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dc.contributor.authorLin, Kuan-Yien_US
dc.contributor.authorChen, Duan-Yuen_US
dc.contributor.authorTsai, Wen-Jiinen_US
dc.date.accessioned2017-04-21T06:56:30Z-
dc.date.available2017-04-21T06:56:30Z-
dc.date.issued2016-05-01en_US
dc.identifier.issn1530-437Xen_US
dc.identifier.urihttp://dx.doi.org/10.1109/JSEN.2016.2526627en_US
dc.identifier.urihttp://hdl.handle.net/11536/133415-
dc.description.abstractContact measurements of the respiratory rate using conventional electrocardiogram equipment requires patients to wear chest straps that can cause skin irritation and discomfort. Therefore, a real-time robust non-contact technique is developed for the measurement of respiratory rate variation. The changes of a simple harmonic motion between inhalation and exhalation from the human\'s upper body can be observed from visual appearance. Therefore, in this paper, to characterize the motion, a salient region is automatically selected in the energy map resulted from Haar-like features through consecutive frames. Furthermore, a median optical flow signal is used to acquire the primary respiratory rate signal. The effective respiratory frequencies resulted from vertical motion variation are decomposed by median motion signal and then characterized by zero-crossing method before the frequencies were rectified by an estimation using the noise elimination methods. In the experiment, the performance is evaluated using an extensive data set obtained under distinct four respiratory types, regular respiration, respiration with body motion, respiration with distinct poses, and respiration with distinct capturing distances. Our approach develops a convenient non-contact method to evaluate the respiratory rate with the achievement of measurement under farther distance and also outperforms the current state-of-the-art approach in terms of high correlation coefficient. Therefore, the experiment results show its efficacy for real-world environment.en_US
dc.language.isoen_USen_US
dc.subjectComputer visionen_US
dc.subjectrespiration rate monitoringen_US
dc.titleImage-Based Motion-Tolerant Remote Respiratory Rate Evaluationen_US
dc.identifier.doi10.1109/JSEN.2016.2526627en_US
dc.identifier.journalIEEE SENSORS JOURNALen_US
dc.citation.volume16en_US
dc.citation.issue9en_US
dc.citation.spage3263en_US
dc.citation.epage3271en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000372609000054en_US
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