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Your Environment. Your Health.

Current SBIR E-Learning Awards

Worker Training Program

The following descriptions of successful applications for current "SBIR E-Learning for HAZMAT and Emergency Response Requests for Applications" were provided by the applicants.

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

Application Number Principal Investigator Company
2 R44 ES030578-02 Baig, Sohail Medcognition, Inc.

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 PerSim™, a patient simulator using augmented reality (AR) and currently a product offered by the PI's company. However, additional research and development 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 the fourth quarter of 2017, four sites have purchased PerSim™ 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 boosts the company's marketing efforts. Preliminary Data: The PI has developed PerSim™, 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 a 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. This project proposes to develop and evaluate HAZMAT training scenarios in the PI's innovative AR-based patient simulator, PerSim™. 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 PerSim™ system. The PI plans to develop textures and animations based on the 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. The proposed research is relevant to public health because it enables more effective training of HAZMAT professionals, which will result in saving lives. This project is relevant to NIEHS's mission because it applies augmented reality in a novel approach to enhance the realism of HAZMAT simulation and training, thereby better preparing trainees for real scenarios.

HazPrep Worker Training - Community Risk Profile (Phase II)

Application Number Principal Investigator Company
5 R44 ES028145-03 Ryng, Henry inXsol, LLC

A worker's personal hazard profile (PHP) is a function of hazards present and his/her exposure level to those hazards. Workers with an elevated level of risk are those who can be engaged in activities related to – or working around – hazardous materials, waste generation, removal, containment, transportation, and emergency response. inXsol's Phase I feasibility study verified appeal and effectiveness of a new form of crowdsourced social learning platform. Our approach using cloud technology creates a dynamically growing library of incidents/scenarios, highly personalized (occupation/task/geo) risk profile and generates learning activities to train on risk awareness and mitigation techniques. The Phase II proposal includes implementation of an innovative use of big data algorithms for community profiles and fusion with PHP allowing for targeted and personalized training completing the HazPrep prototype developed and exercised by our beta test team in Phase I. HazPrep is a new form of a social learning platform, which includes crowdsourcing and machine learning AI to formulate personalized learning activities for at-risk workers with an elevated level of risk, such as those who can be engaged in activities related to – or working around – hazardous materials, waste generation, removal, containment, transportation, and emergency response. Actual incidents are ingested from OSHA, NFIRS, and other sources as scenarios/case studies.

Realistic Adaptive Immersive Learning System (RAILS) for HAZMAT Site Monitoring, Characterization and Remediation Training

Application Number Principal Investigator Company
2 R44 ES028143-02A1 Bautista, Carl Tim Spectral Labs, Inc.

The work proposed aims to develop an immersive videogame-based training program to train HAZMAT workers specifically involved in the emergency response, site characterization, waste removal, and site remediation at the extensively contaminated sites on the National Priorities List. Specific training will be designed to meet the mandates of 29 CFR 1910.120 for HAZWOPER training required for workers accessing Superfund sites and other employees who are exposed to hazardous substances through the clean-up, treatment, storage and disposal of hazardous waste, directly tackling the goals of the NIEHS Hazardous Waste Worker Training Program. The development will provide a first-person immersive training environment for the trainee to learn and practice key operational tasks such as site characterization and analysis, site control, monitoring, and decontamination by allowing the trainee to actively participate in the operation, performing tasks from the first person perspective, with realistic environments, equipment and tools. The trainee will be able to utilize accurately modeled instruments representative of those most commonly found in site emergency response, characterization, and remediation work. By simultaneously simulating both chemical and radiological hazards, the training will have unique capabilities specifically targeted to meet site-specific training requirements of the NIEHS/DOE Nuclear Worker Training Program. Specific Aims of the Phase II program include:

  • Develop six software modules to cover the topics 1910.120 (q) (6) (ii) (A)-(F), Emergency Response Program to Hazardous Substance Releases at the First-Responder Operations Level. This material has the advantage of having overlap with several other portions of the broader 1910.120 training, covering topics as personal protective equipment, decontamination, and emergency response for a wide range of HAZMAT workers.
  • Simulation and modeling of additional equipment to allow for training on the appropriate use and limitations of NFPA and OSHA personal protective equipment classes.
  • Environmental eevelopment and enhancement to provide a virtual training environment for control, containment and confinement training.
  • Software deployment and support to integrate feedback from International Association of Firefighters master trainers based on their testing of the software.
  • Software deployment and support to integrate feedback from instructors of the Environmental Hazardous Materials Technology courses at Southwestern College, with the goal of developing dual-use training software that meets their students learning requirements.
  • Produce a DOE-Site-Specific Radiation Training Module.

VR-Based Evaluation and Training System for Emergency Responders and Managers

Application Number Principal Investigator Company
2 R44 ES029348-02 Buras, William Robinson Tietronix Software, Inc.

Virtual and Augmented Reality (VR/AR) systems are increasingly being utilized as training platforms for complex, extremely demanding or rarely executed tasks. Often, VR systems focus primarily on delivering increasingly realistic scenarios for training purposes without any capability to assess or refine trainee performance in situ. Our novel VR training platform to deliver HAZMAT training not only delivers realistic scenarios, but also measures and evaluates performance using scientifically validated measures of variables associated with both individual and team performance. The advantage of our approach is to immerse first responders in HAZMAT emergency scenarios that are realistic and also designed to focus on measurement and refinement of specific areas of performance. Key contributors to performance among emergency responders and managers were identified by an extensive review of the literature and subsequent tested for association by psychometric assessment of over three hundred emergency responders. A subset of 18 highly associated contributors were then identified through statistical analysis of survey results. These contributors can be measurably represented in VR Training scenario elements. Performance related to each can then be measured and assessed for individual or team trainees. These refined key contributors can then be validated on larger, more diverse samples of emergency responders using the beta version of our proposed VR-based system. Our VR system is also a configurable platform that enables the evaluation and training of a wide range of skills needed by distinct roles (police, firefighters, EMTs, etc.) in diverse scenarios such as biosafety spills, HAZMAT disasters and bioterrorism threats. Also, HAZMAT disasters that are rare or very difficult/costly to create real world training events can be more easily and cost effectively mastered. Scenarios also can be dynamically modulated by trainer input in real-time, or by computerized Artificial Intelligence analysis of performance and trainee real-time physiological measures to rapidly optimize specific key contributor performance of individuals and teams. Rapid, efficient and effective training of emergency responders serves the ultimate goal of minimizing potential catastrophic consequences of these events.Our novel VR training platform to deliver HAZMAT training not only delivers realistic scenarios, but also measures and evaluates performance using scientifically validated measures of variables associated with both individual and team performance.

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