study type
- Interventional
- Recruitment status
- WithdrawnReason stopped: No funding received.
- Enrolment
- 0 participants (actual)
- Lead sponsor
- Florida Atlantic UniversityUniversity, hospital or other
- Study start
- 1 Jul 2029 (estimated)
- Primary completion
- 30 Nov 2029 (estimated)
- Study completion
- 1 Jul 2030 (estimated)
- First posted
- 17 Oct 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this randomized controlled clinical trial is to compare standard methods of weight estimation and drug dose calculations against weight estimates and dose calculations using a 3D camera weight estimation system in critically ill or injured cohorts of patients presenting to the Emergency Department. The main question[s] it aims to answer are:
Are weight estimates from a 3D camera system more accurate than standard methods of weight estimation? Do patients who receive weight estimates with a 3D camera system have fewer drug dosing errors than patients receiving standard care?
Participants will either receive a weight estimate using a 3D camera system, or standard methods of care.
Researchers will compare the 3D camera group to those with standard care to see if the weight estimates are more accurate, to see if drug dosing is more accurate, and to compare the incidence of adverse events related to medications in each group.
Detailed description
Drug dosing errors can have a catastrophic effect in acutely ill patients such as stroke patients needing thrombolytic therapy or patients requiring urgent sedation. In an acutely ill patient, inaccurate weight estimates are a significant cause of dosing errors, and weight estimates that deviate by >10% from actual weight could make treatment itself life threatening. Inaccurate weight estimates lead to inaccurate drug doses, which can result in potentially fatal treatment failure (from subtherapeutic doses) or potentially fatal adverse events (from supratherapeutic doses). Nearly 75% of treatment failures in obese patients may be related to errors in weight estimation. When clinical care is time-sensitive, it may be impossible to obtain a measured weight in >50% of patients. In these circumstances, a rapid, accurate method for estimating weight is critical. One recent innovation is the use of a low-cost 3D camera system to estimate weight. The 3D camera device (e.g., Intel RealSense D415) is used to obtain a point cloud map of the patient's body, from which a weight estimate can be estimated based on algorithms derived using convoluted neural network analysis. Initial studies have been extremely promising in terms of the accuracy achievable by this system in estimating Total Body Weight (TBW).
The primary aim of this study is to measure the accuracy of weight estimations by the 3D camera system in acutely ill or injured ED patients and compare this accuracy against that of standard care. The researchers will compare the performance and downstream effects of weight estimation using the 3D camera system against standard care in a randomized controlled trial of acutely ill or injured adults presenting to the ED.
The key hypothesis is that the 3D camera system will provide real-time estimates of TBW, IBW and LBW in an emergency setting and will exceed the accuracy of existing methods of weight estimation.
Supporting non-clinical trial studies will establish the accuracy of the 3D camera system in laboratory conditions, and in simulated medical emergencies. However, its performance, and its impact on downstream drug dosing accuracy, needs to be established during emergency care in a real clinical setting. This study will provide an essential perspective about the accuracy and functioning of the 3D camera system as well as real-world weight estimation during emergency care. It will also describe the ability to measure weight using in-bed scales and to obtain weight estimations from patients themselves and family members in ED patients. The secondary objective, to determine the accuracy of drug doses in each arm of the study, will provide critical information on the need for alternative weight scalars in obese and morbidly obese patients presenting to the ED. The study will establish the need for standards and policies to guide dose scaling in obese patients in the ED. Information on the actual usage of drugs that should be scaled to TBW and those that should be scaled to LBW will provide useful real-world insight into the magnitude of the problem in the threat to patient safety by using a "one size fits all" approach to drug dose calculations for all patients, irrespective of weight status.
Acutely ill patients presenting to the ED of a large regional hospital, and who require weight-based drug therapy, will be enrolled in the study. They will be randomised to either receive a weight estimation using a 3D camera system (which will provide estimates of TBW, IBW and LBW), or to receive standard care. All other interventions and medical care will be standard care.
These patients will be followed for the first 72 hours of their hospital stay. The accuracy of the weight estimates will be compared between the groups, as will the drug dose accuracy, and any adverse events related to drug therapy.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (investigator, outcomes assessor)
- Number of arms
- 2
- Model description
- Intervention cohort (3D camera weight estimation) and control cohort (standard care) will be used
| Arm | Type | Receives |
|---|---|---|
| Control arm (standard care) | No intervention | –TBW, LBW and IBW will be estimated using standard care processes. All relevant medical care will be based on this weight for the first 72 hours |
| 3D camera weight estimation | Experimental | Other: Weight estimation using 3D cameraTBW, LBW and IBW will be automatically estimated using the 3D camera system. All relevant medical care will be based on this weight for the first 72 hours |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- Any patient presenting to the Emergency Department of the study site, who will require any form of weight-based intravenous drug therapy, and who will be admitted to the hospital.
Key exclusion criteria (2 listed)
- Patients who are unable to provide consent.
- Patients whose medical treatment could be negatively impacted by participation in the study.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Weight estimation using 3D cameraAlso: Weight estimation using computer visionTotal body weight, ideal body weight and lean body weight estimates will be obtained using a 3D camera system. This weight will be used for calculation of weight-based drug doses and other weight-based interventions. | Other | 3D camera weight estimation |
Primary outcome
Weight estimation accuracy
Time frame: Immediately on enrolment
Determination of accuracy of estimates of total body weight, ideal body weight and lean body weight against reference standards
Time to obtain weight estimate
Time frame: Immediately on enrolment
Measurement of time taken to obtain weight estimate
Drug dosing accuracy
Time frame: First 72 hours after enrolment
Determination of accuracy of drug doses against reference standard
Correct dosing scalar used
Time frame: First 72 hours after enrolment
Determination of appropriateness of dosing scalar used for each drug
1 secondary outcome
Accuracy of in-bed scales
Time frame: First 72 hours after enrolment
Results and safety
The study was withdrawn before enrolling participants, so there are no results.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Dec 2025.
- Background: PubMed 34974251Wells M, Goldstein LN, Cattermole G. Development and validation of a length- and habitus-based method of total body weight estimation in adults. Am J Emerg Med. 2022 Mar;53:44-53. doi: 10.1016/j.ajem.2021.12.053. Epub 2021 Dec 28.
- Background: PubMed 36277563Wells 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.
- Background: PubMed 36123560Wells 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.
- Background: PubMed 36190388Wells 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.
- Background: PubMed 38056057Wells 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.
- BackgroundSonar 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
- BackgroundJan 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: PubMed 39371964Wells 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.
- Individual participant dataSharing planned: Yes. Data generated during this project will be shared in multiple different forums. Data will be shared locally at Florida Atlantic University through presentations. Results will be made available to the broader scientific community through publications and presentations at national and international meetings. Protocols and/or method(s) developed during the proposed study will be made readily available for educational, research, and non-profit purposes, provided that a data-sharing agreement is signed. Any other important techniques developed from this work will be made available electronically for all non-business purposes described above. The intended date for such availability will be less than 6 months after the fulfillment of the Specific Aims of this proposal. In addition, a dataset containing non-identifiable point cloud data and images, along with ground truth weight data, will be stored in a repository that can be accessed through a data-sharing agreement.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
A study testing Weight estimation using 3D camera in people with Body Weights and Measures and Body Weight in the Overweight and Obese Class - I Population, run by Florida Atlantic University.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: withdrawn, as of the sponsor's last update on 19 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study was withdrawn before enrolling participants, so there are no results.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Weight estimation accuracy (time frame: Immediately on enrolment). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06645548, which also lists 8 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Dec 2025.