A novel algorithm for determining contact area between a respirator and a headform

A combined imaging, deformation and registration methodology for predicting respirator fitting

N95/FFP3 respirators have been critical to protect healthcare workers and their patients from the transmission of COVID-19. However, these respirators are characterised by a limited range of size and geometry, which are often associated with fitting issues in particular sub-groups of gender and ethnicities. This study describes a novel methodology which combines magnetic resonance imaging (MRI) of a cohort of individuals (n = 8), with and without a respirator in-situ, and 3D registration algorithm which predicted the goodness of fit of the respirator. Sensitivity analysis was used to optimise a deformation value for the respirator-face interactions and corroborate with the soft tissue displacements estimated from the MRI images. An association between predicted respirator fitting and facial anthropometrics was then assessed for the cohort.

A critical review on the role of leakages in the facemask protection against SARS-CoV-2 infection with consideration of vaccination and virus variants

The protection provided by facemasks has been extensively investigated since the beginning of the SARS-CoV-2 outbreak, focusing mostly on the filtration efficiency of filter media for filtering face pieces (FFP), surgical masks, and cloth masks. However, faceseal leakage is a major contributor to the number of potentially infectious airborne droplets entering the respiratory system of a susceptible individual. The identification of leaking spots and the quantification of leaking flows are crucial to estimate the protection provided by facemasks. This study presents a critical review on the measurement and calculation of facemask leakages and a quantitative analysis of their role in the risk of SARS-CoV-2 infection. It shows that the pairing between the mask dimensions and the wearer's face is essential to improve protection efficiency, especially for FFP2 masks, and summarizes the most common leaking spots at the interface between the mask and the wearer's face. Leakage is a crucial factor in the calculation of the protection provided by facemasks and outweighs the filtration performances. The fit factors measured among mask users were summarized for different types of face protection. The reviewed data were integrated into a computational model to compare the mitigation impact of facemasks with vaccination with consideration of new variants of SARS-CoV-2. Combining a high adoption rate of facemasks and a high vaccination rate is crucial to efficiently control the spread of highly infectious variants.

Frame to Improve the Fit of N95 Filtering Face Mask Respirators

OBJECTIVE

Test a device that can improve upon the seal of filtering face mask respirators (FFRs).

METHODS

A 3-D prototype for a fit improvement frame (FIF) was created and quantitative fit testing was performed for FFRs with and without the FIF.

RESULTS

Thirty eight volunteers underwent fit testing. The overall fit pass rate was 100% for the 3M model 1860 masks, 50% for the 3M model 8511 masks, 13% for the BYD CARE model DE2322, and 7% for the Honeywell DC300N95. When using the FIF the overall passing rate increase to 87% for the DE2322 + FIF (P < 0.01) and for the DC300N95 + FIF the passing rate increase to 73% (P < 0.01).

CONCLUSION

The FIF is effective in improving the mask fit of a common flat fold N95 masks and potentially other N95 masks.

Use of 3D printing to support COVID-19 medical supply shortages: a review

The novel coronavirus, COVID-19, created a pandemic with significant mortality and morbidity which poses challenges for patients and healthcare workers. The global spread of COVID-19 has resulted in shortages of personal protective equipment (PPE) leaving frontline health workers unprotected and overwhelming the healthcare system. 3D printing is well suited to address shortages of masks, face shields, testing kits and ventilators. In this article, we review 3D printing and suggest potential applications for creating PPE for healthcare workers treating COVID-19 patients. A comprehensive literature review was conducted using PubMed with keywords "Coronavirus disease 2019", "COVID-19", "severe acute respiratory syndrome coronavirus 2", "SARS-CoV-2", "supply shortages", "N95 respirator masks", "personal protective equipment", "PPE", "ventilators", "three-dimensional model", "three-dimensional printing" "3D printing" and "ventilator". A summary of important studies relevant to the development of 3D-printed clinical applications for COVID-19 is presented. 3D technology has great potential to revolutionize healthcare through accessibility, affordably and personalization.

A computational model for predicting changes in infection dynamics due to leakage through N95 respirators

In the absence of fit-testing, leakage of aerosolized pathogens through the gaps between the face and N95 respirators could compromise the effectiveness of the device and increase the risk of infection for the exposed population. To address this issue, we have developed a model to estimate the increase in risk of infection resulting from aerosols leaking through gaps between the face and N95 respirators. The gaps between anthropometric face-geometry and N95 respirators were scanned using computed tomography. The gap profiles were subsequently input into CFD models. The amount of aerosol leakage was predicted by the CFD simulations. Leakage levels were validated using experimental data obtained using manikins. The computed amounts of aerosol transmitted to the respiratory system, with and without leaks, were then linked to a risk-assessment model to predict the infection risk for a sample population. An influenza outbreak in which 50% of the population deployed respirators was considered for risk assessment. Our results showed that the leakage predicted by the CFD model matched the experimental data within about 13%. Depending upon the fit between the headform and the respirator, the inward leakage for the aerosols ranged between 30 and 95%. In addition, the non-fit-tested respirator lowered the infection rate from 97% (for no protection) to between 42 and 80%, but not to the same level as the fit-tested respirators (12%). The CFD-based leakage model, combined with the risk-assessment model, can be useful in optimizing protection strategies for a given population exposed to a pathogenic aerosol.

Development of an algorithm for effective design of respirator half-masks and encapsulated particle filters

Objective. Social and economic situations in the modern world require new approaches to the development of respiratory protective equipment. This study aimed to improve the three-dimensional modeling process for respirator half-masks and encapsulated particle filters. Methods. Basic provisions of the theory of non-stationary filtration and hydroaerodynamics, the Nelder-Mead method and the linear interpolation equation were used. Results. The peculiarity of the algorithm is the adjustment stage of the design process aimed at checking efficiency of the half-mask. The surface of the half-mask was constructed according to the coordinates of a three-dimensional model of a worker's head. Conclusion. For the first time, the regularities of an algorithm for designing the half-mask surface of dust respirators were defined based on the data for three-dimensional coordinates of key points of anthropometric parameters of workers' faces. The pressure difference on the encapsulated particle filters of dust respirators is determined by the particle filter's resistance coefficient and air flow through them, and the diameter ratio of their outlets and inlets. The developed algorithm provides product verification at the design stage using criteria evaluating parameters of a polygonal model of the head, preliminary calculation of the protection factor and checking the tightness of the prototype.

Customized design and 3D printing of face seal for an N95 filtering facepiece respirator

Filtering Facepiece Respirator (FFR) is the most common respirator users in the health care environment utilize for personal protection from outside particles. Comfort and fit are important while wearing an FFR. This paper proposes a novel technology to produce customized face seal design for improving the wearing comfort and fit of FFR wearers. In order to customize the design of face seals, we scanned the faces of three subjects using three-dimensional (3D) laser scanning method. A customized face seal for a 3M 8210 N95 FFR for each headform was designed using reverse engineering technique. Next, the face seal prototypes were fabricated with Acrylonitrile Butadiene Styrene (ABS) plastic using the 3D printing method. A force sensing system based on Arduino Uno R3 was developed, and the force sensor of this system was inserted between the FFR and headform to measure contact pressure. Experimental results showed that the newly designed FFR face seal provided the subjects with an improved contact pressure.

Ergonomic evaluation of pilot oxygen mask designs

A revised pilot oxygen mask design was developed for better fit to the Korean Air Force pilots' faces. The present study compared an existing pilot oxygen mask and a prototype of the revised mask design with 88 Korean Air Force pilots in terms of subjective discomfort, facial contact pressure, and slip distance on the face in high gravity. The average discomfort levels, facial contact pressures, and slip distance of the revised mask were reduced by 33%-56%, 11%-33%, and 24%, respectively, compared to those of the existing oxygen mask. The mask evaluation method employed in the study can be applied to ergonomic evaluation of full- or half-face mask designs.

A method for evaluating aerosol leakage through the interface between protective suits and full-face respirators

Military personnel and first responders use a range of personal equipment including protective suits, gloves, boots, and respirators to prevent exposure of their skin and airways to hazardous chemical, biological, radiological, and/or nuclear substances. Although each individual item of personal protective equipment is well tested against existing standards, it is also necessary to consider the performance of the interfaces between items in terms of prevention from exposure, and the protection system as a whole. This article presents an aerosol challenge method for assessing the performance of the interface between a respirator and the hood of a protective suit. The interface is formed between the sealing strip of the hood and the surface of the respirator's outer sealing area and is affected by how well the sealing strip can cover and adapt to the sealing area. The method evaluates the leakage of particles of different sizes into the hood via the interface by particle counting at sampling points around the respirator's perimeter. Three different respirators were tested together with a single hood having a tight-fitting seal. The method variation between measurements was low but increased appreciably when the protective ensemble was re-dressed between measurements. This demonstrates the difficulty of achieving a reliable and reproducible seal between respirator and hood under normal conditions. Different leakage patterns were observed for the three respirators and were linked to some specific design features, namely the respirator's sealing area at the chin and its width at cheek level. Induced leak experiments showed that to detect substantial particle leakage, channels at the hood-respirator interface must be quite large. The method outlined herein provides a straightforward way of evaluating hood-respirator interfaces and could be useful in the further development of personal protective equipment.

Estimating the Dead Space Volume Between a Headform and N95 Filtering Facepiece Respirator Using Microsoft Kinect

N95 filtering facepiece respirator (FFR) dead space is an important factor for respirator design. The dead space refers to the cavity between the internal surface of the FFR and the wearer's facial surface. This article presents a novel method to estimate the dead space volume of FFRs and experimental validation. In this study, six FFRs and five headforms (small, medium, large, long/narrow, and short/wide) are used for various FFR and headform combinations. Microsoft Kinect Sensors (Microsoft Corporation, Redmond, WA) are used to scan the headforms without respirators and then scan the headforms with the FFRs donned. The FFR dead space is formed through geometric modeling software, and finally the volume is obtained through LS-DYNA (Livermore Software Technology Corporation, Livermore, CA). In the experimental validation, water is used to measure the dead space. The simulation and experimental dead space volumes are 107.5-167.5 mL and 98.4-165.7 mL, respectively. Linear regression analysis is conducted to correlate the results from Kinect and water, and R(2) = 0.85.