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Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring
DC Field | Value | Language |
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dc.contributor.author | 김정민 | - |
dc.contributor.author | 유선국 | - |
dc.date.accessioned | 2023-08-23T00:18:27Z | - |
dc.date.available | 2023-08-23T00:18:27Z | - |
dc.date.issued | 2023-07 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/196210 | - |
dc.description.abstract | (Objective)Breathing can be measured in a non-contact method using a thermal camera. The objective of this study investigates non-contact breathing measurements using thermal cameras, which have previously been limited to measuring the nostril only from the front where it is clearly visible. The previous method is challenging to use for other angles and frontal views, where the nostril is not well-represented. In this paper, we defined a new region called the breathing-associated-facial-region (BAFR) that reflects the physiological characteristics of breathing, and extract breathing signals from views of 45 and 90 degrees, including the frontal view where the nostril is not clearly visible. (Methods) Experiments were conducted on fifteen healthy subjects in different views, including frontal with and without nostril, 45-degree, and 90-degree views. A thermal camera (A655sc model, FLIR systems) was used for non-contact measurement, and biopac (MP150, Biopac-systems-Inc) was used as a chest breathing reference. (Results) The results showed that the proposed algorithm could extract stable breathing signals at various angles and views, achieving an average breathing cycle accuracy of 90.9% when applied compared to 65.6% without proposed algorithm. The average correlation value increases from 0.587 to 0.885. (Conclusion)The proposed algorithm can be monitored in a variety of environments and extract the BAFR at diverse angles and views. (Clinical Impact)The proposed algorithm shows the feasibility of non-contact breathing reliable monitoring that versatile and accurate than previous methods. The proposed algorithm could be used to monitor breathing in various clinical environments, including isolated wards, operation rooms, and intensive care units with high infection risks. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.relation.isPartOf | IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Anesthesiology and Pain Medicine (마취통증의학교실) | - |
dc.contributor.googleauthor | Junhwan Kwon | - |
dc.contributor.googleauthor | Oyun Kwon | - |
dc.contributor.googleauthor | Kyeong Taek Oh | - |
dc.contributor.googleauthor | Jeongmin Kim | - |
dc.contributor.googleauthor | Sun K. Yoo | - |
dc.identifier.doi | 10.1109/jtehm.2023.3295775 | - |
dc.contributor.localId | A00884 | - |
dc.contributor.localId | A02471 | - |
dc.relation.journalcode | J04480 | - |
dc.identifier.eissn | 2168-2372 | - |
dc.subject.keyword | Cameras | - |
dc.subject.keyword | Temperature measurement | - |
dc.subject.keyword | Nose | - |
dc.subject.keyword | Biomedical monitoring | - |
dc.subject.keyword | Faces | - |
dc.subject.keyword | Monitoring | - |
dc.subject.keyword | Temperature distribution | - |
dc.contributor.alternativeName | Kim, Jeongmin | - |
dc.contributor.affiliatedAuthor | 김정민 | - |
dc.contributor.affiliatedAuthor | 유선국 | - |
dc.citation.volume | 11 | - |
dc.citation.startPage | 505 | - |
dc.citation.endPage | 514 | - |
dc.identifier.bibliographicCitation | IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE, Vol.11 : 505-514, 2023-07 | - |
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