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JCR Impact Factor: 0.650
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

2018-May-31
Starting today, the minimum number a pages for a paper is 8, so all submitted papers should have 8, 10 or 12 pages. No exceptions will be accepted.

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

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  3/2019 - 5

Dynamic Heart Rate Measurements from Video Sequences using Canonical Component Analysis

LING, S.-S. See more information about LING, S.-S. on SCOPUS See more information about LING, S.-S. on IEEExplore See more information about LING, S.-S. on Web of Science, PARAMESRAN, R. See more information about  PARAMESRAN, R. on SCOPUS See more information about  PARAMESRAN, R. on SCOPUS See more information about PARAMESRAN, R. on Web of Science, YU, Y.-P. See more information about YU, Y.-P. on SCOPUS See more information about YU, Y.-P. on SCOPUS See more information about YU, Y.-P. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (558 KB) | Citation | Downloads: 92 | Views: 108

Author keywords
video signal processing, image processing, image analysis, independent component analysis, blind source separation

References keywords
rate(7), heart(7), biomedical(7), optics(6), video(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2019-08-31
Volume 19, Issue 3, Year 2019, On page(s): 41 - 48
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.03005
Web of Science Accession Number: 000486574100005
SCOPUS ID: 85072202782

Abstract
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Dynamic heart rate computation from facial images obtained from video sequences has random artifacts and noises. A novel method is formulated by assuming that two video durations will contain the heart rate signals that are strongly correlated to each other while the random artifacts and noises are not correlated to each other. Canonical Component Analysis (CCA) is used to recover the heart-rate signals by determining the maximum correlation of the two video durations. The identified heart signal is then passed to a bandpass filter (0.8 - 4Hz) followed by Fast Fourier Transform to obtain the heart rate. Two experiments related to increasing and decreasing heart rate variations are carried out to determine the effectiveness of the proposed method. Eight subjects participated in each experiment, where their facial images were captured for a minute while they were cycling. Their heart rates varied from 83 to 153 beats per minute (BPM). The results of the proposed method are compared to a method using independent component analysis (ICA). The root mean square errors (RMSE) for the proposed method and ICA based-method that used 5-second video duration for the first and second experiments are 3.70 BPM and 2.33 BPM and 14.36 BPM and 9.72 BPM, respectively.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [SCOPUS Times Cited 16]


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References Weight

Web of Science® Citations for all references: 4,437 TCR
SCOPUS® Citations for all references: 5,713 TCR

Web of Science® Average Citations per reference: 211 ACR
SCOPUS® Average Citations per reference: 272 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2019-10-13 09:48 in 120 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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