Cuff-less Calibration-free Blood Pressure Estimation under Ambulatory Environment using Pulse Wave Velocity and Photoplethysmogram Signals

Haruyuki Sanuki, Rui Fukui, Tsukasa Inajima, Shin'ichi Warisawa

2017

Abstract

This paper presents a blood pressure estimation method based on pulse wave velocity (PWV). Although there are a variety of methods based on PWV to estimate blood pressure, most of them require calibration per patient, and the patient has to remain still. The goal of our research is to develop a calibration-free blood pressure estimation method that is applicable not only during rest but also during exercise. To accomplish our goal, we extracted properties of blood vessels from photoplethysmogram (PPG) signals, and compared several regression models, such as the deductive model based on blood vessel physics equation, and the inductive model based on machine learning. Twenty-four participants performed exercise, measuring blood pressure, electrocardiogram (ECG) and PPG. The best result showed that the mean error for the estimated systolic blood pressure (SBP) against cuff-based blood pressure was 0.18 ± 8.68 mmHg. Although there was not a big difference between the regression models, PWV and Augmentation Index are effective features to estimate SBP. In addition to this, Heart Rate was effective only for the young men, and height ratio of c-wave to a-wave of acceleration pulse wave might be effective for elderly men. These results suggest that our proposed method has the potential for cuff-less calibration-free blood pressure estimation which include measurements during rest and exercise.

References

  1. Alty, S., Angarita, J. N., Millasseau, S., Chowienczyk P., 2007. Predicting arterial stiffness from the digital volume pulse waveform. IEEE Transactions on Biomedical Engineering, 54(12), pp.2268-2275.
  2. Boser, B. E., Guyon, I. M., Vapnik, V.N., 1992. A training algorithm for optimal margin classifiers. Proceedings of the fifth annual workshop on Computational learning theory - COLT 7892, pp.144-152.
  3. Breiman, L., 2001. Random forests. Machine Learning, 45(1), pp. 5-32.
  4. Caruana, R. Freitag, D., 1994. Greedy attribute selection. Machine Learning Proceedings 1994, pp.28-36.
  5. Cover, T. M., Hart, P. E., 1967. Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13(1), pp.21-27.
  6. Daubechies, I., 1992. Ten lectures on wavelets. Society for Industrial and Applied Mathematics Philadelphia, PA.
  7. Ding, X. R., Zhang, Y. T., Liu, J., Dai, W. X., Tsang, H. K., 2016. Continuous cuffless blood pressure estimation using pulse transit time and photoplethysmogram intensity ratio. IEEE Transactions on Biomedical Engineering, 63(5), pp.964-972.
  8. Elgendi, M., 2012. On the analysis of fingertip photoplethysmogram Signals. Current Cardiology Reviews, 8(1), pp.14-25.
  9. Fan, Z., Zhang, G., Liao, S., 2011.Pulse wave analysis. Advanced Biomedical Engineering, pp.21-40.
  10. Gesche, H., Grosskurth, D., Kuchler, G., Patzak, A., 2012. Continuous blood pressure measurement by using the pulse transit time: comparison to a cuff-based method. European Journal of Applied Physiology, 112(1), pp.309-315.
  11. Homma, S., Ito, S., Koto, T., Ikegami, H., 1992. Relationship between accelerated plethysmogram, blood pressure and arteriolar elasticity. Japanese Journal of Physical Fitness and Sports Medicine, 41(1), pp.98-107.
  12. Inajima, T., Imai, Y., Shuzo, M., Lopez, G., Yanagimoto, S., Iijima, Katsuya, Morita, H., Nagai, R., Yahagi, N., Yamada, I., 2012. Relation between blood pressure estimated by pulse wave velocity and directly measured arterial pressure. Journal of Robotics and Mechatronics, 24(5), pp.811-819.
  13. IEEE Standards Association, 2014. IEEE standard for wearable, cuffless blood pressure measuring devices.
  14. Kachuee, M., Kiani, M. M., Mohammadzade H., Shabany M., 2015. Cuff-less high-accuracy calibration-free blood pressure estimation using pulse transit time. 2015 IEEE International Symposium on Circuits and Systems (ISCAS).
  15. Legarreta, I.R., Addison, P. S., Reed, M. J., Grubb, N., Clegg, G. R., Robertson, C. E., Watson, J. N., 2005. Continuous wavelet Transform modulus maxima analysis of the electrocardiogram: beat characterisation and beat-to-beat measurement. International Journal of Wavelets, Multiresolution and Information Processing, 03(01), pp.19-42.
  16. Lopez, G., Shuzo, M., Ushida, H., Hidaka, K., Yanagimoto, S., Imai, Y., Kosaka, A., Delaunay, J. J., Yamada, I., 2010. Continuous blood pressure monitoring in daily life. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 4(1), pp.179-186.
  17. Mourad, J.J., 2008. The evolution of systolic blood pressure as a strong predictor of cardiovascular risk and the effectiveness of fixed-dose ARB/CCB combinations in lowering levels of this preferential target. Vasc Health Risk Manag, 4(6), pp.1315-1325.
  18. Mukkamala, R., Hahn, J., Inan, O. T., Mestha, L. K., Kim, C., Toreyin, H., Kyal, S., 2015. Toward ubiquitous blood pressure monitoring via pulse transit time: theory and practice. IEEE Transactions on Biomedical Engineering, 62(8), pp.1879-1901.
  19. Takazawa, K., Tanaka, N., Fujita, M., Matsuoka, O., Saiki, T., Aikawa, M., Tamura, S., Ibukiyama, C., 1998. Assessment of vasoactive agents and vascular aging by the second derivative of photoplethysmogram waveform. Hypertension, 32(2), pp.365-370.
  20. Wang, L., Pickwell, M. E., Liang, Y. P., Zhang, Y. T., 2009. Noninvasive cardiac output estimation using a novel photoplethysmogram index. 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.1746-1749.
  21. World Health Organization, 2014. Global Health Statistics 2014.
Download


Paper Citation


in Harvard Style

Sanuki H., Fukui R., Inajima T. and Warisawa S. (2017). Cuff-less Calibration-free Blood Pressure Estimation under Ambulatory Environment using Pulse Wave Velocity and Photoplethysmogram Signals . In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017) ISBN 978-989-758-212-7, pages 42-48. DOI: 10.5220/0006112500420048


in Bibtex Style

@conference{biosignals17,
author={Haruyuki Sanuki and Rui Fukui and Tsukasa Inajima and Shin'ichi Warisawa},
title={Cuff-less Calibration-free Blood Pressure Estimation under Ambulatory Environment using Pulse Wave Velocity and Photoplethysmogram Signals},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017)},
year={2017},
pages={42-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006112500420048},
isbn={978-989-758-212-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017)
TI - Cuff-less Calibration-free Blood Pressure Estimation under Ambulatory Environment using Pulse Wave Velocity and Photoplethysmogram Signals
SN - 978-989-758-212-7
AU - Sanuki H.
AU - Fukui R.
AU - Inajima T.
AU - Warisawa S.
PY - 2017
SP - 42
EP - 48
DO - 10.5220/0006112500420048