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Tytuł artykułu

Reliability of Pulse Measurements in Videoplethysmography

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Reliable, remote pulse rate measurement is potentially very important for medical diagnostics and screening. In this paper the Videoplethysmography was analyzed especially to verify the possible use of signals obtained for the YUV color model in order to estimate the pulse rate, to examine what is the best pulse estimation method for short video sequences and finally, to analyze how potential PPG-signals can be distinguished from other (e.g. background) signals. The presented methods were verified using data collected from 60 volunteers.
Rocznik
Strony
359--371
Opis fizyczny
Bibliogr. 28 poz., rys., tab., wykr., wzory
Twórcy
autor
  • Gdańsk University of Technology, Faculty of Electronics, Telecommunications and Informatics, Narutowicza 11/12, 80-233 Gdańsk, Poland
Bibliografia
  • [1] Humphreys, K., Markham, Ch., Ward, T.E. (2005). A CMOS camera-based system for clinical photoplethysmographic applications. Proc. SPIE, 5823, 88-95.
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  • [3] Poh, M.Z., McDuff, D.J., Picard, R.W. (2010). Non- contact, automated cardiac pulse measurements using video imaging and blind source separation. Optics Express, 18,10762-10774.
  • [4] Christinaki, E., Giannakakis, G., Chiarugi, F., Pediaditis, M., Iatraki, G., Manousos, D., Marias, K., Tsiknakis, M. (2014). Comparison of blind source separation algorithms for optical heart rate monitoring. Proc. of Mobihealth Conference, 339-342.
  • [5] Mannapperuma, K., Holton, B.D., Lesniewski, P.J., Thomas, J.C. (2015). Performance limits of ICA-based heart rate identification techniques in imaging photoplethysmography. Physiol Meas., 36(1), 67-83.
  • [6] Lewandowska, M., Ruminski, J., Kocejko, T., Nowak, J. (2011), Measuring pulse rate with a webcam − A non-contact method for evaluating cardiac activity. Proc. of FedCSIS Conference, IEEE Xplore, 405-410.
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  • [10] Ruminski, J., Smiatacz, M., Bujnowski, A., Andrushevich, A., Biallas, M., Kistler, R. (2015). Interactions with recognized patients using smart glasses. Proc. of HSI 2015 Conference, IEEE Xplore, 187-194.
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  • [13] Fuller, W.A. (1996). Introduction to Statistical Time Series. UK: John Wiley & Sons, Inc.
  • [14] Gävert, H., Hurri, J., Särelä, J., Hyvärinen, A. (2005). FastICA, http://research.ics.aalto.fi/ica/fastica/about.shtml
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  • [19] Augustyniak, P. (2013). Coherence-based measure of instantaneous ECG noise. Computing in Cardiology Conference (CinC), 787-790.
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  • [23] Iyriboz, Y., Powers, S., Morrow, J., Ayers, D., Landry G. (1991). Accuracy of pulse oximeters in estimating heart rate at rest and during exercise. British Journal of Sports Medicine, 25(3), 162-164.
  • [24] Oh, S.H., Lee, Y.R., Kim, H.N. (2014). A Novel EEG Feature Extraction Method Using Hjorth Parameter. International Journal of Electronics and Electrical Engineering, 2(2), 106-110.
  • [25] Deshmane, A.V. (2009). False arrhythmia alarm suppression using ECG, ABP, and photoplethysmogram. MS Thesis, MIT, USA.
  • [26] Xin, L., Yongfeng, R., Chengqun, C., Wei, W.F. (2015). Accurate Frequency Estimation Based On Three- Parameter Sine-Fitting With Three FFT Samples. Metrol. Meas. Syst., 22(3), 403-416.
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Uwagi
EN
This work has been partially supported by NCBiR, FWF, SNSF, ANR and FNR within the framework of the ERA-NET CHIST-ERA II, European project eGLASSES – The interactive eyeglasses for mobile, perceptual computing and by Statutory Funds of Electronics, Telecommunications and Informatics Faculty, Gdansk University of Technology.
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
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Bibliografia
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