Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
권호 표지

Robust Extraction of Heartbeat Signals from Mobile Facial Videos

모바일 얼굴 비디오로부터 심박 신호의 강건한 추출

  • Lomaliza, Jean-Pierre (Department of Electronic Engineering, Pukyong National University) ;
  • Park, Hanhoon (Department of Electronic Engineering, Pukyong National University)
  • Received : 2019.01.16
  • Accepted : 2019.03.27
  • Published : 2019.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

This paper proposes an improved heartbeat signal extraction method for ballistocardiography(BCG)-based heart-rate measurement on mobile environment. First, from a mobile facial video, a handshake-free head motion signal is extracted by tracking facial features and background features at the same time. Then, a novel signal periodicity computation method is proposed to accurately separate out the heartbeat signal from the head motion signal. The proposed method could robustly extract heartbeat signals from mobile facial videos, and enabled more accurate heart rate measurement (measurement errors were reduced by 3-4 bpm) compared to the existing method.

본 논문은 모바일 환경에서의 BCG기반 심박 수 측정을 위한 향상된 심박 신호 추출 방법을 제안한다. 우선, 모바일 카메라를 이용하여 사용자의 얼굴을 촬영한 비디오로부터 얼굴 특징과 배경 특징을 동시에 추적함으로써 손 떨림에 의한 영향을 제거한 머리 움직임 신호를 추출한다. 그리고 머리 움직임 신호로부터 심박 신호를 정확하게 분리해내기 위해 신호의 주기성을 계산하는 새로운 방법을 제안한다. 제안 방법은 모바일 얼굴 비디오로부터 강건하게 심박 신호를 추출할 수 있으며, 기존 방법에 비해 보다 정확하게 심박 수 측정(측정 오차가 3-4 bpm 감소)을 할 수 있다.

Keywords

References

  1. A. Arcelus, M. Sardar, and A. Mihailidis, "Design of a capacitive ECG sensor for unobtrusive heart rate measurements," in IEEE Int. Instrumentation and Measurement Technology Conf., Minneapolis, MN, USA, May 2013.
  2. P. Leonard, N. Grubb, P. Addison, D. Clifton, and J. Watson, "An algorithm for the detection of individual breaths from the pulse oximeter waveform," J. Clin. Monit. Comput., vol. 18, pp. 309-312, 2004. https://doi.org/10.1007/s10877-005-2697-z
  3. D. W. Holdsworth, "Characterization of blood-flow waveforms in normal human subjects," Physiol. Meas., vol. 20, no. 3, pp. 219-240, 1999. https://doi.org/10.1088/0967-3334/20/3/301
  4. M. Garbey, N. Sun, A. Merla, and I. Pavlidis, "Contact-free measurement of cardiac pulse based on the analysis of thermal imagery," IEEE Trans. Biomed. Eng., vol. 54, no. 8, pp. 1418-1426, 2007. https://doi.org/10.1109/TBME.2007.891930
  5. M.-Z. Poh, D. J. McDuff, and R. W. Picard, "Non-contact, automated cardiac pulse measurements using video imaging and blind source separation," Optics Express, vol. 18, no. 10, pp. 10762-10774, 2010. https://doi.org/10.1364/OE.18.010762
  6. Y.-C. Lin, N.-K. Chou, G.-Y. Lin, M.-H. Li, and Y.-H. Lin, "A real-time contactless pulse rate and motion status monitoring system based on complexion tracking," Sensors, vol. 17, no. 7, pp. 1490, 2017. https://doi.org/10.3390/s17071490
  7. J.-P. Lomaliza and H. Park, "A highly efficient and reliable heart rate monitoring system using smartphone cameras," Multimed. Tools Appl., vol. 76, no. 20, pp. 21051-21071, 2017. https://doi.org/10.1007/s11042-016-4010-1
  8. D. Grimaldi, Y. Kurylyak, F. Lamonaca, and A. Nastro, "Photo-plethysmography detection by smart-phone's video camera," in IEEE Int. Conf. on Intell. Data Acqu. Adv. Compu. Syst., Prague, Czech Republic, 2011, pp. 488-491.
  9. M. A. Hassan, A. S. Malik, D. Fofi, N. Saad, B. Karasfi, Y. S. Ali, and F. Meriaudeau, "Heart rate estimation using facial video: A review," Biomedical Signal Processing and Control, vol. 38, pp. 346-360, 2017. https://doi.org/10.1016/j.bspc.2017.07.004
  10. G. Balakrishnan, F. Durand, and J. Guttag, "Detecting pulse from head motions in video," in CVPR, Portland, OR, USA, June 2013.
  11. J.-P. Lomaliza and H. Park, "Detecting pulse from head motions using smartphone camera," LNEE, vol. 415, pp. 243-251, 2016.
  12. Y.-G. Lim, "Development of chair backrest for non-intrusive simultaneous measurement of ECG and BCG," Journal of the Institute of Convergence Signal Processing, vol. 19, no. 3, pp. 104-109, 2018.
  13. J. Shi and C. Tomasi, "Good features to track," in IEEE Conference on Computer Vision and Pattern Recognition, 1994, pp. 593-600.
  14. B.D. Lucas and T. Kanade, "An iterative image registration technique with an application to stereo vision," in Imaging Understanding Workshop, 1981, pp. 121-130.