Skip to main content
SpringerLink
Log in

Noncontact Imaging Plethysmography for Accurate Estimation of Physiological Parameters

  • Original Article
  • Published:
Journal of Medical and Biological Engineering Aims and scope Submit manuscript

Abstract

In this paper, a novel non-contact device that accurately measures physiological parameters is proposed. This system consists of a CCD camera and a set of band pass filters. To eliminate the noise from the original signal, threshold segment and image registration algorithm are used. In addition, motion artifact is a vital issue that cannot be ignored. Here, an adaptive filter based on wavelet transform is introduced to reduce the motion artifact. Besides, the influence of ambient light intensity is discussed, which the result demonstrates that the change of ambient light intensity has no obvious impact on measurement results. Compared with the traditional contact method, this method is more convenient when mechanical isolation is required. Contrast experiment was performed with a multi-parameter monitor and a CO-oximeter. The comparison showed that our method is comparable with the contact method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Terminelli, L., Carpignano, F., May, J. M., Merlo, S., & Kyriacou, P. A. (2014). Photoplethysmography and electrocardiography for real time evaluation of pulse transit time a diagnostic marker of peripheral vascular diseases. In 2014 fotonica AEIT Italian conference on photonics technologies. IEEE, 2014.

  2. Gandhi, Pratiksha G., & Rao, Gundu H. R. (2014). The spectral analysis of photoplethysmography to evaluate an independent cardiovascular risk factor. International Journal of General Medicine, 7, 539.

    Google Scholar 

  3. Riede, F. T., Wörner, C., Dähnert, I., Möckel, A., Kostelka, M., & Schneider, P. (2010). Effectiveness of neonatal pulse oximetry screening for detection of critical congenital heart disease in daily clinical routine—Results from a prospective multicenter study. European Journal of Pediatrics, 169.8, 975–981.

  4. Sinex, James E. (1999). Pulse oximetry: Principles and limitations. The American Journal of Emergency Medicine, 17(1), 59–66.

    Article  Google Scholar 

  5. Sun, Yu., & Thakor, Nitish. (2016). Photoplethysmography revisited: From contact to noncontact, from point to imaging. IEEE Transactions on Biomedical Engineering, 63(3), 463–477.

    Article  Google Scholar 

  6. Fu, Tsu-Hsun, Liu, Shing-Hong, & Tang, Kuo-Tai. (2008). Heart rate extraction from photoplethysmogram waveform using wavelet multi-resolution analysis. Journal of Medical and Biological Engineering, 28(4), 229–232.

    Google Scholar 

  7. Anand, S., & Sujatha, N. (2015). Effects of probe placement on tissue oxygenation levels during reflectance measurements for different types of tissues in a clinical setting. In 2015 international conference on biophotonics (BioPhotonics). IEEE.

  8. Teng, X. F., & Zhang, Y. T. (2004). The effect of contacting force on photoplethysmographic signals. Physiological Measurement, 25(5), 1323.

    Article  Google Scholar 

  9. Grabovskis, A., Marcinkevics, Z., Rubins, U., & Kviesis-Kipge, E. (2013). Effect of probe contact pressure on the photoplethysmographic assessment of conduit artery stiffness. Journal of Biomedical Optics, 18.2, 027004–027004

  10. Wieringa, F. P., Mastik, F., & Van der Steen, A. F. W. (2005). Contactless multiple wavelength photoplethysmographic imaging: A first step toward “SpO2 camera” technology.” Annals of Biomedical Engineering, 33.8, 1034–1041.

  11. Humphreys, Kenneth, Ward, Tomas, & Markham, Charles. (2007). Noncontact simultaneous dual wavelength photoplethysmography: A further step toward noncontact pulse oximetry. Review of Scientific Instruments, 78(4), 044304.

    Article  Google Scholar 

  12. Kong, L., Zhao, Y., Dong, L., Jian, Y., Jin, X., Li, B., et al. (2013). Non-contact detection of oxygen saturation based on visible light imaging device using ambient light. Optics Express, 21(15), 17464–17471.

    Article  Google Scholar 

  13. Matcher, S. J., Elwell, C. E., Cooper, C. E., Cope, M., & Delpy, D. T. (1995). Performance comparison of several published tissue near-infrared spectroscopy algorithms. Analytical Biochemistry, 227(1), 54–68.

    Article  Google Scholar 

  14. Otsu, Nobuyuki. (1975). A threshold selection method from gray-level histograms. Automatica, 11(285-296), 23–27.

    Google Scholar 

  15. Pluim, J. P. W., Antoine Maintz, J. B., & Viergever, M. A. (2003). Mutual-information-based registration of medical images: A survey. IEEE Transactions on Medical Imaging, 22.8, 986–1004.

  16. Maes, F., Loeckx, D., Vandermeulen, D., & Suetens, P. (2015). Image registration using mutual information. Handbook of Biomedical Imaging (pp. 295–308).

  17. Viergever, M. A., Maintz, J. A., Klein, S., Murphy, K., Staring, M., & Pluim, J. P. (2016). A survey of medical image registration—Under review. Medical Image Analysis.

  18. Sardy, S., Tseng, P., & Bruce, A. (2001). Robust wavelet denoising. IEEE Transactions on Signal Processing, 49.6, 1146–1152.

  19. Hong, Zhang, Wei-xin, Sun, & Jie, Jin. (2000). Methods of noises elimination in the design of the pulse oximetry system. Foreign Medical Sciences (Biomedical Engineering Fascicle), 23(2), 90–95.

    Google Scholar 

  20. Bousefsaf, Frédéric, Maaoui, Choubeila, & Pruski, Alain. (2013). Continuous wavelet filtering on webcam photoplethysmographic signals to remotely assess the instantaneous heart rate. Biomedical Signal Processing and Control, 8(6), 568–574.

    Article  Google Scholar 

  21. Joseph, G., Joseph, A., Titus, G., Thomas, R. M., & Jose, D. (2014). Photoplethysmogram (PPG) signal analysis and wavelet de-noising. In Annual international conference on emerging research areas: Magnetics, machines and drives (AICERA/iCMMD), 2014. IEEE.

  22. Yadhuraj, S. R., & Harsha, H. (2013). Motion artifact reduction in photoplethysmographic signals: A review. International Journal of Innovative Research and Development, 2(3), 626–640.

    Google Scholar 

  23. Peng, F., Zhang, Z., Gou, X., Liu, H., & Wang, W. (2014). Motion artifact removal from photoplethysmographic signals by combining temporally constrained independent component analysis and adaptive filter. Biomedical Engineering Online, 13(1), 1.

    Article  Google Scholar 

  24. Sun, Y., Hu, S., Azorin-Peris, V., Greenwald, S., Chambers, J., & Zhu, Y. (2011). Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise. Journal of Biomedical Optics, 16(7), 077010–077010.

    Article  Google Scholar 

  25. Ram, M. R., Madhav, K. V., Krishna, E. H., Reddy, K. N., & Reddy, K. A. (2010). Adaptive reduction of motion artifacts from PPG signals using a synthetic noise reference signal. In 2010 IEEE EMBS conference on biomedical engineering and sciences (IECBES). IEEE, 2010.

  26. Bazes, M. (1999). Method and apparatus for detecting differential threshold levels while compensating for baseline wander. U.S. Patent No. 5,880,615. 9 Mar. 1999.

  27. Bland, J. M., & Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet, 327.8476, 307–310.

  28. Bland, J. M., & Altman, D. G. (2010). Statistical methods for assessing agreement between two methods of clinical measurement. International Journal of Nursing Studies, 47.8, 931–936.

  29. Xu, Xiu-zhen, Li, Zi-tian, & Xue, Li-jun. (2004). Analysis and processing of CCD noise. Infrared and Laser Engineering, 33(4), 343–346.

    Google Scholar 

Download references

Acknowledgments

This work was financially supported by Grants from the National Major Special Program of Scientific Instrument & Equipment Development of China (No. 2012YQ160203) and the first author also thanks financial supports by the Fundamental Research Funds for the Center Universities of China (No. 2011120202020006).

Author information

Authors and Affiliations

  1. Department of Electronic Science and Technology, School of Physics and Technology, Wuhan University, Wuhan, 430072, China

    Qiang Fan & Kaiyang Li

Authors
  1. Qiang Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kaiyang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kaiyang Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fan, Q., Li, K. Noncontact Imaging Plethysmography for Accurate Estimation of Physiological Parameters. J. Med. Biol. Eng. 37, 675–685 (2017). https://doi.org/10.1007/s40846-017-0272-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40846-017-0272-y

Keywords

Search

Navigation