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Computational and Mathematical Methods in Medicine
Volume 2013, Article ID 231762, 7 pages
http://dx.doi.org/10.1155/2013/231762
Research Article

Multiscale Cross-Approximate Entropy Analysis as a Measurement of Complexity between ECG R-R Interval and PPG Pulse Amplitude Series among the Normal and Diabetic Subjects

1Department of Electrical Engineering, National Dong Hwa University, Hualien 97401, Taiwan
2Department of Neurology, Buddhist Tzu Chi General Hospital and Buddhist Tzu Chi University, No. 707, Section 3, Chung-Yang Road, Hualien 97074, Taiwan

Received 21 June 2013; Revised 6 August 2013; Accepted 14 August 2013

Academic Editor: Kevin Ward

Copyright © 2013 Hsien-Tsai Wu 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. C.-K. Peng, M. Costa, and A. L. Goldberger, “Adaptive data analysis of complex fluctuations in physiologic time series,” Advances in Adaptive Data Analysis, vol. 1, no. 1, pp. 61–70, 2009. View at Publisher · View at Google Scholar · View at Scopus
  2. M. Costa, A. L. Goldberger, and C.-K. Peng, “Multiscale entropy analysis of biological signals,” Physical Review E, vol. 71, no. 2, Article ID 021906, 2005. View at Publisher · View at Google Scholar · View at Scopus
  3. M. U. Ahmed and D. P. Mandic, “Multivariate multiscale entropy: a tool for complexity analysis of multichannel data,” Physical Review E, vol. 84, no. 6, Article ID 061918, 2011. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Koskinen, T. Seppänen, S. Tong, S. Mustola, and N. V. Thakor, “Monotonicity of approximate entropy during transition from awareness to unresponsiveness due to propofol anesthetic induction,” IEEE Transactions on Biomedical Engineering, vol. 53, no. 4, pp. 669–675, 2006. View at Publisher · View at Google Scholar · View at Scopus
  5. R. Alcaraz and J. J. Rieta, “A review on sample entropy applications for the non-invasive analysis of atrial fibrillation electrocardiograms,” Biomedical Signal Processing and Control, vol. 5, no. 1, pp. 1–14, 2010. View at Publisher · View at Google Scholar · View at Scopus
  6. S. Berger, A. Kliem, V. Yeragani, and K.-J. Bär, “Cardio-respiratory coupling in untreated patients with major depression,” Journal of Affective Disorders, vol. 139, no. 2, pp. 166–171, 2012. View at Publisher · View at Google Scholar · View at Scopus
  7. X. Wang, D. M. Keenan, S. M. Pincus, P. Y. Liu, and J. D. Veldhuis, “Oscillations in joint synchrony of reproductive hormones in healthy men,” American Journal of Physiology, Endocrinology and Metabolism, vol. 301, no. 6, pp. E1163–E1173, 2011. View at Publisher · View at Google Scholar · View at Scopus
  8. A. G. Hudetz, “Effect of volatile anesthetics on interhemispheric EEG cross-approximate entropy in the rat,” Brain Research, vol. 954, no. 1, pp. 123–131, 2002. View at Publisher · View at Google Scholar · View at Scopus
  9. A. G. Hudetz, J. D. Wood, and J. P. Kampine, “Cholinergic reversal of isoflurane anesthesia in rats as measured by cross-approximate entropy of the electroencephalogram,” Anesthesiology, vol. 99, no. 5, pp. 1125–1131, 2003. View at Publisher · View at Google Scholar · View at Scopus
  10. M. Kreuzer, H. Hentschke, B. Antkowiak, C. Schwarz, E. F. Kochs, and G. Schneider, “Cross-approximate entropy of cortical local field potentials quantifies effects of anesthesia—a pilot study in rats,” BMC Neuroscience, vol. 11, no. 122, 2010. View at Publisher · View at Google Scholar · View at Scopus
  11. J. S. Chang, K. Ha, I. Y. Yoon et al., “Patterns of cardiorespiratory coordination in young women with recurrent major depressive disorder treated with escitalopram or venlafaxine,” Progress in Neuro-Psychopharmacology and Biological Psychiatry, vol. 39, no. 1, pp. 136–142, 2012. View at Google Scholar
  12. J. Peupelmann, M. K. Boettger, C. Ruhland et al., “Cardio-respiratory coupling indicates suppression of vagal activity in acute schizophrenia,” Schizophrenia Research, vol. 112, no. 1, pp. 153–157, 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. H. T. Wu, C. C. Liu, M. T. Lo et al., “Multiscale cross-approximate entropy analysis as a measure of complexity among the aged and diabetic,” Computational and Mathematical Methods in Medicine, vol. 2013, Article ID 324325, 7 pages, 2013. View at Publisher · View at Google Scholar
  14. M. Costa, A. L. Goldberger, and C.-K. Peng, “Multiscale entropy analysis of complex physiologic time series,” Physical Review Letters, vol. 89, no. 6, Article ID 068102, 2002. View at Google Scholar · View at Scopus
  15. M. Costa, C.-K. Peng, A. L. Goldberger, and J. M. Hausdorff, “Multiscale entropy analysis of human gait dynamics,” Physica A, vol. 330, no. 1-2, pp. 53–60, 2003. View at Publisher · View at Google Scholar · View at Scopus
  16. H.-T. Wu, P.-C. Hsu, C.-F. Lin et al., “Multiscale entropy analysis of pulse wave velocity for assessing atherosclerosis in the aged and diabetic,” IEEE Transactions on Biomedical Engineering, vol. 58, no. 10, pp. 2978–2981, 2011. View at Publisher · View at Google Scholar · View at Scopus
  17. H.-T. Wu, M.-T. Lo, G.-H. Chen, C.-K. Sun, and J.-J. Chen, “Novel application of a multiscale entropy index as a sensitive tool for detecting subtle vascular abnormalities in the aged and diabetic,” Computational and Mathematical Methods in Medicine, vol. 2013, Article ID 645702, 8 pages, 2013. View at Publisher · View at Google Scholar
  18. A. B. Liu, P. C. Hsu, Z. L. Chen, and H. T. Wu, “Measuring pulse wave velocity using ECG and photoplethysmography,” Journal of Medical Systems, vol. 35, no. 5, pp. 771–777, 2011. View at Publisher · View at Google Scholar · View at Scopus
  19. H. T. Wu, P. C. Hsu, A. B. Liu et al., “Six-channel ECG-based pulse wave velocity for assessing whole-body arterial stiffness,” Blood Press, vol. 21, no. 3, pp. 167–176, 2012. View at Google Scholar
  20. Z. Wu, N. E. Huang, S. R. Long, and C.-K. Peng, “On the trend, detrending, and variability of nonlinear and nonstationary time series,” Proceedings of the National Academy of Sciences of the United States of America, vol. 104, no. 38, pp. 14889–14894, 2007. View at Publisher · View at Google Scholar · View at Scopus
  21. N. E. Huang, Z. Shen, S. R. Long et al., “The empirical mode decomposition and the Hubert spectrum for nonlinear and non-stationary time series analysis,” Proceedings of the Royal Society A, vol. 454, no. 1971, pp. 903–995, 1998. View at Google Scholar · View at Scopus
  22. S. Pincus and B. H. Singer, “Randomness and degrees of irregularity,” Proceedings of the National Academy of Sciences of the United States of America, vol. 93, no. 5, pp. 2083–2088, 1996. View at Publisher · View at Google Scholar · View at Scopus
  23. S. M. Pincus, “Approximate entropy in cardiology,” Herzschrittmachertherapie und Elektrophysiologie, vol. 11, no. 3, pp. 139–150, 2000. View at Google Scholar · View at Scopus
  24. S. M. Pincus, “Irregularity and asynchrony in biologic network signals,” Methods in Enzymology, vol. 321, pp. 149–182, 2000. View at Google Scholar · View at Scopus
  25. Y. Fusheng, H. Bo, and T. Qingyu, “Approximate entropy and its application to biosignal analysis,” Nonlinear Biomedical Signal Processing, vol. 2, pp. 72–91, 2001. View at Google Scholar
  26. S. M. Pincus, “Approximate entropy as a measure of system complexity,” Proceedings of the National Academy of Sciences of the United States of America, vol. 88, no. 6, pp. 2297–2301, 1991. View at Google Scholar · View at Scopus
  27. D. Cheng, S.-J. Tsai, C.-J. Hong, and A. C. Yang, “Reduced physiological complexity in robust elderly adults with the APOE ε4 allele,” PLoS ONE, vol. 4, no. 11, Article ID e7733, 2009. View at Publisher · View at Google Scholar · View at Scopus
  28. H. T. Wu, C. C. Liu, Y. C. Huang et al., “A simplified method for assessing spontaneous baroreflex in diabetic subjects and aged persons by pressure pulse analysis with pulse-pulse intervals and pulse amplitudes,” Journal of Medical and Biological Engineering, 2013. View at Publisher · View at Google Scholar
  29. K. Dewitte, C. Fierens, D. Stöckl, and L. M. Thienpont, “Application of the Bland-Altman plot for interpretation of method-comparison studies: a critical investigation of its practice,” Clinical Chemistry, vol. 48, no. 5, pp. 799–801, 2002. View at Google Scholar · View at Scopus
  30. M. P. Tarvainen, J. A. Lipponen, H. Al-Aubaidy, and H. F. Jelinek, “Effect of hyperglycemia on cardiac autonomic function in type 2 diabetes,” Proceedings of the Computing in Cardiology (CinC '12), pp. 405–408, 2012. View at Google Scholar
  31. N. Okada, N. Takahashi, K. Yufu et al., “Baroreflex sensitivity predicts cardiovascular events in patients with type 2 diabetes mellitus without structural heart disease,” Circulation Journal, vol. 74, no. 7, pp. 1379–1383, 2010. View at Publisher · View at Google Scholar · View at Scopus
  32. G. Parati and G. Bilo, “Arterial baroreflex modulation of sympathetic activity and arterial wall properties: new evidence,” Hypertension, vol. 59, no. 1, pp. 5–7, 2012. View at Publisher · View at Google Scholar · View at Scopus
  33. G. Mancia and A. L. Mark, “Arterial baroreflexes in humans,” in Comprehensive Physiology, 1983. View at Publisher · View at Google Scholar
  34. A. J. Liu, X. J. Ma, F. M. Shen, J. G. Liu, H. Chen, and D. F. Su, “Arterial baroreflex: a novel target for preventing stroke in rat hypertension,” Stroke, vol. 38, no. 6, pp. 1916–1923, 2007. View at Publisher · View at Google Scholar · View at Scopus
  35. Y. Hodgson and J. Choate, “Continuous and noninvasive recording of cardiovascular parameters with the Finapres finger cuff enhances undergraduate student understanding of physiology,” American Journal of Physiology: Advances in Physiology Education, vol. 36, no. 1, pp. 20–26, 2012. View at Publisher · View at Google Scholar · View at Scopus
  36. B. P. Imholz, J. J. Settels, A. H. van der Meiracker, K. H. Wesseling, and W. Wieling, “Non-invasive continuous finger blood pressure measurement during orthostatic stress compared to intra-arterial pressure,” Cardiovascular Research, vol. 24, no. 3, pp. 214–221, 1990. View at Google Scholar · View at Scopus