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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.

Agile Development of Innovative, Interactive Hazard Recognition and Mitigation Tools / Learning E-Platforms for Workers Involved in the Rescue and Recovery Operations in Diverse Flooding Environments

Application Number Principal Investigator Company
1 R43 ES030580-01 McLaughlin, Jeffery Radiant Creative Group, LLC

Flooding events continue to increase in both frequency and intensity. Workers involved in post-flood reconstruction work are at increased risk of adverse health effects due to respiratory exposures and other hazards. Proposed e-learning platform "Pocket Ark" provides training before flooding occurs, real-time decision support during a clean-up, and communications capabilities during and after clean-up to the workers involved. It addresses an important public health problem and uses a novel app-based e-learning platform to improve and enhance the cognitive understanding of flood-related health hazards within this vulnerable working population. The proposed research is relevant to public health because the safety of individuals participating in post-flood reconstruction is becoming increasingly more important in terms of the number of workers involved in this activity and the number of hazards they are exposed to in the aftermath of storms of increasing intensity. Our goal is to develop an e-learning platform called "Pocket Ark (PA)" that will: (1) disseminate and enhance the critical knowledge regarding hazards prior to being deployed (pre-deployment) in the flooded environment to protect the health of construction workers who may be involved in response and recovery operations (PA's multi-module interactive educational program), (2) provide workers with real-time data to assist with making safe decisions during the deployment phase in the flooded zone, and (3) provide a communications platform to improve logistics between operational bases and workers during and after the deployment to the flooded zone. It is a cross-platform mobile application with a cloud-based, service-oriented backend for data collection, analysis, reporting, and communication. The e-learning platform will be based on persuasive design strategies incorporated through the initial user feedback/survey. Our overall objective in this Phase I study is to develop an e-learning platform prototype and to evaluate its usability and appeal for the construction worker population working in flooded environments.

Augmented Reality Sensor Simulation System for HAZMAT Training

Application Number Principal Investigator Company
2 R44 ES028142-02 Bandera, Cesar Cell Podium

A goal of HAZMAT training exercises is to present learners with realistic tasks and experiences involving mock hazards, protective equipment (PPE), tools, and hazard sensors. However, while mock hazards, PPE, and tools are readily available to trainers, sensors that operate with mock hazards are not. Because the decisions that a HAZMAT worker makes are often dictated by the readings from sensors, making sensor readings and interpreting them are critical skills, and the ability of a HAZMAT training program to teach these skills is significant. Cell Podium proposes to develop, in collaboration with the Rutgers School of Public Health's Office of Public Health Practice, an augmented reality training system for realistic and experiential health and safety training of hazardous materials (HAZMAT) workers. The system meets key requirements assessed in Phase I. First, it includes handheld devices that look similar to handheld chemical and radiological hazard sensors and behave as though they were actual hazard sensors and the training hazards were real. The behavior is realistic both in terms of the exposure values displayed – themselves a function of the type of hazards in the exercise and their distance from the learner – and the response time to changes in the environment (e.g., if the instructor invokes a sudden chemical release or if the learner quickly runs to or from a hazard). To mitigate technological risk, Phase I successfully developed and tested a proof-of-concept of the proposed system and evaluated its performance at a Rutgers 40-hour Hazardous Waste Training course. A common practice in HAZMAT exercises is for the instructor to shout verbal descriptions of hazard exposure to the learner. This practice has several drawbacks: (1) much of the effort to make the exercise realistic to the learner is undone; (2) the skills of making, interpreting, and responding to continuous readings from handheld sensors are not rehearsed; (3) the instructor, who should be focused on advising and assessing the learner, bears the burden of serving as a prop in the simulation; and (4) the large size of the exercise, measured in either square feet or in number of concurrent participating learners, is limited by the reach of the verbal descriptions. The proposed system relieves the instructor from this burden so that s/he can focus on assessing the learners. A specific aim of the Phase II effort is that cost to acquire and operate the system be low and that it work with existing training program assets. To achieve this aim, the system hardware consists only of consumer cell phones to emulate the handheld hazard sensors and inexpensive miniature Bluetooth beacons (under $35 each) that are placed on each mock hazard of the exercise. Two systems will be deployed during the two-year Phase II period of performance: a minimum viable product will be released at the end of the first year, and a full-featured product at the end of the second year. To obtain market feedback and promote product usage, the system will be offered for free to WTP training grantees throughout the Phase II period of performance with help support. The business opportunity for augmented reality sensors extends beyond HAZMAT training organizations into markets that conduct internal HAZMAT training, including fire departments, utility companies, and military installations.

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

Application Number Principal Investigator Company
1 R43 ES030578-01 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
2 R44 ES028145-02A1 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.

Interactive Training in Emergency Operations for the Response Community

Application Number Principal Investigator Company
2 R44 ES025448-02 Venugopalan, Gautham Gryphon Scientific, LLC

In this Phase II SBIR, Gryphon Scientific proposes to develop a refresher training in the form of an interactive, mobile app that will allow two groups that are intermittent participants in disaster response to practice their emergency response skills after completing basic training. The app will target the research responders (RR) who were the focus of the Phase I project, as well as the "citizen responder" community including Community Emergency Response Teams (CERT) and the Medical Reserve Corps (MRC). Using three different disaster scenarios, modular active learning exercises will be presented in two tracks for the two responder types. The app will provide a creative means for maintaining trainee engagement after the completion of classroom sessions. It can also be used in a flipped classroom structure where students review classroom materials on their own and spend much of their classroom time in practice exercises. Recognizing that financial constraints often pose a barrier to the sale of novel commercial training products, the app will be deployed at no out-of-pocket cost to training organizations or trainees using an advertising-supported business model commonly encountered in the mobile video game market. Moreover, as a freely available app that will be deployed nationwide, the technology we propose provides a framework to study trends in citizen responder capabilities and improve curricula. CERT trainers (in over 2,600 programs nationwide) will be able to track knowledge decay and evaluate the long-term learning outcomes of their training programs. Formative research will be conducted using unstructured interviews with nine CERT volunteers and nine trainers to understand the learning styles and usage needs of our target populations and to develop appropriate learning objectives. Following the development in Unity of the iOS- and Android-compatible apps, usability testing will occur with seven experienced RRs, seven experienced CERT volunteers, and seven CERT trainers. The revised prototype will then be tested with up to 30 RRs and 60 CERT volunteers. Within RRs and CERTs, testers will be randomly assigned into three groups of equal size (10 for RRs, 20 for CERTs): (1) use the app on a recurring basis for three months, (2) use the app only once, at the start of the three-month period, and (3) a control group that receives no training. All testers will complete three short assessments: pre-training baseline, immediately post-training (or one week after the pre-assessment for the control group), and approximately three months following the date of first training. Based on the results of these assessments, the app will be revised, translated into Spanish, and deployed through CERT training providers and professional research organizations.

Preventing Opioid Exposure Training (POET) for First Responders

Application Number Principal Investigator Company
1 R43 ES030582-01 Rush, Margaret Andrews Gryphon Scientific, LLC

The U.S. opioid crisis, referring to the rapid increase in the 2010s of both prescription and non-prescription opioid abuse in the United States, is a major public health issue, with overdose deaths from opioids reaching epidemic levels, surpassing the number of gun-related deaths in 2016. While heroin remains the main illicit opioid abused in the U.S., a recent dramatic increase in the availability of synthetic opioids (mainly fentanyl and fentanyl-like substances) up to 10,000 times more potent than morphine has placed first responders at risk of accidental overdose and even death. The extreme potency of these substances, which can be accidentally ingested, inhaled, or absorbed through the skin or via contact with mucous membranes, means that accidental contact with even a minuscule amount can pose a severe threat to first responders. Responders can be exposed to fentanyl not only when responding to overdoses but also during the execution of search or arrest warrants and during the processing of drug or contaminated non-drug evidence. There is a clear need in the community for products to train first responders on how to effectively protect themselves while still performing their duties and providing timely and appropriate care. The computer-based Preventing Opioid Exposure Training (POET) will be an innovative learning product that teaches first responders about the risks of opioid exposures and how to recognize and manage these risks on the job. Training participants will learn to identify warning signs that they may be encountering a potential fentanyl exposure based on the signs and symptoms of a patient and/or the material observed at a scene. Then, the training will review risk assessment and selection of personal protective equipment (PPE) and guidelines for post-exposure treatment, clean-up, and decontamination. For Phase I, the training curriculum will be developed based on exposure guidelines published by federal agencies and other institutions, as well as interviews with stakeholders. This will be followed by usability testing of the prototype as well as a pre- and post-assessment of first responder knowledge gains at the end of training and three months later. This will contribute to shifting the paradigm of how novel training technologies can drive responder preparedness by using virtual worlds to teach first responders how to recognize and manage occupational risks. The potential commercial application of POET includes law enforcement officers at the local, state, and federal level; medical professionals (including EMTs, paramedics, and hospital staff); and other responders who face occupational opioid exposure risks. This product will include a 15- to 20-minute interactive learning experience and two five-minute immersive, realistic test scenarios.

Safety Using Augmented Reality to Facilitate Effective Training and Education (SAFE-TE)

Application Number Principal Investigator Company
1 R43 ES029351-01A1 Ma, Tony Xuyen Benten Technologies, Inc.

The objective of SAFE-TE is to support workers being trained to work with hazardous materials more efficiently.

The Occupational Safety and Health Act (OSHA) was formed to protect workers and prevent work-related injuries. OSHA standards include explicit safety and health training requirements to ensure that workers have required skills and knowledge to do their work safely. Benten Technologies is partnering with the International Brotherhood of Teamsters (IBT) to help workers in the HAZMAT/HAZWASTE industry gain the training they need to do their job safely and effectively. Benten will develop an augmented reality (AR) / mixed reality (MR) platform called "Safety using Augmented reality to Facilitate Effective Training and Education (SAFE-TE)" that enhances training in combination with classroom and practical training and that is more efficient, effective, and engaging than the traditional one. The platform will have programmable/configurable environments using Bluetooth beacons and fiducial markers to initially deliver the HAZWOPER Initial Hazardous Waste Worker training program to allow instructors to conduct simulated real-world training for individuals that work with hazardous materials and waste. The innovative AR mobile platform will allow IBT to conduct the already successful hazardous materials worker training program with ease. The objective of SAFE-TE is to support workers to work with hazardous materials more safely and efficiently. Approach: SAFE-TE will be initially designed and developed by Benten Technologies utilizing training scripts and curriculum provided by the IBT. The specific aims of this SBIR are (1) develop the prototype SAFE-TE platform integrating commercial components, such as Estimote's Bluetooth beacon and Samsung hardware, for training within workplace environments and (2) conduct a usability pilot test of SAFE-TE to test the effectiveness of AR training with 20 trainees and five instructors to augment practical hands-on training when compared with hands-on using props. The power that AR will have in HAZMAT/HAZWASTE training will be transformative for the industry because it will revolutionize many aspects of training from design and creation to how it is conducted. It will allow for instructor-led and -created training scenarios that incorporate AR technology to allow for mixed-reality training that accurately reflects the types of hazards that workers may encounter on a HAZWASTE site or during the transportation of hazardous materials. AR training will allow for realistic training using interactive drills, so the workers learn the relevant information they need in the environment they will be working in. This will aid in knowledge, skills, and aptitude retention and also allow the workers to reference the material later on as necessary since it will all be stored digitally. The comprehensive, integrated SAFE-TE platform is designed to supplement the HAZMAT Initial Hazardous Waste Worker Course for IBT by promoting trainee engagement and kinesthetic learning. SAFE-TE will allow trainees to interact with virtual images and figures to give them a realistic environment to apply the training they have received and therefore absorb the material in a more intuitive way.

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