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Enabling Realistic HAZMAT Training Simulations with the PerSim™ Augmented Reality Patient Simulator

使用 PerSim™ 增强现实病人模拟器实现逼真的 HAZMAT 培训模拟

基本信息

批准号：
9752938
负责人：
Sohail Baig
金额：
$ 9.9万
依托单位：
MEDCOGNITION, INC.
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2020-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9752938
关键词：
Address Affect Agreement Algorithms Ambulances Augmented Reality Back Behavior Code Competence Corrosives Data Defibrillators Electricity Emergency medical service Emotional Environment Evaluation Gases Goals Hazardous Substances Health Human Resources Immersion Investigative Technique Individual Inhalation Interview Joints Learning Legal patent Literature Manikins Marketing Mechanics Medical Mission Mustard Myocardial Infarction National Institute of Environmental Health Sciences Organophosphates Outcome Participant Patient Simulation Patients Performance Phosgene Physiologic Monitoring Population Procedures Process Public Health Questionnaires Research Resolution Respiratory distress Savings Seizures Site Surface Symptoms System Tablets Text Texture Time Training Underserved Population Visual Work animation artist base cost first responder haptics heart rhythm improved innovation instructor learning outcome lectures novel novel strategies off-patent operation portability research and development response simulation sound success user centered design

项目摘要

Abstract Significance: Although patient simulators have demonstrated improved learning outcomes in medical training, there is a significant lack of realism. Thus, they do not effectively provoke a realistic emotional response in trainees. This significantly limits their educational value to the emergency medical service (EMS) training agencies, as does – in the case of mannequins – their cost, reliance on electricity, and lack of portability. To address these significant limitations of the current medical patient simulators, the PI has developed PerSimTM, a patient simulator using augmented reality (AR) and currently a product offered by the PI's company. However, additional research and development in is needed to effectively support HAZMAT training scenarios. Commercial Need: Based on interviews with individuals at training agencies within EMS agencies, HAZMAT training scenarios would be of significant value. Since being released in 4th quarter 2017, there are 4 sites that have purchased PerSimTM for ~$20-30K each and are using the system for EMS training, effectively training over 100 trainees per year. Moreover, the PI has a joint marketing agreement with Microsoft, which boost the company’s marketing efforts. Preliminary Data: The PI has developed PerSimTM an AR-based patient simulator. Via the Microsoft HoloLens AR display, the system projects high-resolution, realistic animations of a patient onto any surface a trainee chooses, such as low-fidelity mannequin as a physical reference for haptic input during procedures. The instructor uses a handheld tablet as both a controller for the simulation and an automated assessment system to track trainee performance. The system utilizes another tablet to act as a defibrillator and a physiologic monitor to provide real-time vital sign and heart rhythm data. The system’s control interfaces and registration algorithms are provisionally patented. Specific Aims: This project proposes to develop and evaluate HAZMAT training scenarios in the PI's innovative AR-based patient simulator, PerSimTM. In Specific Aim 1, the PI will work with medical artists from UT Health and a HAZMAT expert co-I to create realistic scenarios and integrate them with the PerSimTM system. The PI plans to develop textures and animations based on NFPA 472 Standard for Competence of Responders to Hazardous Materials, specifically poisonous gas (e.g., phosgene) inhalation, corrosive materials (e.g., a vesicular agent such as Mustard), and poisonous materials (e.g., organophosphate). In Specific Aim 2, the PI will evaluate the realism of the HAZMAT scenarios through user studies with HAZMAT professionals as participants.

摘要