Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring
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 metho...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Journal of Translational Engineering in Health and Medicine |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10184419/ |
| _version_ | 1797663078912884736 |
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| author | Junhwan Kwon Oyun Kwon Kyeong Taek Oh Jeongmin Kim Sun K. Yoo |
| author_facet | Junhwan Kwon Oyun Kwon Kyeong Taek Oh Jeongmin Kim Sun K. Yoo |
| author_sort | Junhwan Kwon |
| collection | DOAJ |
| description | 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. 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. 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. The proposed algorithm can be monitored in a variety of environments and extract the BAFR at diverse angles and views. |
| first_indexed | 2024-03-11T19:09:20Z |
| format | Article |
| id | doaj.art-980861cf860d4e378e5113d59e485b98 |
| institution | Directory Open Access Journal |
| issn | 2168-2372 |
| language | English |
| last_indexed | 2024-03-11T19:09:20Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Translational Engineering in Health and Medicine |
| spelling | doaj.art-980861cf860d4e378e5113d59e485b982023-10-09T23:00:19ZengIEEEIEEE Journal of Translational Engineering in Health and Medicine2168-23722023-01-011150551410.1109/JTEHM.2023.329577510184419Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing MonitoringJunhwan Kwon0https://orcid.org/0000-0002-6464-3895Oyun Kwon1https://orcid.org/0000-0002-9092-2812Kyeong Taek Oh2https://orcid.org/0000-0002-6857-0945Jeongmin Kim3https://orcid.org/0000-0002-0468-8012Sun K. Yoo4https://orcid.org/0000-0002-6032-4686Department of Medical Engineering, Yonsei University College of Medicine, Seoul, South KoreaDepartment of Medical Engineering, Yonsei University College of Medicine, Seoul, South KoreaDepartment of Medical Engineering, Yonsei University College of Medicine, Seoul, South KoreaDepartment of Anesthesiology and Pain Medicine, Severance Hospital, College of Medicine, Seoul, South KoreaDepartment of Medical Engineering, Yonsei University College of Medicine, Seoul, South KoreaBreathing 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. 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. 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. The proposed algorithm can be monitored in a variety of environments and extract the BAFR at diverse angles and views.https://ieeexplore.ieee.org/document/10184419/Breathingthermal cameraphysiological featuresnoncontactMarkov random field (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 environmentsincluding isolated wards |
| spellingShingle | Junhwan Kwon Oyun Kwon Kyeong Taek Oh Jeongmin Kim Sun K. Yoo Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring IEEE Journal of Translational Engineering in Health and Medicine Breathing thermal camera physiological features noncontact Markov random field (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 |
| title | Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring |
| title_full | Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring |
| title_fullStr | Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring |
| title_full_unstemmed | Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring |
| title_short | Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring |
| title_sort | breathing associated facial region segmentation for thermal camera based indirect breathing monitoring |
| topic | Breathing thermal camera physiological features noncontact Markov random field (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 |
| url | https://ieeexplore.ieee.org/document/10184419/ |
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