Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care: Study 2

Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care: Study 2 - Measure the Accuracy and Speed of Weight Estimations Using a 3D Camera System During Simulated Medical Emergencies

The goal of this prospective crossover simulation study is to evaluate the accuracy and usability of a 3D camera weight estimation system during simulated emergency care in adult simulated patients, when used by emergency physicians. The main questions the study aims to answer are:

• to evaluate the accuracy of 3D camera weight estimation during simulated emergency care, when compared with standard methods
• to evaluate the usability of 3D camera weight estimation during emergency care, when compared with standard methods
• to evaluate the inter-user reliability of 3D camera weight estimates Volunteers for simulated patients will be required to have anthropometric measurements, a DXA scan, and 3D camera weight estimates.

Physician volunteers will need to participate in simulated emergency scenarios during which weight-based therapy must be administered.

There will be no interventions.

The performance of the 3D camera system needs to be evaluated in conditions in which it will be used in a clinical setting, but without the risk to patients. It also needs to be compared against other, standard, methods of weight estimation. In addition the downstream accuracy of drug doses, with the correct use of alternative dose scalars (such as ideal body weight or lean body weight) in patients with obesity needs to be evaluated.

In this prospective crossover simulation study, resident and attending emergency physician volunteers will conduct simulated emergency care on simulated patient volunteers. The physicians will be randomised to start with either 3D camera systems, or standard care systems. After completing the scenario they will perform a new simulation scenario on a different patient using standard methods of weight estimation (crossover). At the end of the data collection session, each physician will have performed four scenarios (two standard methods, two 3D camera methods). Each simulated patient will similarly have participated in two standard method scenarios and two 3D camera scenarios. Each simulated patient and each physician will only have a single encounter.

In this way the accuracy of weight estimation and drug dosing can be compared between the 3D camera system and standard methods. In addition, inter-rater reliability can be determined and compared between resident and attending physicians.

Inclusion Criteria for simulated patients:

• Any volunteer aged ≥18 years.

Exclusion Criteria for simulated patients:

• 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.

Inclusion criteria for Emergency Physicians:

- Any willing emergency medicine resident or attending physician.

Exclusion criteria for Emergency Physicians:

- Any physical limitation to performing anthropometric measurements as part of simulation scenario.