Enhancement of peripheral seal of medical face masks using a 3-dimensional-printed custom frame

Conducting quantitative mask fit tests: application details and affecting factors

Introduction

Respirators chosen based on their assigned protection factor (APF) enable wearers to effectively reduce particulate matter concentrations to safe levels when used correctly. As a crucial factor in achieving the intended APF, the fit test has become a necessary procedure in respiratory disease protection.

Methods

This study involved 225 participants who underwent a fit test using two reusable types of half masks and two types of full masks. Condensation nuclei counting (CNC) and controlled negative pressure (CNP) were performed.

Results

The results revealed that the passing rate of full masks was higher compared to half masks. Specifically, the passing rate for the half masks and the full masks were 84.7 and 91.6%, respectively. Gender exerted a statistically significant effect on the passing rate. Nevertheless, age, educational background, and training exhibited relatively negligible effects. Certain movements, such as facing forward, were identified as key actions with strong correlation. Additionally, talking was considered a key action with a high failure rate due to instantaneous leakages. Most participants failed at the initial step of CNP, but nearly all of them passed the fit test using CNC.

Discussion

Therefore, putting on full masks, especially for women, provides optimal protection during work. Furthermore, attention should be given to the displacement and deformation of the respirator during the key actions. When it comes to fit test methods, CNC was found to be more practical and comprehensive compared to CNP. Moreover, additional physiological characteristics, such as double chins, could be explored as potential influential factors.

Personalized 3D-printed frames to reduce leak from N95 filtering facepiece respirators: A prospective crossover trial in health care workers

Correctly fitting N95 filtering facepiece respirators (FFRs) have become increasingly important in health care throughout the COVID-19 pandemic. We evaluated the hypothesis that personalized 3D-printed frames could improve N95 FFRs quantitative fit test pass rates and test scores in health care workers (HCWs). HCWs were recruited at a tertiary hospital in Adelaide, Australia (ACTRN 12622000388718). A mobile iPhone camera + app was used to produce 3D scans of volunteers' faces, which were then imported into a software program to produce personalized virtual scaffolds suited to each user's face and their unique anatomical features. These virtual scaffolds were printed on a commercially available 3D printer, producing plastic (and then silicone-coated, biocompatible) frames that can be fitted inside existing hospital supply N95 FFR. The primary endpoint was improved pass rates on quantitative fit testing, comparing participants wearing an N95 FFR alone (control 1) with participants wearing the frame + N95 FFR (intervention 1). The secondary endpoint was the fit factor (FF) in these groups, and R-COMFI respirator comfort and tolerability survey scores. N = 66 HCWs were recruited. The use of intervention 1 increased overall fit test pass rates to 62/66 (93.8%), compared to 27/66 (40.9%) for controls. (OR for pFF pass 20.89 (95%CI: 6.77, 64.48, p < 0.001.) Average FF increased, with the use of intervention 1-179.0 (95%CI: 164.3,193.7), compared to 85.2 (95%CI: 70.4,100.0) with control 1. Pass rates and FF were improved with intervention 1 compared to control 1 for all stages of the fit-test: bending, talking, side-to-side, and up-down motion. (p < 0.001 all stages). Tolerability and comfort of the frame were evaluated with the validated R-COMFI respirator comfort score, showing improvement with the frame compared to N95 FFR alone (p = 0.006). Personalized 3D-printed face frames decrease leakage, improve fit testing pass rates and FF, and provide improved comfort compared to the N95 FFR alone. Personalized 3D-printed face frames represent a rapidly scalable new technology to decrease FFR leakage in HCW and potentially the wider population.

3D printed biomedical devices and their applications: A review on state-of-the-art technologies, existing challenges, and future perspectives

3D printing, also known as Additive manufacturing (AM), has emerged as a transformative technology with applications across various industries, including the medical sector. This review paper provides an overview of the current status of AM technology, its challenges, and its application in the medical industry. The paper covers the different types of AM technologies, such as fused deposition modeling, stereolithography, selective laser sintering, digital light processing, binder jetting, and electron beam melting, and their suitability for medical applications. The most commonly used biomedical materials in AM, such as plastic, metal, ceramic, composite, and bio-inks, are also viewed. The challenges of AM technology, such as material selection, accuracy, precision, regulatory compliance, cost and quality control, and standardization, are also discussed. The review also highlights the various applications of AM in the medical sector, including the production of patient-specific surgical guides, prosthetics, orthotics, and implants. Finally, the review highlights the Internet of Medical Things (IoMT) and artificial intelligence (AI) for regulatory frameworks and safety standards for 3D-printed biomedical devices. The review concludes that AM technology can transform the healthcare industry by enabling patients to access more personalized and reasonably priced treatment alternatives. Despite the challenges, integrating AI and IoMT with 3D printing technology is expected to play a vital role in the future of biomedical device applications, leading to further advancements and improvements in patient care. More research is needed to address the challenges and optimize its use for medical applications to utilize AM's potential in the medical industry fully.

Improving the fit of filtering facepiece respirators

Aims To assess the effectiveness and acceptability of smartphone customised frame technology to improve the fit of disposable filtering facepiece class 3 (FFP3) respirators for dental staff who previously failed fit testing.Method In total, 20 volunteers who previously failed FFP3 fit testing were recruited to use smartphone technology (Bellus3D FaceApp) to have a 3D-printed bespoke face frame produced for them. They underwent qualitative fit testing with and without the frame with two freely available disposable FFP3 respirator designs (mask A: GVS F31000 Segre folded model; mask B: Valmy Spireor). The order of testing was random. Ease of use of the smartphone technology and the comfort of the frame were determined by questionnaire.Results Fit test passes increased from 5% without the frame to 70% and 95%, respectively, for masks A and B with the frame (p <0.01). Very few participants reported using the technology as difficult (n = 1/20) or the frame uncomfortable (n = 3/20) or difficult to wear (n = 0/20).Conclusion Customised frames produced using smartphone technology improved qualitative fit test pass rates for two commonly available FFP3 respirators. Using smartphone technology for frame design, wearing a frame and frame comfort levels were all acceptable to the majority of participants.