{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T18:00:16Z","timestamp":1769277616296,"version":"3.49.0"},"reference-count":18,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,13]],"date-time":"2020-03-13T00:00:00Z","timestamp":1584057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Continuous respiration monitoring is important for predicting a potential disease. Due to respiration measurements using contact sensors, it is difficult to achieve continuous measurement because the sensors are inconvenient to attach. In this study, a radar sensor was used for non-contact respiration measurements. The radar sensor had a high precision and could even be used in the dark. It could also be used continuously regardless of time and place. The radar sensor relied on the periodicity of respiration to detect the respiration rate. A respiration adaptive interval was set and the respiration rate was detected through harmonic quefrency selection. As a result, it was confirmed that there was no difference between the respiratory rate measured using a respiration belt and the respiratory rate detected using a radar sensor. Furthermore, case studies on changes in the radar position and about measurement for long periods confirmed that the radar sensor could detect respiration rate continuously regardless of the position and measurement duration.<\/jats:p>","DOI":"10.3390\/s20061607","type":"journal-article","created":{"date-parts":[[2020,3,18]],"date-time":"2020-03-18T08:20:44Z","timestamp":1584519644000},"page":"1607","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Radar-Based Detection of Respiration Rate with Adaptive Harmonic Quefrency Selection"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5177-9152","authenticated-orcid":false,"given":"JeeEun","family":"Lee","sequence":"first","affiliation":[{"name":"Graduate Program of Biomedical Engineering, Yonsei University, Seoul 03722, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6032-4686","authenticated-orcid":false,"given":"Sun K.","family":"Yoo","sequence":"additional","affiliation":[{"name":"Department of Medical Engineering, Yonsei University College of Medicine, Seoul 03722, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1002\/ppul.21416","article-title":"Respiration rate monitoring methods: A review","volume":"46","author":"Saatchi","year":"2011","journal-title":"Pediatric Pulmonol."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Miwa, H., and Sakai, K. (2009, January 4\u20137). Development of heart rate and respiration rate measurement system using body-sound. Proceedings of the 2009 9th International Conference on Information Technology and Applications in Biomedicine, Larnaka, Cyprus.","DOI":"10.1109\/ITAB.2009.5394438"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1007\/BF02348078","article-title":"Critical review of non-invasive respiratory monitoring in medical care","volume":"41","author":"Folke","year":"2003","journal-title":"Med Biol. Eng. Comput."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Nam, Y., Kim, Y., and Lee, J. (2016). Sleep monitoring based on a tri-axial accelerometer and a pressure sensor. 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