A BioEngineering approach for the SAFE design and fitting of Respiratory Protective Equipment (BE-SAFE RPE)
Lead Research Organisation:
University of Southampton
Department Name: Sch of Health Sciences
Abstract
Respiratory protective equipment (RPE) is widely used to limit the transmission of viruses and bacteria, representing a critical means of controlling Covid-19. In particular, respirator masks of the FFP3/N95 types, originally designed to protect against airborne dust particles, have been widely used to protect healthcare workers (Fig 1). It is essential that these masks fit tightly against the face to make an airtight seal, checked by fit testing. However, these masks are typically designed for a white male workforce, providing a limited range of size and geometry. This can lead to overtightening to compensate for a poor fit, which is associated with soft tissue injuries, as well as an increased risk of infection. This multidisciplinary project will investigate the fit and biomechanics of RPE devices, to ensure provision of a safe interface with users. Computational modelling and MRI will be used to explore how the soft tissues of the face deform in contact with a mask. These models will be informed through experimental monitoring of mechanical and thermal loads during RPE application and the associated changes in local skin physiology. In addition, the project will utilise existing databases of face shapes to investigate the fit of masks on a more representative range of users. This will lead to the development of design templates for new masks (working with UK manufacturers), standard test methods (STMs) to evaluate the risk of facial injury (working with testing and standards organisations), and intelligent fitting software to ensure that users select the correct mask.
Publications
Abiakam N
(2023)
Biophysical and biochemical changes in skin health of healthcare professionals using respirators during COVID-19 pandemic.
in Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
Caggiari S
(2022)
A combined imaging, deformation and registration methodology for predicting respirator fitting.
in PloS one
Caggiari S
(2022)
Biomechanical and Physiological Evaluation of Respiratory Protective Equipment Application.
in Medical devices (Auckland, N.Z.)
Chopra J
(2021)
The influence of gender and ethnicity on facemasks and respiratory protective equipment fit: a systematic review and meta-analysis.
in BMJ global health
Keenan BE
(2022)
MRI safety, imaging artefacts, and grid distortion evaluated for FFP3 respiratory masks worn throughout the COVID-19 pandemic.
in Clinical radiology
S Évora A
(2023)
Characterisation of superficial corneocytes in skin areas of the face exposed to prolonged usage of respirators by healthcare professionals during COVID-19 pandemic.
in Journal of tissue viability
| Description | The research team have been working with partners in the UK to identify key factors in fitting respiratory protective equipment in healthcare settings. In collaboration with our partners NHS England and Improvement we were able to access and analyze respirator fitting data from over 5000 NHS workers. We conducted a secondary analysis of a national database of fit testing outcomes collated between July to August 2020. Key demographics including age, gender, ethnicity and face measurements were compared to fitting outcome in a variety of respirator designs. A mixed-effects logistic regression model was used to determine the factors which affected fit testing outcome. During our analysis we included a total of 9,592 observations from 5,544 healthcare workers were included in the analysis. The mixed-effects logistic regression model identified that males experienced a significantly (p<0.05) higher fit test success than females (OR = 1.57; 95% CI: 1.31 to 1.88). Those with non-white ethnicities demonstrated significantly lower odds of successful mask fitting; Black (OR = 0.66; 95% CI: 0.51 to 0.86), Asian (OR = 0.60; 95% CI: 0.50 to 0.71) and Mixed (OR = 0.79; 95% CI: 0.64 to 0.99). Thus, this analysis demonstrated that in the early phase of COVID-19, females and non-White ethnicities were less likely to have a successful respirator mask fitting in England. Commercially available FFP3 respirators underwent an MR safety evaluation prior to commencing the MRI study. This identified three respirators that were safe for the volunteer to wear whilst in an electromagnetic field. Ten healthy volunteers were recruited to undergo several MRI scans with and without a respirator in situ. Both female and male (4 female / 6 male) volunteers participated in the study and consented to a quantitative fit test prior to their MRI examination. The Easimask FSM18 and Handanhy 9632 were a good fit for 60% of volunteers compared to only 10% successful fit for the GVS F31000. Up to 10mm of deformation observed in cheek soft tissue. Max Green Lagrange strains of up to 0.4 observed when participant is wearing a respirator. Gravity flattened the cheek soft tissues up to 3mm in supine during the participants MRI scan. In order to provide an intelligence means of identifying which masks fit specific face shapes a novel software application was developed. This was adapted from an algorithm designed to support prosthetics socket fitting and subsequently the goodness of fit of non-invasive respirator masks. To accommodate the materials that respirators are made from, a unique non-linear fitting method was implemented optimized through comparison to the MRI data. The algorithm was developed to reflect both gapping and indentation caused by commercial respirator devices. Several goodness of fit metrics are produced to support respirator assessment, these include a deformation value, gapping values and optimum fit percentage. As per the experimental data, the facial anthropometrics resulted in significant associations with goodness of fit parameters. |
| Exploitation Route | We are currently applying for further funding to extend this research. In addition, the reports to the Department of Health and Social Care, and NHS England and Improvement have enabled them to identify specific mask performance and trends in fitting outcomes. This will be used to create better understanding of respirators to procure and how to meet the needs of the diverse population of healthcare workers. |
| Sectors | Healthcare |
| Description | Our findings have been used by policy makers in NHS England and Improvement and the Department of Health and Social Care to understand fitting outcomes of respiratory protective equipment in the NHS. This was used to report back to government officials regarding respirator procurement and the need to increase the number of respirators available to accommodate the diverse population of healthcare workers. It also identified critical trends in fitting outcomes, and the need for improved fitting practices particularly in those with a non-white ethnicity. Working with NHS England and Improvement we have also supported the publication of guidelines to protect skin health whilst wearing personal protective equipment, which was informed by our research. |
| First Year Of Impact | 2021 |
| Sector | Healthcare |
| Impact Types | Policy & public services |
| Description | Guidelines for skin safety during the application of personal protective equipment |
| Geographic Reach | National |
| Policy Influence Type | Participation in a guidance/advisory committee |
| Impact | Published in April 2020 by NHS England and NHS Improvement to protect clinicians from pressure injuries, the guidelines, titled Helping prevent facial skin damage beneath personal protective equipment, include recommendations from the Group on the use of a barrier skin wipe, mask fitting (e.g. do not over-tighten), regular inspection and regular breaks from mask wearing (every two hours). |
| URL | https://www.england.nhs.uk/coronavirus/documents/helping-prevent-facial-skin-damage-beneath-personal... |
| Title | respirator fitting |
| Description | The dataset includes the face geometry (.stl files) of 8 individuals, scanned with a MRI 3D imaging technique, with and without respirator in situ (loaded and unloaded, respectively). It also includes for each individual the result of a respirator to face registration characterised by different degree of respirator's deformation and the respirator's goodness of fit result. MicroCT scan of the respirator and its corresponding parameters are also included. This data set was generated between 28.12.2020 and 27.06.2022. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Data set for publication |
| URL | https://doi.org/10.5258/SOTON/D2381 |
| Description | Department of Health and Social Care |
| Organisation | Government of the UK |
| Department | Department of Health and Social Care |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | We have analysed fitting outcome data from the DHSC from 70,000 NHS workers in a range of clinical settings. Using logistic regression analysis we could determine the best performing respirators and regions in the UK. |
| Collaborator Contribution | The provision of fitting outcome data from 70,000 healthcare workers. Presenting and attendance at key stakeholder sandpit events organised by the BE-SAFE team. |
| Impact | Report back to the DHSC regarding fitting outcome data and ongoing collaboration on developing a tool to support respirator fitting. This involved healthcare scientists, bioengineers and statisticians. |
| Start Year | 2021 |
| Description | NHS England and Improvement |
| Organisation | NHS England |
| Department | NHS Institute for Innovation and Improvement |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | We collaborated with NHS England and Improvement to analyse 6 months of respiratory protective equipment fitting outcome data. This was reported back to key individuals in the organisation and the Department of Health. The results from the retrospective analysis has also resulted in a manuscript being submitted. Following this collaboration, NHS England and Improvement have reported to the government regarding respiratory protective equipment inequalities and have continued to work with the team in following sandpit events. |
| Collaborator Contribution | NHS England and Improvement provided data from 50,000 respirator fittings within NHS hospitals. The data included the gender, ethnicity and age of participants, along with outcomes from specific respirator testing. They have attended sandpit events and supported our research investigations. |
| Impact | Report to NHS England and Improvement regarding factors affecting respiratory protective equipment fitting. This involved a multidisciplinary team of healthcare scientists, bioengineers and statisticians. |
| Start Year | 2021 |
| Title | COntactless Mask Fit-testing sYstem (COMFY) |
| Description | Scanning tool for the prediction of respirator fitting in healthcare workers. |
| Type | Support Tool - For Fundamental Research |
| Current Stage Of Development | Early clinical assessment |
| Year Development Stage Completed | 2022 |
| Development Status | Under active development/distribution |
| Impact | A first in kind tool to support respirator protective equipment fitting in NHS workers using a technology platform. Clinical study conducted in IRAS ethics (IRAS ID: 300826, Sponsor reference number: RHM O&G0298). |
| Title | AmpScan - respirator modification |
| Description | The software enables individuals to import head scans, fit a respirator and establish goodness of fit parameters. |
| Type Of Technology | Software |
| Year Produced | 2021 |
| Open Source License? | Yes |
| Impact | Currently under evaluation. |
| Description | BE-SAFE RPE sandpit event |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | The sandpit meeting is designed to promote exchange of ideas between these clinicians, industrialists, academics and partners. Knowledge transfer will be a key outcome throughout the network, achieved through the established partnership and the proposed expansion our collaborative network. Specific aims of the sandpit meeting are to provide: • An overview of the state-of-the-art in mask fitting outcomes and key research priorities • Opportunities for scientists and industrialists to translate their research into commercialization of new respiratory protective equipment • Directions for R&D, such that they meet the needs of healthcare workforce, including technologies for more efficient fitting protocols. • A convivial atmosphere with sufficient time for informal discussions, and encourage follow-up contacts between scientists, healthcare and medical personnel, and industrialists. We had 35 individuals attend from a range of sectors including respirator manufacturers, Department of Health and Social Care, NHS England and Improvement, fit testers working in different NHS hospitals, and academia. |
| Year(s) Of Engagement Activity | 2021 |