Koichi Ashida, Yuta Hino, Chawan Koopipat, Keiko Ogawa-Ochiai, Norimichi Tsumura
{"title":"Monitoring respiratory state from near-infrared face video images","authors":"Koichi Ashida, Yuta Hino, Chawan Koopipat, Keiko Ogawa-Ochiai, Norimichi Tsumura","doi":"10.1007/s10015-023-00926-3","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, we propose an algorithm for estimating respiratory state using near-infrared facial video images. Estimation of respiratory state is an important indicator for early detection of respiratory diseases. In particular, there is a demand for monitoring respiratory state during the night. One method of monitoring respiratory state is to use contact-type sensors. However, this method requires the installation of many sensors and a visit to a hospital, which place a burden on patients. Therefore, we propose to acquire respiratory-induced features from near-infrared face video images and investigate their similarity to measurements obtained with a respirometer for non-contact monitoring of respiratory state in the dark. Respiratory-induced features were obtained from pulse wave signals extracted from the face video images. The results showed correlations in several respiratory states. This study opens some perspectives in non-contact monitoring of respiratory states.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"29 1","pages":"197 - 203"},"PeriodicalIF":0.8000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10015-023-00926-3.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Life and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s10015-023-00926-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we propose an algorithm for estimating respiratory state using near-infrared facial video images. Estimation of respiratory state is an important indicator for early detection of respiratory diseases. In particular, there is a demand for monitoring respiratory state during the night. One method of monitoring respiratory state is to use contact-type sensors. However, this method requires the installation of many sensors and a visit to a hospital, which place a burden on patients. Therefore, we propose to acquire respiratory-induced features from near-infrared face video images and investigate their similarity to measurements obtained with a respirometer for non-contact monitoring of respiratory state in the dark. Respiratory-induced features were obtained from pulse wave signals extracted from the face video images. The results showed correlations in several respiratory states. This study opens some perspectives in non-contact monitoring of respiratory states.