文献类型：期刊文献

英文题名：Computer vision-based objective evaluation of increase in breathing resistances of respirators on human subjects

作者：Yang, Zhongliang[1];Chen, Yumiao[2];Tang, Zhichuan[3];Jia, Miao[1]

机构：[1]Donghua Univ, Coll Mech Engn, Shanghai 201620, Peoples R China;[2]East China Univ Sci & Technol, Sch Art Design & Media, Shanghai 200237, Peoples R China;[3]Zhejiang Univ Technol, Ind Design Inst, Hangzhou 310023, Zhejiang, Peoples R China

年份：2018

卷号：159

起止页码：189

外文期刊名：OPTIK

收录：;EI(收录号：20180604773239);WOS:【SCI-EXPANDED(收录号:WOS:000430761300025)】；

基金：The authors would like to thank the participants of the experiment. This study was partly supported by the Fundamental Research Funds for the Central Universities (No. 2232018D3-27), the Zhejiang Provincial Key Laboratory of integration of healthy smart kitchen system (No. 2014E10014), and the Funds for IV Design Peak Subjects of Shanghai (No. DC17013).

语种：英文

外文关键词：Breathing resistances; Respirators; Computer vision; Nasal airflow; Swing angle; Human-in-the-loop

摘要：The purpose of this study was to evaluate objectively the impact of wearing respirators on breathing resistances of actual human subjects. We designed a monitor of the nasal airflow, which was composed of a full facepiece mask, a pipe for gathering nasal airflow, a monitoring line and a camera. A total of 5 normal adult volunteers were recruited in this study. Wearing the monitor, the subjects were required to sit for 1 min and walk for 1 min during wearing eight different models of respirators and without a respirator. Subsequently, the swing video of the monitoring line was collected by the camera during each breath of the subjects. The mean value of maximum swing angles of the monitoring line and the swing angle ratio were calculated through the image processing of the experimental videos. The experimental results show that the swing angle ratio during exhalation and inhalation are effective for representing exhalation resistances and inhalation resistances respectively. This is the first reported study that combines computer vision and the self-developed nasal airflow monitor to demonstrate quantitatively and objectively the exhalation resistances and inhalation resistances with the use of different respirators on actual human subjects. (C) 2018 Elsevier GmbH. All rights reserved.