Linsey Griffin, Minji Yu, Susan Sokolowski, Susan Arnold, William K. Durfee
{"title":"呼吸器设计、研究和保护方面的创新:职业安全与健康预测模型。","authors":"Linsey Griffin, Minji Yu, Susan Sokolowski, Susan Arnold, William K. Durfee","doi":"10.1177/21695067231192265","DOIUrl":null,"url":null,"abstract":"Improving the fit of a half-mask respirator can be achieved by developing a design, fit, and sizing strategy to fit the faces of the general population or a specific group such as race, age group, or occupation. The purpose of this study was to define respirator fit based on the body product relationship and to develop a new set of facial landmarks and measurements for half-mask respirator design. 3D scan data and quantitative fit factor scores from 47 healthcare workers and 9 researchers in healthcare-related fields were utilized to investigate the relationship of new anthropometry measurements to respirator fit. A mask fit association model was validated through logistic regression. The respirator fit prediction model incorporating highly correlated face measurements opens the possibility of developing a system for judging respirator fit success and failure based on face dimensions; it can be integrated with automated measuring technologies and machine learning.","PeriodicalId":20673,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","volume":"1 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Innovation in Respirator Design, Research, & Protection: A model of predictive fit for occupational safety and health.\",\"authors\":\"Linsey Griffin, Minji Yu, Susan Sokolowski, Susan Arnold, William K. Durfee\",\"doi\":\"10.1177/21695067231192265\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Improving the fit of a half-mask respirator can be achieved by developing a design, fit, and sizing strategy to fit the faces of the general population or a specific group such as race, age group, or occupation. The purpose of this study was to define respirator fit based on the body product relationship and to develop a new set of facial landmarks and measurements for half-mask respirator design. 3D scan data and quantitative fit factor scores from 47 healthcare workers and 9 researchers in healthcare-related fields were utilized to investigate the relationship of new anthropometry measurements to respirator fit. A mask fit association model was validated through logistic regression. The respirator fit prediction model incorporating highly correlated face measurements opens the possibility of developing a system for judging respirator fit success and failure based on face dimensions; it can be integrated with automated measuring technologies and machine learning.\",\"PeriodicalId\":20673,\"journal\":{\"name\":\"Proceedings of the Human Factors and Ergonomics Society Annual Meeting\",\"volume\":\"1 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Human Factors and Ergonomics Society Annual Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/21695067231192265\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/21695067231192265","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Innovation in Respirator Design, Research, & Protection: A model of predictive fit for occupational safety and health.
Improving the fit of a half-mask respirator can be achieved by developing a design, fit, and sizing strategy to fit the faces of the general population or a specific group such as race, age group, or occupation. The purpose of this study was to define respirator fit based on the body product relationship and to develop a new set of facial landmarks and measurements for half-mask respirator design. 3D scan data and quantitative fit factor scores from 47 healthcare workers and 9 researchers in healthcare-related fields were utilized to investigate the relationship of new anthropometry measurements to respirator fit. A mask fit association model was validated through logistic regression. The respirator fit prediction model incorporating highly correlated face measurements opens the possibility of developing a system for judging respirator fit success and failure based on face dimensions; it can be integrated with automated measuring technologies and machine learning.