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dc.contributor.advisor Sabharwal, Ashutosh
dc.creatorKumar, Mayank
dc.date.accessioned 2016-02-05T22:29:15Z
dc.date.available 2016-02-05T22:29:15Z
dc.date.created 2014-12
dc.date.issued 2014-09-04
dc.date.submitted December 2014
dc.identifier.citation Kumar, Mayank. "Robust acquisition of Photoplethysmograms using a Camera." (2014) Master’s Thesis, Rice University. https://hdl.handle.net/1911/88445.
dc.identifier.urihttps://hdl.handle.net/1911/88445
dc.description.abstract Non-contact monitoring of vital signs, such as pulse rate, using a camera is gaining popularity because of its potential for ubiquitous in-situ low-cost health tracking. Camera-based vital sign monitoring measures small skin color changes due to blood flow, and can potentially be extracted from the recorded video. However, current methods of camera-based vital sign monitoring have poor performance for people having darker skin tones and/or in the presence of relative motion between the camera and the subject. In this thesis, we propose distancePPG, a new algorithm which addresses aforementioned challenges and can reliably estimate the whole photoplethysomogram (PPG) for most skin tones in presence of subject motion. We first propose a new method to combine the PPG signal from different regions of the skin, which improves the SNR of the estimated PPG signal by 4.7 dB on an average compared to past methods for people having different skin tones. Second, by tracking different regions of the face independently during motion, our algorithm provides a gain of 5.3 dB in SNR compared to past methods of motion tracking. The combined effect of our proposed innovations is a significant improvement in SNR of estimated PPG signal, as a result of which camera-based vital sign monitoring can potentially be used in many more scenarios.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectcamera
vital signs
non-contact
neonatal ICU

dc.title Robust acquisition of Photoplethysmograms using a Camera
dc.contributor.committeeMember Veeraraghavan, Ashok
dc.contributor.committeeMember Aazhang, Behnaam
dc.date.updated 2016-02-05T22:29:15Z
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Electrical and Computer Engineering
thesis.degree.discipline Engineering
thesis.degree.grantor Rice University
thesis.degree.level Masters
thesis.degree.name Master of Science


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