Acoustic Assessment of a Novel Visor Concept with Aerodynamic Sealing for Medical Protection

Abstract—This paper details the acoustic evaluation and optimization of a new solid visor with aerodynamic sealing for medical care. This novel personal protective equipment (PPE) ensures effective aerodynamic sealing of the breathing zone, reducing the risk of inhaling infectious droplets and aerosols. To mitigate considerable noise from the air supply system, various solutions were investigated, including adjustments to air flow rate, tube diameter, tube insulation, tube splitter configurations, and the addition of physical barriers and a sound muffler. These optimizations reduced noise levels by 34.1 dBA for an air flow rate of 25 l/min, with a final prototype producing a noise level of 44.3 dBA. Speech Intelligibility Index (SII) significantly improved across all flow rates, reaching values close to 1. Comparison with surgical masks and FFP2 respirators was conducted to evaluate speech transmission, demonstrating the potential for enhanced acoustic performance this type of PPE.

Keywords: Air-curtain, Air-sealed visor, Acoustic assessment, Speech Intelligibility Index, PPE

Ingress

·         Acoustic assessment and optimization of a novel Personal Protective Equipment (PPE).

·         PPE uses an air curtain and a visor as infection control barriers.

·         Noise levels were reduced by 34. for an air flow rate of 25 l/min.

·         Speech Intelligibility Index improved from 0.17 to approximately 1.0.

·         PPE had slightly higher speech attenuation than surgical mask and FFP2 respirator.

I. Introduction

The COVID-19 pandemic has prompted the adaptation of safety measures in healthcare systems worldwide, emphasizing the importance of personal protective equipment (PPE) like masks, respirators, and face shields to mitigate airborne transmission risks.

Given the potential for future pandemics [1], [2], there's a growing demand for reliable PPE to safeguard essential workers. While traditional face masks have limitations [3], [4], visors provide enhanced comfort and eye protection [5]–[7]. However, their protection effectiveness compared to masks and respirators is typically lower [8], driving ongoing developments to improve PPE design for better comfort and effectiveness.

In response to the pandemic, novel PPE designs, including air-curtain sealed devices, have emerged [9]–[11]. Air curtains, initially introduced for protecting against aerosols and droplets, also show promise in industrial settings for safeguarding against gaseous contaminants and particulate matter [12], [13]. Positioned in front of the face, they effectively intercept and redirect potential contaminants, improving air quality. However, integrating air curtains into visors can produce significant noise, which can adversely affect human health and cause issues related to prolonged use of such PPE [14]–[16].

Among these innovative designs is the MASK4MC (Mask for Medical Care) [17], and its evolution, the VV4MC (Ventilated Visor for Medical Care), designed to offer additional protection against airborne transmission. This study focuses on evaluating and optimizing the acoustic performance of such novel air-curtain sealed PPE, considering noise levels, frequency characteristics, speech intelligibility, and the impact on speech transmission. This study aims to offer design solutions for future devices, aiding healthcare workers in preventing the spread of new viruses.

II. Methods

A. Description of the air curtain personal protective equipment

The design of the personal protective equipment (PPE) for medical professionals, as depicted in Figure 1, ensures comfort and safety in clinical settings. With its solid face shield (A in Figure 1) and air curtain provided by a two-chamber plenum (B in Figure 1), this PPE offers reliable protection against various airborne particles while seamlessly integrating with essential gear such as surgical masks, respirators, and goggles. The robust support system (C and D in Figure 1) not only guarantees a secure fit but also acts as a structural component, helping its assembly with the shield and plenum through screws (J in Figure 1).

As air is channelled through the main tube (E in Figure 1) and directed by the T-shaped splitter (F in Figure 1), it encounters polymeric barriers (I in Figure 1) to establish a stable air curtain, vital for safeguarding against contaminants. An airflow rate of 24.5 l/min was found to be optimal for stability and protection efficiency [18], achieving a velocity of approximately 0.5 m/s across the frontal jet outlets. The subsequent analysis will focus on evaluating the PPE's efficacy at an air flow rate of 25 l/min. Further details can be found in references [18], [19] and a complete analysis for more air flow rates can be also be found in reference [20].

Figure 1. MASK4MC illustration. Source: [20]

B. Experimental setup and procedures

The aim is to experimentally evaluate the acoustic performance of the PPE prototype and optimize it. Figure 2 illustrates the experimental setup used for measuring A-weighted Noise Equivalent Level, Third-Octave Frequency Distribution, and the Speech Intelligibility Index. Experiments were conducted in a controlled low-noise room during nighttime to mitigate external interferences.

Figure 2. Illustration of the experimental setup. Source: [20]

An acoustic manikin (Brüel & Kjær Sound Quality Head and Torso Simulator Type 4100) with built-in condenser microphones and a preamplifier within each ear was used for data acquisition of sound signals. The air supply system utilized the building’s compressed air network, comprising an additional air compressor tank, a pressure converter, a pressure control unit, and a flow meter.

LabView-based software applications [21]–[23] were employed for data acquisition of sound signals and analysis. A-weighted sound levels were used to account for human hearing sensitivity across the audible frequency spectrum. The A-weighting slightly amplifies the mid-range frequencies, where human hearing is most sensitive, while significantly attenuating the low-frequency region, where the sensitivity is reduced. The application of this weighting to the measurements is noticeable in the frequency spectra, particularly in the low-frequency range where the negative values indicate that sound levels, although present, fall below the human hearing threshold in those specific frequencies. The first experiment aimed to assess the impact of the PPE on ambient noise by measuring the values and one-third octave spectra over a 30 s period. The measurements were conducted under two conditions: without the PPE and with the manikin wearing the PPE, but without the air supply. The assessment of the PPE acoustic performance was initiated by measuring the sound levels without the air curtain flow and establishing the initial conditions (t = 0 s) for each experiment. After approximately 45 s, the air supply was then activated, and the desired air flow rate was set. To ensure the stabilization of the short-term equivalent continuous sound pressure level (Lpeq,T), data was acquired continuously over a period of 105 s. The total time for each experiment is 150 s. The equivalent continuous pressure levels for both the ambient noise (Leqroom) and total noise (Leqtot) were calculated using equation (1). The calculations were performed using data collected from t = 15 to 45 s, for ambient noise, and from 120 to 150 s, for total noise.

The evaluation of noise levels was based on the following equations:

Where n is the total number of sound pressure levels (Lpi) recorded over each measurement, Leqtot represents the measured total equivalent continuous sound pressure level, when air supply is turned on, and Leqroom the measured ambient equivalent continuous sound pressure level, when air supply is turned off. To obtain the LeqPPE, the equivalent continuous sound pressure level generated by the PPE, equation (2) is used.

The Speech Intelligibility Index (SII) was calculated following ANSI/ASA 3.5–1997 [24] standard.

To assess the impact of wearing the VV4MC on speech transmission, a comparative study using white noise was conducted considering other commonly used PPE. Figure 3 illustrates the experimental setup for the speech transmission study. A microphone was placed 2 meters apart from the manikin, which had a loudspeaker inside its head to emit the white noise (set to 67 dBA) (a in Figure 3). Figure 3 also depicts the different scenarios considered, including without any mask or visor (b in Figure 3), with a surgical mask (c in Figure 3), with an FFP2 respirator (d in Figure 3), and with the optimized version of the VV4MC (e in Figure 3).

Figure 3. Experimental setup to assess the impact of PPEs on speech levels. Source: [20]

C. Noise reduction strategies

Acoustic optimization strategies for the novel PPE encompass several approaches, as shown in Figure 4.

Figure 4. a) Flowchart of the design optimization process and b) Proposed solutions sketches. Source: [20]

Initially, replacing the T-shaped splitter (A in Figure 4b) with a Y-shaped one (B in Figure 4b) minimizes air disturbance and eliminates sharp corners, reducing airflow disruptions. Additionally, experiments explore the impact of tube diameter and air flow rate on noise levels. As already mentioned, the complete study including all air flow rates tested is available in reference [20]. Further noise reduction components include a muffler (E in Figure 4b) with porous material placed upstream of the splitter to absorb and reflect sound waves [25], [26]. Lateral physical barriers (sideguards) (F in Figure 4b) enhance protection efficiency and further reduce noise from the jet slots [19]. Tube thickness variations (8 mm inner diameter, 1 and 2 mm thickness) are also tested, as well as the application of a layer of tube insulation.

Within the plenum, strategies involve covering the floor with a cushion pad (3 mm height) to absorb sound energy and installing a cone (G in Figure 4b) to diffuse air and minimize pressure fluctuations. Computational Fluid Dynamics simulations ensured that both these changes inside the plenum geometry would not compromise efficiency [20].

The final stage explores alternative splitter designs, including the Ys (Y streamlined) splitter (C in Figure 4b) and the Reactive Muffler Splitter (RMS) (D in Figure 4b). The RMS, similar to an automotive muffler, reflects sound waves to reduce noise within the inlet and outlet tubes [27].

Both the Ys and RMS are non-commercial components, custom-designed and 3D printed in-house for this specific application.

III. Data presentation and discussion

A. PPE impact on ambient noise

The effect of wearing the novel PPE on ambient A-weighted noise equivalent level, measured at the manikin's ears, was evaluated by analyzing Lpeq,T values and one-third octave spectra. Figure 5 shows the results of the ambient one-third octave bands frequency spectra with and without the PPE. The results indicate that the PPE impact on A-weighted noise equivalent level was minimal, as Lpeq,T remained consistent at ≈ 34.8 dBA. However, slight effects were noted in the spectra at the mid-frequency range (Figure 5).

Figure 5. Ambient A-weighted noise equivalent level. Adapted from [20]

B. Acoustic optimizations

As depicted in Figure 4, the design optimization process was iterative, with adopted solutions leading to incremental improvements throughout the study. Table I provides a description of each optimization iteration, serving as a guide for analysing the results presented in Figure 6, Figure 7, and Figure 8. The results in these figures are depicted with a colour gradient ranging from red, indicating the worst result, to bright green, indicating the best.

As previously noted, the analysis only considers an airflow rate of 25 l/min. However, a comprehensive analysis for other airflow rates, as well as a detailed frequency analysis of each tested solution, can be found in reference [20].

Furthermore, detailed analysis of tube thickness variation, plenum modifications, and tube insulation are also available in reference [20].

Iterations 1, 3, 4, and 8 employ the same type of splitter (Y) but feature varying tube internal diameters, which increase accordingly. Notably, increasing the tube diameter while maintaining the same airflow rate, i.e. reducing air flow velocity, leads to an improvement in acoustic performance. Simply adjusting the tube internal diameter resulted in a reduction of the noise level from 78.4 to 59.1 dBA and an increase in the Speech Intelligibility Index (SII) from 0.17 to 0.53 (Figure 6 and Figure 7). While increasing the tube diameter improves the acoustic performance, excessive increases often coincide with greater tube thickness, potentially compromising flexibility and adding weight, therefore, the tube internal diameter was not further increased.

Regarding noise reduction components, the ones that are analysed in this work are the muffler (E in Figure 4b) and the sideguards (F in Figure 4b). Comparing optimization iterations 4, 5, and 6, for a tube internal diameter of 8 mm, highlights the acoustic performance improvements brought by these components. Introducing these solutions separately allowed to assess the noise reduction capability of each one. Notably, the muffler demonstrated a higher impact on noise reduction compared to the sideguards, reducing noise levels from 62.0 dBA to 54.9 dBA, while the sideguards reduced noise levels to 57.8 dBA (Figure 6). Although the muffler outperformed the sideguards in noise reduction, both components showed equivalent improvements in SII, increasing this value from 0.44 to 0.64 (Figure 7). The variations in improvement can be attributed to the different spectral attenuation achieved by each component. This is further detailed in reference [20].

Combining both components brings further improvements of both noise levels and speech intelligibility. Comparing optimization iterations 4 and 7 shows that this combined solution results in noise levels reduction from 62.0 dBA down to 51.4 dBA and an improvement of the SII from 0.44 up to 0.80. Now comparing optimization iterations 7 and 11, where the only difference is in the tube internal diameter, which increased from 8 to 10 mm, the improvements are more pronounced, with noise levels decreasing to 47.8 dBA and SII increasing to 0.92 (Figure 6 and Figure 7). This marks a significant achievement in the optimization process, reaching a point where the VV4MC guarantees good speech intelligibility, as defined by the guidelines in ANSI/ASA S3.5-1997 (R2020) [24], where values above 0.75 characterize a good communication system.

In the final stage of this optimization process, there was a concern regarding the contribution of the splitter (F in Figure 1) to the noise. This concern was caused by an earlier modification from a T-shaped splitter to a Y-shaped one (optimization iteration 2 and 3), which resulted in a reduction of noise levels from 69.1 to 66.9 dBA and an increase in the SII from 0.17 to 0.25 (Figure 6 and Figure 7).

 Therefore, two new components, the Ys and the RMS, were designed and 3D-printed to further improve the acoustic performance (C and D in Figure 4b, respectively).

As the improvements observed from iteration 2 to 3 were attributed to reduced air flow disturbances by eliminating sharp corners in the air flow path, the Ys was designed in a way that could further minimize these disturbances and improve the acoustic performance.

However, this solution did not yield the expected results. Comparing the results of optimization iterations 8 and 9, the introduction of the Ys splitter led to an increase in noise levels, from 59.1 to 62.2 dBA, and a decrease in the SII, from 0.53 down to 0.44 (Figure 6 and Figure 7). These results suggested that this design actually facilitated noise propagation from upstream due to reduced disturbance, when compared with the commercial Y-splitter (B in Figure 4b).

To address this issue, and motivated by the positive impact of the muffler, the RMS was designed. Its design aimed to reflect sound waves back upstream and within itself, reducing upstream noise propagation. The impact of this solution can be seen by comparing iterations 8 and 10. This comparison reveals the impact of this solution, with the RMS alone reducing noise levels from 59.1 to 54.9 dBA and increasing the SII from 0.53 to 0.71. When integrated with the muffler and sideguards in iteration 12, the results showed a further reduction of noise levels down to 44.3 dBA and an increase of the SII to 0.99 (Figure 6 and Figure 7), close to its maximum value (1.0).

Iteration 12 represents the final prototype of the VV4MC, incorporating the RMS, the muffler, and the sideguards, with a tube internal diameter of 10 mm. Comparing the frequency spectra of the first and the final iterations of this optimization process (Figure 8), reveals a striking difference which shows how the entire frequency spectrum was attenuated, resulting in an overall noise levels reduction of 34.1 dBA, from 78.4 dBA down to 44.3 dBA, and an increase of the SII from 0.17 to 0.99. Moreover, the noise levels generated by the VV4MC are considered safe and well below the recommended occupational noise limits set by the World Health Organization (WHO) [28], the National Institute for Occupational Safety and Health (NIOSH) [29], and European directives [30].

Table I. Optimization iteration description with tube internal diameter (ø), splitter designs and other noise reduction components.

Figure 6. Equivalent Continuous Sound Pressure Level Leq evolution throughout the study (for 25 l/min).

Figure 7. Speech Intelligibility Index (SII) evolution throughout the study (for 25 l/min).

Figure 8. One-Third Octave Frequency Spectra comparison between the first optimization iteration (1) and the last (12).

C. Speech Attenuation of different PPE

PPEs can impact have a negative impact in communication, especially in critical work settings where clear communication is essential to carry out procedures and maintain high performance [3].

This study addresses this concern by assessing the impact of wearing the VV4MC in speech transmission. This is done by comparing how different PPE attenuate the white noise attenuation emitted by a speaker. The experimental setup for this purpose can be seen in Figure 3. Evaluation of white noise attenuation with different PPE revealed reductions ranging from 2.2 dBA for the surgical mask, close to those of Goldin et al. [31], 3.7 dBA for the FFP2 respirator, and 4.7 dBA for the VV4MC (Figure 9). These results demonstrate that the VV4MC has a higher impact on speech transmission and that this issue still needs to be properly addressed.

Figure 9. White noise attenuation of the different PPE. Adapted from [20]

IV. Conclusions

This paper presents the assessment and optimization of the acoustic performance of a novel visor concept with aerodynamic sealing. Methods include measuring A-weighted Noise Equivalent Level, conducting frequency analysis, evaluating Speech Intelligibility Index (SII), and assessing speech attenuation of the final PPE prototype. The primary noise source is the air supply system, mitigated through various strategies to prevent noise propagation. Implementation of strategies such as increasing tube diameter, adding a muffler, new splitter designs, and a lateral physical barrier resulted in a 34.1 dBA reduction in noise level for an air flow rate of 25 l/min. The final PPE configuration achieved an A-weighted Noise Equivalent Level at 44.3 dBA, with excellent speech intelligibility (0.99). In speech attenuation tests, the final prototype showed lower results compared to surgical masks and FFP2 respirators. Future work should focus on usability tests in real working conditions, incorporating survey testing for user feedback to refine PPE design and functionality.

Acknowledgement

This work was funded by FEDER - European Regional Development Funds through the operational program Centro 2020 of Portugal 2020 according to Support System for Scientific and Technological Research (SAICT) in the framework of the project “VV4MC – A new type of ventilated visor for medical care” (CENTRO-01-0145-FEDER-181248) and was sponsored by national funds through FCT – Fundação para a Ciência e a Tecnologia, under project LA/P/0079/2020, DOI: 10.54499/LA/P/0079/2020 (https://doi.org/10.54499/LA/P/0079/2020).

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