Neuro-fuzzy Indirect Blood Pressure Estimation during Bruce Stress Test

Soheil Mottaghi, Mohammad Hassan Moradi, Mahmoud Moghavvemi, Leyla Roohisefat, Eshwar C. V. Sagar

2014

Abstract

An accurate blood pressure monitoring method during the course of an exercise stress test is paramount. This is due to the fact that the patients are under intense physical pressure, and most of the time, are usually afflicted with cardiovascular problems. Exercise or intense physical activities elevates blood pressures, which renders cuff-based measuring systems highly inaccurate, but convenient for lesser artifacts. Much research has been conducted on The Pulse Arrival Time (PAT), and it was concluded that it is inexplicably linked to blood pressure. In this study, we propose a novel approach using a neuro-fuzzy system (Fuzzy Type I) and Adaptive neuro-fuzzy inference system (ANFIS)for cuffless blood pressure estimation before, during, and after the stress test. Systolic BP and diastolic BP estimation were carried out in this study as well. There are no significant advantages in having lower error rate and/or higher correlation coefficients between the fuzzy systems. However it has been shown that the results of the non-linear fuzzy estimators possess higher correlation and lower errors than the Least Squared regression introduced in previous studies.

References

  1. Pickering, T., et al, 2005. "Recommendations for blood pressure measurement in humans and experimental animals-part 1: Blood pressure measurement in humans," Hypertension, vol. 45, p. 14261.
  2. Baker, P., Westenskow, D., and Kück, K., 1997. "Theoretical analysis of non-invasive oscillometric maximum amplitude algorithm for estimating mean blood pressure," Medical and Biological Engineering and Computing, vol. 35, pp. 271-278.
  3. Poon, C., Zhang, Y., 2005. "Cuff-less and Noninvasive Measurements of Arterial Blood Pressure by Pulse Transit Time," 27th Annual International Conference of the Engineering in Medicine and Biology Society, Chinease University, HK, pp. 5877-5880.
  4. Naka, K et. al, 2003. "Arterial distensibility: acute changes following dynamic exercise in normal subjects," American Journal of Physiology - Heart and Circulatory Physiology, vol. 284, pp. H970-H978.
  5. Kingwell, B., et al., 1997. "Arterial compliance increases after moderate-intensity cycling," American Journal of Physiology - Heart and Circulatory Physiology, vol. 273, pp. H2186-H2191.
  6. Zhang, W., et al., 2007. "Viscoelasticity reduces the dynamic stresses and strains in the vessel wall: implications for vessel fatigue," American Journal of Physiology - Heart and Circulatory Physiology, vol. 293, pp. H2355-H2360.
  7. Wong, M., et al., 2011. "The effects of pre-ejection period on post-exercise systolic blood pressure estimation using the pulse arrival time technique," European Journal of Applied Physiology, vol. 111, pp. 135-144.
  8. Forouzanfar, M., et al., 2011. "Feature-Based Neural Network Approach for Oscillometric Blood Pressure Estimation," Instrumentation and Measurement, IEEE Transactions on, vol.60, no.8, pp.2786-2796.
  9. Jia-Jung, W., et al., 2002. "Model-based synthetic fuzzy logic controller for indirect blood pressure measurement," Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 32, pp. 306-315.
  10. Colak, S., 2003. "Fuzzy oscillometric blood pressure classification," 22nd International Conference of the North American, Fuzzy Information Processing Society, Syracuse University, NY, pp. 208-213.
  11. Mottaghi, S., et al., 2012. "Cuffless Blood Pressure Estimation during Exercise Stress Test" International Journal of Bioscience, Biochemistry and Bioinformatics vol. 2, no. 6, pp. 395-398.
  12. Shahsavari, S., et al., 2011. "Cerebrovascular Mechanical Properties and Slow Waves of Intracranial Pressure in TBI Patients," Biomedical Engineering, IEEE Transactions on, vol. 58, pp. 2072-2082.
  13. Man, S., et al., 2007. "Reconstruction of standard 12-Lead ECGs from 12-lead ECGs recorded with the MasonLikarelectrode configuration," in Computers in Cardiology, vol 41, pp. 701-704.
  14. Bezdek, J., et al., 1987. "Convergence theory for fuzzy cmeans: Counterexamples and repairs," Systems, Man and Cybernetics, IEEE Transactions on, vol. 17, pp. 873-877.
  15. Setnes, M., 2000. "Supervised fuzzy clustering for rule extraction," Fuzzy Systems, IEEE Transactions on, vol. 8, pp. 416-424.
  16. Wang, L., et al., 1992. "Back-propagation fuzzy system as nonlinear dynamic system identifiers," IEEE International Conference on Fuzzy Systems, Los Angeles, CA , pp. 1409-1418.
  17. Narendra, K., 1990. "Identification and control of dynamical systems using neural networks," Neural Networks, IEEE Transactions on, vol. 1, pp. 4-27.
  18. Jang, J., 1993. "ANFIS: adaptive-network-based fuzzy inference system," Systems, Man and Cybernetics, IEEE Transactions on, vol. 23, pp. 665-685.
  19. Sarle, W., 1995. “Stopped training and other remedies for overfitting,” in Proc. 27th Symp. Interface Comput. Sci. Statist., Pittsburgh, PA, pp. 352-360.
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Paper Citation


in Harvard Style

Mottaghi S., Hassan Moradi M., Moghavvemi M., Roohisefat L. and C. V. Sagar E. (2014). Neuro-fuzzy Indirect Blood Pressure Estimation during Bruce Stress Test . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014) ISBN 978-989-758-011-6, pages 257-263. DOI: 10.5220/0004862402570263


in Bibtex Style

@conference{biosignals14,
author={Soheil Mottaghi and Mohammad Hassan Moradi and Mahmoud Moghavvemi and Leyla Roohisefat and Eshwar C. V. Sagar},
title={Neuro-fuzzy Indirect Blood Pressure Estimation during Bruce Stress Test},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)},
year={2014},
pages={257-263},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004862402570263},
isbn={978-989-758-011-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)
TI - Neuro-fuzzy Indirect Blood Pressure Estimation during Bruce Stress Test
SN - 978-989-758-011-6
AU - Mottaghi S.
AU - Hassan Moradi M.
AU - Moghavvemi M.
AU - Roohisefat L.
AU - C. V. Sagar E.
PY - 2014
SP - 257
EP - 263
DO - 10.5220/0004862402570263