Effect of Differing Facial Characteristics on Breathing Resistance Inside a Respirator Mask

Rebar, Joyce E.; Johnson, Arthur T.; Russek‐Cohen, Estelle; Caretti, David M.; Scott, William H.

doi:10.1080/15459620490447956

Cited by 7 publications

(3 citation statements)

References 11 publications

(7 reference statements)

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“…A resistance level of 3.5 cm H 2 O-sec/L is expected to result in a 30 % performance decrement. Because of this, one might expect performance with PAPR to be better than with air-purifying respirators, but this has yet to be definitively answered, and the extra weight of the blower and tubing may counteract at least some of the advantage of lower resistance [ 51 , 63 ].…”

Section: Respirationmentioning

confidence: 99%

Respirator masks protect health but impact performance: a review

2016

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Respiratory protective masks are used whenever it is too costly or impractical to remove airborne contamination from the atmosphere. Respirators are used in a wide range of occupations, form the military to medicine. Respirators have been found to interfere with many physiological and psychological aspects of task performance at levels from resting to maximum exertion. Many of these limitations have been investigated in order to determine quantitatively how much performance decrement can be expected from different levels of respirator properties. The entire system, including respirator and wearer interactions, must be considered when evaluating wearer performances. This information can help respirator designers to determine trade-offs or managers to plan to compensate for reduced productivity of wearers.

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Section: Respirationmentioning

confidence: 99%

Respirator masks protect health but impact performance: a review

2016

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“…Han and Choi [6] showed that Africans and Americans have shallower and smaller noses compared to Caucasians by a length difference of approximately two mm. Rebar et al [7] in 2004, noticed that Caucasians can be distinguished by their long narrow faces for both males and females. Ballihi et al [8] extracted radial curves and several specific geometrical circulars using the AdaBoost algorithm for gender classification on the FRGCv2 dataset.…”

Section: Introductionmentioning

confidence: 99%

3D Human Facial Traits’ Analysis for Ethnicity Recognition Using Deep Learning

Reda,

Abbas

2024

ISI

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Among different recent technologies proposed for human face classification and recognition, solutions based on analyzing the 3D geometric facial features emerged as a promising academic and practical direction. Researchers have examined both holistic and local approaches to analyzing the 3D face regions to study the impact of facial features in real-life applications such as medical and security implementations. However, a few works have investigated the relevant impact of the extracted geometric features from the descriptive local regions of the human face on identifying human ethnicity. This work proposes a classifier to categorize individuals into their distinctive ethnic groups and deeply analyzes the facial feature variations to highlight the most descriptive parts and features of the human face in race classification. The proposed ML-based classifier is preceded by extracting the 3D facial features from 3D meshes using the recent SIFT and Geodesic distance calculations. In addition, it implements and discusses the initial important preprocessing steps including, cropping the frontal parts, correcting the head pose, selecting the suitable initial key points, aligning the 3D meshes, and implementing the suitable template-based 3D registration. The proposed NN race classifiers are built and evaluated using Headspace, a well-known multi-ethnic dataset, and achieved high accuracy (90% globally, and 100% for the mouth area) especially while using the SIFT features.

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“…The CDC reported that a mismatch between the FFR and the facial structure of healthcare workers resulted in a 6-88% failure rate in respirator fit and a 33% reduction in protective efficacy against infectious agents [12]. The type, model, and size of FFR fit differently according to facial dimensions, which can be influenced by gender, ethnicity, and age groups [13][14][15]. Facial dimensions, such as facial length and width, are some of the significant variables in a FFR's proper fit [16].…”

Section: Introductionmentioning

confidence: 99%

The effect of N95 designs on respirator fit and its associations with gender and facial dimensions

Khairul Hasni,

Ismail,

Muhamad Robat

et al. 2023

PLoS ONE

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This study examined the association of various brands of NIOSH-certified N95 filtering face-piece respirators (FFR) fit with facial dimensions and gender. One hundred and thirty-five participants (77 females and 58 males) were recruited from the previous facial anthropometry study among Malaysians in 2020. Quantitative respirator fit testing of six FFR were performed using the TSI Portacount Pro+ 8038 which comprised of four exercises (bending over, talking, up-down head movement, and side to side head movement). An overall fit factor (FF) of ≥ 100 was considered a pass for each FFR. Analysis was done using T-test, Pearson’s correlations, and generalised linear regression. The passing rates for the six FFR were 36.3% (Cup B), 50.4% (Trifold A), 54.1% (Duckbill A), 57.0% (Cup A), 74.1% (Trifold B), and 83.7% (Duckbill B). Both Duckbill B and Trifold B had the highest passing rates for both genders. However, certain FFR models (Cup B, Trifold A, Trifold B, and Duckbill A) fit better for participants with large facial size who were mostly males, while others (Cup A and Duckbill B) specifically fit better for those with small facial size, who were mostly females. This study showed significant positive effect of nose protrusion, nasal root and subnasale-sellion and the negative effect of menton-sellion, bigonial breadth and nose breadth on fit factors of various FFR. The results of this study emphasized the importance of choosing and designing FFR based on local anthropometry data, with careful consideration on the dimensions that affect the respirator fit. Since N95 are commonly used in the healthcare settings to prevent airborne transmission, the practice of respirator fit testing and selecting N95 with high passing rates for healthcare workers need to be emphasized.

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Effect of Differing Facial Characteristics on Breathing Resistance Inside a Respirator Mask

Cited by 7 publications

References 11 publications

Respirator masks protect health but impact performance: a review

Respirator masks protect health but impact performance: a review

3D Human Facial Traits’ Analysis for Ethnicity Recognition Using Deep Learning

The effect of N95 designs on respirator fit and its associations with gender and facial dimensions

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