Solutions to Improve Respirator Fit Testing Emerge from NIOSH Challenge
The winning solution from the final phase of NIOSH’s Respirator Fit Evaluation Challenge is an app that detects leaks or gaps along the face seal of a respirator using an infrared camera, the agency announced yesterday. According to NIOSH, the second-place solution is “a low-cost, open source, quantitative fit tester that pairs a unique non-destructive sampling probe with an open-source condensation particle counter to calculate a fit measurement.” The agency describes the solution that placed third as “a continuous pressure/temperature sensor that uses machine learning to notify the user of a respirator’s fit condition” during wear.
NIOSH’s crowdsourcing competition was intended to find practical solutions to improve respirator fit testing and progressed in multiple phases. The first phase involved competitors submitting concept papers outlining their solutions, and those who moved on to the second phase developed and demonstrated prototypes. For the third and final phase of the competition, NIOSH evaluated functional prototypes from the participants.
When NIOSH first announced the challenge, it stressed that small or disadvantaged workplaces often lack the resources required to conduct initial and annual fit testing to ensure that workers are wearing respirator models and sizes that fit correctly. The agency also noted that members of the public are increasingly wearing respirators such as N95s for protection against infectious diseases, wildfire smoke, and pollution, without knowing whether the equipment provides adequate protection.
“The winning technologies were designed to provide immediate evaluation and feedback to users on the fit of filtering facepiece respirators, enhancing both safety and effectiveness in real-world settings,” NIOSH’s news update states.
More information about the winners can be found on the challenge website.