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BioMed Research International
Volume 2014, Article ID 923260, 10 pages
http://dx.doi.org/10.1155/2014/923260
Research Article

Modelling Arterial Pressure Waveforms Using Gaussian Functions and Two-Stage Particle Swarm Optimizer

1School of Control Science and Engineering, Shandong University, Jinan 250061, China
2School of Information Science and Engineering, Shandong University, Jinan 250100, China
3Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
4National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

Received 21 March 2014; Revised 27 April 2014; Accepted 27 April 2014; Published 20 May 2014

Academic Editor: John J. Gildea

Copyright © 2014 Chengyu Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. E. Hermeling, A. P. G. Hoeks, M. H. M. Winkens et al., “Noninvasive assessment of arterial stiffness should discriminate between systolic and diastolic pressure ranges,” Hypertension, vol. 55, no. 1, pp. 124–130, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. Y. J. Sheen, J. L. Lin, T. C. Li, C. T. Bau, and W. H. H. Sheu, “Peripheral arterial stiffness is independently associated with a rapid decline in estimated glomerular filtration rate in patients with type 2 diabetes,” BioMed Research International, vol. 2013, Article ID 309294, 10 pages, 2013. View at Publisher · View at Google Scholar
  3. J. N. Cohn, S. Finkelstein, G. McVeigh et al., “Noninvasive pulse wave analysis for the early detection of vascular disease,” Hypertension, vol. 26, no. 3, pp. 503–508, 1995. View at Google Scholar · View at Scopus
  4. A. Swillens and P. Segers, “Assessment of arterial pressure wave reflection: methodological considerations,” Artery Research, vol. 2, no. 4, pp. 122–131, 2008. View at Publisher · View at Google Scholar · View at Scopus
  5. M. C. Baruch, D. E. R. Warburton, S. S. D. Bredin, A. Cote, D. W. Gerdt, and C. M. Adkins, “Pulse Decomposition Analysis of the digital arterial pulse during hemorrhage simulation,” Nonlinear Biomedical Physics, vol. 5, no. 1, pp. 1–15, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. P. Segers, J. Mynard, L. Taelman, S. Vermeersch, and A. Swillens, “Wave reflection: myth or reality?” Artery Research, vol. 6, no. 1, pp. 7–11, 2012. View at Publisher · View at Google Scholar · View at Scopus
  7. J. Sugawara, K. Hayashi, and H. Tanaka, “Distal shift of arterial pressure wave reflection sites with aging,” Hypertension, vol. 56, no. 5, pp. 920–925, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. B. E. Westerhof, I. Guelen, N. Westerhof, J. M. Karemaker, and A. Avolio, “Quantification of wave reflection in the human aorta from pressure alone: a proof of principle,” Hypertension, vol. 48, no. 4, pp. 595–601, 2006. View at Publisher · View at Google Scholar · View at Scopus
  9. G. F. Mitchell, H. Parise, E. J. Benjamin et al., “Changes in arterial stiffness and wave reflection with advancing age in healthy men and women: the Framingham Heart Study,” Hypertension, vol. 43, no. 6, pp. 1239–1245, 2004. View at Publisher · View at Google Scholar · View at Scopus
  10. M. Frimodt-Moller, A. L. Kamper, S. Strandgaard, S. Kreiner, and A. H. Nielsen, “Beneficial effects on arterial stiffness and pulse-wave reflection of combined enalapril and candesartan in chronic kidney disease—a randomized trial,” PLoS ONE, vol. 7, no. 7, Article ID e41757, 2012. View at Google Scholar
  11. S. Asgari, N. Gonzalez, A. W. Subudhi et al., “Continuous detection of cerebral vasodilatation and vasoconstriction using intracranial pulse morphological template matching,” PLoS ONE, vol. 7, no. 11, Article ID e50795, 2012. View at Google Scholar
  12. A. Zambanini, S. L. Cunningham, K. H. Parker, A. W. Khir, S. A. M. Thom, and A. D. Hughes, “Wave-energy patterns in carotid, brachial, and radial arteries: a noninvasive approach using wave-intensity analysis,” The American Journal of Physiology—Heart and Circulatory Physiology, vol. 289, no. 1, pp. H270–H276, 2005. View at Publisher · View at Google Scholar · View at Scopus
  13. N. Westerhof, P. Sipkema, G. C. V. D. Bos, and G. Elzinga, “Forward and backward waves in the arterial system,” Cardiovascular Research, vol. 6, no. 6, pp. 648–656, 1972. View at Publisher · View at Google Scholar · View at Scopus
  14. S. C. Millasseau, R. P. Kelly, J. M. Ritter, and P. J. Chowienczyk, “Determination of age-related increases in large artery stiffness by digital pulse contour analysis,” Clinical Science, vol. 103, no. 4, pp. 371–377, 2002. View at Google Scholar · View at Scopus
  15. L. A. Bortolotto, J. Blacher, T. Kondo, K. Takazawa, and M. E. Safar, “Assessment of vascular aging and atherosclerosis in hypertensive subjects: second derivative of photoplethysmogram versus pulse wave velocity,” The American Journal of Hypertension, vol. 13, no. 2, pp. 165–171, 2000. View at Publisher · View at Google Scholar · View at Scopus
  16. M. Karamanoglu, “A system for analysis of arterial blood pressure waveforms in humans,” Computers and Biomedical Research, vol. 30, no. 3, pp. 244–255, 1997. View at Publisher · View at Google Scholar
  17. A. D. Hughes, C. Park, J. Davies et al., “Limitations of augmentation index in the assessment of wave reflection in normotensive healthy individuals,” PLoS ONE, vol. 8, no. 3, Article ID e59371, 2013. View at Google Scholar
  18. M. Huotari, A. Vehkaoja, K. Määttä, and J. Kostamovaara, “Pulse waveforms are an indicator of the condition of vascular system,” in Proceedings of the World Congress on Medical Physics and Biomedical Engineering., vol. 39, pp. 526–529, Beijing, China, 2012.
  19. M. Huotari, A. Vehkaoja, K. Määttä, and J. Kostamovaara, “Photoplethysmography and its detailed pulse waveform analysis for arterial stiffness,” Journal of Structural Mechanics, vol. 44, no. 4, pp. 345–362, 2011. View at Google Scholar
  20. L. Wang, L. S. Xu, S. T. Feng, M. Q. H. Meng, and K. Q. Wang, “Multi-Gaussian fitting for pulse waveform using weighted least squares and multi-criteria decision making method,” Computers in Biology and Medicine, vol. 43, no. 11, pp. 1661–1672, 2013. View at Publisher · View at Google Scholar
  21. L. Xu, S. Feng, Y. Zhong, C. Feng, M. Q.-H. Meng, and H. Yan, “Multi-Gaussian fitting for digital volume pulse using weighted least squares method,” in Proceedings of the International Conference on Information and Automation (ICIA '11), pp. 544–549, Shenzhen, China, June 2011. View at Publisher · View at Google Scholar · View at Scopus
  22. U. Rubins, “Finger and ear photoplethysmogram waveform analysis by fitting with Gaussians,” Medical and Biological Engineering and Computing, vol. 46, no. 12, pp. 1271–1276, 2008. View at Publisher · View at Google Scholar · View at Scopus
  23. C. Y. Liu, D. C. Zheng, A. Murray, and C. C. Liu, “Modelling carotid and radial artery pulse pressure waveforms by curve fitting with Gaussian functions,” Biomedical Signal Processing and Control, vol. 8, no. 5, pp. 449–454, 2013. View at Publisher · View at Google Scholar
  24. C. Y. Liu, D. C. Zheng, L. N. Zhao, and C. C. Liu, “Gaussian fitting for carotid and radial artery pressure waveforms: comparison between normal subjects and heart failure patients,” Bio-Medical Materials and Engineering, vol. 24, no. 1, pp. 271–277, 2014. View at Google Scholar
  25. T. Zhuang, Q. Li, Q. Guo, and X. Wang, “A two-stage particle swarm optimizer,” in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '08), pp. 557–563, June 2008. View at Publisher · View at Google Scholar · View at Scopus
  26. M. Nasir, S. Das, D. Maity, S. Sengupta, U. Halder, and P. N. Suganthan, “A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization,” Information Sciences, vol. 209, no. 5, pp. 16–36, 2012. View at Publisher · View at Google Scholar
  27. R. Mendes, J. Kennedy, and J. Neves, “The fully informed particle swarm: simpler, maybe better,” IEEE Transactions on Evolutionary Computation, vol. 8, no. 3, pp. 204–210, 2004. View at Publisher · View at Google Scholar · View at Scopus
  28. M. A. Luersen and R. le Riche, “Globalized nelder-mead method for engineering optimization,” Computers & Structures, vol. 82, no. 23–26, pp. 2251–2260, 2004. View at Publisher · View at Google Scholar · View at Scopus
  29. H.-L. Shieh, C.-C. Kuo, and C.-M. Chiang, “Modified particle swarm optimization algorithm with simulated annealing behavior and its numerical verification,” Applied Mathematics and Computation, vol. 218, no. 8, pp. 4365–4383, 2011. View at Publisher · View at Google Scholar · View at Scopus
  30. J. J. Liang and P. N. Suganthan, “Dynamic multi-swarm particle swarm optimizer,” in Proceedings of the IEEE Swarm Intelligence Symposium (SIS '05), pp. 124–129, June 2005. View at Publisher · View at Google Scholar · View at Scopus
  31. J. P. Martínez, R. Almeida, S. Olmos, A. P. Rocha, and P. Laguna, “A wavelet-based ECG delineator evaluation on standard databases,” IEEE Transactions on Biomedical Engineering, vol. 51, no. 4, pp. 570–581, 2004. View at Publisher · View at Google Scholar · View at Scopus
  32. C. Y. Liu, L. P. Li, L. N. Zhao, D. C. Zheng, P. Li, and C. C. Liu, “A combination method of improved impulse rejection filter and template matching for identification of anomalous intervals in electrocardiographic RR sequences,” Journal of Medical and Biological Engineering, vol. 32, no. 4, pp. 245–250, 2012. View at Publisher · View at Google Scholar
  33. J. Solà, R. Vetter, P. Renevey, O. Chételat, C. Sartori, and S. F. Rimoldi, “Parametric estimation of pulse arrival time: a robust approach to pulse wave velocity,” Physiological Measurement, vol. 30, no. 7, pp. 603–615, 2009. View at Publisher · View at Google Scholar · View at Scopus
  34. Y. Shi and R. Eberhart, “Modified particle swarm optimizer,” in Proceedings of the IEEE IEEE World Congress on Computational Intelligence, The IEEE International Conference on Evolutionary Computation, pp. 69–73, May 1998. View at Scopus
  35. D. Goswami, K. Chaudhuri, and J. Mukherjee, “A new two-pulse synthesis model for digital volume pulse signal analysis,” Cardiovascular Engineering, vol. 10, no. 3, pp. 109–117, 2010. View at Publisher · View at Google Scholar · View at Scopus
  36. W. Qian, L. Xu, F. Chen, and R. Zheng, “Acquiring characteristics of pulse wave by Gauss function separation,” Chinese Journal of Biomedical Engineering, vol. 13, no. 1, pp. 1–7, 1994. View at Google Scholar · View at Scopus
  37. J. J. Liang, P. N. Suganthan, C. C. Chan, and V. L. Huang, “Wavelength detection in FBG sensor network using tree search DMS-PSO,” IEEE Photonics Technology Letters, vol. 18, no. 12, pp. 1305–1307, 2006. View at Publisher · View at Google Scholar · View at Scopus
  38. M. F. O'Rourke and W. W. Nichols, “Changes in wave reflection with advancing age in normal subjects,” Hypertension, vol. 44, no. 6, pp. E10–E11, 2004. View at Google Scholar · View at Scopus
  39. P. Segers, E. R. Rietzschel, M. L. de Buyzere et al., “Assessment of pressure wave reflection: getting the timing right!,” Physiological Measurement, vol. 28, no. 9, pp. 1045–1056, 2007. View at Publisher · View at Google Scholar · View at Scopus