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Remote optical cardiopulmonary signal extraction with noise artifact removal, multiple subject detection & long-distance

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dc.contributor.authorAl Naji, A.
dc.contributor.authorChahl, J.
dc.date.issued2018
dc.description.abstractOAPA Most existing imaging technologies are prone to noise artifact resulting from movement of subjects, movement of the camera, facial expressions, talking, skin tone and lighting variations. In addition, these technologies have been limited to detecting physiological signs from a single subject at a time. Still, another challenge facing these technologies is that they have only been demonstrated over a limited range to a subject. This paper proposes an efficient remote imaging system with a new, low-complexity method for noise artifact removal to extract the cardiopulmonary signal from a number of subjects (up to six people) and at long-distances (up to 60 m). The experimental results of the proposed system showed a strong agreement, high correlation and low noise level with the reference measurements and outperformed the conventional measurement methods such as independent component analysis (ICA) and principle component analysis (PCA) in both the stationary and non-stationary scenarios.
dc.identifier.citationIEEE Access, 2018; 6:11573-11595
dc.identifier.doi10.1109/ACCESS.2018.2811392
dc.identifier.issn2169-3536
dc.identifier.issn2169-3536
dc.identifier.urihttps://hdl.handle.net/11541.2/131203
dc.language.isoen
dc.publisherIEEE
dc.rightsCopyright 2018 IEEE
dc.source.urihttp://dx.doi.org/10.1109/ACCESS.2018.2811392
dc.subjectimaging photoplethysmography (iPPG)
dc.subjectcardiopulmonary signal
dc.subjectvideo magnification
dc.subjectsignal decomposition technique
dc.subjectblind source separation (BSS)
dc.subjectcanonical correlation analysis (CCA)
dc.titleRemote optical cardiopulmonary signal extraction with noise artifact removal, multiple subject detection & long-distance
dc.typeJournal article
pubs.publication-statusPublished
ror.fileinfo12153806540001831 13153806530001831 08306266.pdf
ror.mmsid9916178605301831

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