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Breathing resistance is the main factor that influences the wearing comfort of respirators. This paper aims to demonstrate the feasibility of using the gene expression programming (GEP) for the purpose of predicting subjective perceptions of breathing resistances of wearing respirators via surface electromyography (sEMG) and respiratory signals (RSP) sensors.

The authors developed a physiological signal monitoring system with a specific garment. The inputs included seven physical measures extracted from (RSP) and (sEMG) signals. The output was the subjective index of breathing resistances of wearing respirators derived from the category partitioning-100 scale with proven levels of reliability and validity. The prediction model was developed and validated using data collected from 30 subjects and 24 test combinations (12 respirator conditions × 2 motion conditions). The subjects evaluated 24 conditions of breathing resistances in repeated measures fashion.

The results show that the GEP model can provide good prediction performance (R² = 0.71, RMSE = 0.11). This study demonstrates that subjective perceptions of breathing resistance of wearing respirators on the human body can be predicted using the GEP via sEMG and RSP in real-time, at little cost, non-invasively and automatically.

This is the first paper suggesting that subjective perceptions of subjective breathing resistances can be predicted from sEMG and RSP sensors using a GEP model, which will remain helpful to the scientific community to start further human-centered research work and product development using wearable biosensors and evolutionary algorithms.

Investigating the subjective breathing resistance of wearing respirators requires a valid and reliable technique to measure breathing resistance. The purpose of this study is to test the validity and reliability of several rating scales and select the best for investigation of breathing resistance.

The authors designed three scales, that is, BRX scale, CP-100 scale and RVAS scale, and 30 subjects were separated into three groups, each group with a different scale. They sat for 5 min and walked for 5 min while wearing three models of respirators. After each trial, subjects were asked to complete subjective ratings of breathing resistance. Reliability was examined by the coefficient of Cronbach’s α, and validity was examined through content validity, discriminant validity and criterion validity. Generally, subjects were capable of reporting their sensation of breathing resistance by using the rating scale technique. However, the accuracy of rating strongly depended upon the properties of the scale.

The CP-100 scale was found to be highly reliable and most valid for rating subjective breath resistance. The validated CP-100 scale is very sensitive and accurate.

This is the first paper to select the best subjective scale for investigation of breathing resistance of respirators. The CP-100 scale will find wide applications in subjective breathing resistance evaluation for the use of respirators in industrial benchmarking activities. It will introduce the human factor engineering into the respirator manufacturing to improve the comfort of respirators.

The purpose of this paper is to provide an overview of the human factors/ergonomics (HFE) studies for respirator.

This review paper describes and discusses the various factors and methodologies of HFE, for the purpose of better considering human factors, used in respirator studies and further human-centered product development.

Many attempts have been made to study human factors for respirators mainly including fit, human performance, comfort, and mood. Physical, psychological, and physiological indices of people are extremely valuable to HFE studies for respirator. Objective and subjective measures were methodologies widely used. Quantitative and qualitative approaches were adopted to illustrate the human performance and well-being influenced by respirators. A summary table presented with major methods used for indices of respirators in the field of HFE. According to the current researches, this review indicated three particular challenges facing HFE studies of respirators now.

With the ever increasing role of protection from air pollution in society, respirator has become an increasingly important part of our daily lives. HFE intervene in optimizing the relationships between respirators and the human using them. Plenty of efforts have been dedicated for the development of protection capability, but HFE studies for respirators are lacking. In recent years, there has been a tremendous interest in introducing HFE research methods that can evaluate respirators from the perspective of human and translate them into constraints for designing human-centered respirators.

This is a first paper in the field of HFE studies for respirator, which will remain helpful to the scientific community to start further human-centered research work and product development.

THE partial pressure of the oxygen content in the atmosphere decreases directly with the atmospheric pressure, i.e., with the altitude, the proportion of oxygen in the atmosphere (about 20·9 per cent) remaining practically constant in the substratosphere.

The aim of this study was to develop a smart wearable mask designed for the prevention of respiratory infectious diseases by understanding consumer's preferences in designs and functions of the smart wearable masks.

To develop a smart mask design, a survey was conducted on Chinese consumers in their 20–40s and analyzed their mask wearing behaviors, preferences and caring aspects of masks. The collected data were analyzed to identify the demographic characteristics of the subjects surveyed by using the SPSS program, and technical statistical analysis was conducted. To identify differences in demographic characteristics, an independent samples t-test, one-way analysis of variance and Scheffe's ad hoc test were conducted.

Based on the research results, design guidelines for wearable masks were defined, and four wearable mask designs were developed and presented in 2D and 3D images based on the design guidelines. There were significant differences among people with different backgrounds.

It is significant that this research presents smart wearable mask design guidelines and designs through supplementation and improvement of existing mask. It is expected that this research provides basic empirical data for mask designs through the planning of smart wearable mask designs and surveys assessing consumer perceptions, attitudes and satisfaction.

A facemask is used to cover the nose and mouth to protect a wearer's health in daily life. The authors’ long-term goal aimed to ensure more people with different physical characteristics and different attitudes can wear a high performance and comfortable facemask. In the present paper, wearers were surveyed by a questionnaire. Additionally, a prototype improvement pattern with a fit performance was investigated.

The survey of facemask wearers was conducted with local students and international students in Japan. A basic pattern with high fit performance was analyzed using a combination of triangles based on the measured three-dimensional coordinates of the head shape of a Japanese mannequin.

The aggregated survey data indicated that 85.0% of the Japanese female students, 77.2% of international female students, 70.8% of Japanese male students and 54.3% of international male students were facemask wearers. Wearers had problems related to their masks' thermal, hygroscopic and airflow properties. Japanese nonusers did not wear them due to dislike related to the problems above. International nonusers had no experience of wearing them. It was concerned that these discomfort factors influence fit performance and reduction of wearing effects. Therefore, the authors analyzed a sheet pattern with a high fit performance for a Japanese head mannequin.

These results will contribute in improving hygienic facemasks for people at the global level. The survey results and pattern analysis provide of necessary conditions of development of the mask with comfortable and high fit performance.

The COVID-19 pandemic has popularized wearing face masks for personal protection. However, the protection afforded by a mask is decreased if an individual accidently touches the outer surface of the mask and then touches other parts of their face. To overcome this problem, antimicrobial masks have become commercially available. However, many are disposable and/or made from synthetic antimicrobial agents which have a negative impact on the environment. The purpose of this study was to create material for stitching antimicrobial masks that are reusable and natural.

The authors developed natural antimicrobial finishes from Azadirachata indica, Butea monosperma and Litchi chinensis leaves. The authors used biodegradable polyurethane binder and pad-dry-cure method to apply them on 100% cotton fabric. The authors used Fourier-transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM) to confirm the application and ASTM E2149 to assess the efficacy and wash-resistance of the finish.

Fabric treated with leaves of A. indica, B. monosperma and L. chinensis showed 80%, 100 and 100% antimicrobial activity, respectively. All fabrics were washed 25 times in home laundry cycles and maintained 100% of their antimicrobial effect.

These findings highlight that B. monosperma and L. chinensis finishes on cotton fabric can be a used as a material for stitching antimicrobial, natural and reusable masks that provide more protection than traditional masks but do not pose the environmental concerns of disposable masks or synthetic finishes. This study can be furthered by performing more laundry cycles to determine if the finishes remain 100% effective beyond 25 cycles.