Skip to main content
Log in

Aging reduces complexity of heart rate variability assessed by conditional entropy and symbolic analysis

  • IM - ORIGINAL
  • Published:
Internal and Emergency Medicine Aims and scope Submit manuscript

Abstract

Increasing age is associated with a reduction in overall heart rate variability as well as changes in complexity of physiologic dynamics. The aim of this study was to verify if the alterations in autonomic modulation of heart rate caused by the aging process could be detected by Shannon entropy (SE), conditional entropy (CE) and symbolic analysis (SA). Complexity analysis was carried out in 44 healthy subjects divided into two groups: old (n = 23, 63 ± 3 years) and young group (n = 21, 23 ± 2). It was analyzed SE, CE [complexity index (CI) and normalized CI (NCI)] and SA (0V, 1V, 2LV and 2ULV patterns) during short heart period series (200 cardiac beats) derived from ECG recordings during 15 min of rest in a supine position. The sequences characterized by three heart periods with no significant variations (0V), and that with two significant unlike variations (2ULV) reflect changes in sympathetic and vagal modulation, respectively. The unpaired t test (or Mann–Whitney rank sum test when appropriate) was used in the statistical analysis. In the aging process, the distributions of patterns (SE) remain similar to young subjects. However, the regularity is significantly different; the patterns are more repetitive in the old group (a decrease of CI and NCI). The amounts of pattern types are different: 0V is increased and 2LV and 2ULV are reduced in the old group. These differences indicate marked change of autonomic regulation. The CE and SA are feasible techniques to detect alteration in autonomic control of heart rate in the old group.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Malliani A, Montano N (2002) Emerging excitatory role of cardiovascular sympathetic afferents in pathophysiological conditions. Hypertension 39:63–68

    Article  PubMed  CAS  Google Scholar 

  2. Di Rienzo M, Porta A (2009) Clinical applications of linear and nonlinear components. IEEE Eng Med Biol Mag nov/dic:16–17

  3. Porta A, Faes L, Masé M et al (2007) An integrated approach based on uniform quantization for the evaluation of complexity of short-term heart period variability: application to 24 h Holter recordings in healthy and heart failure humans. Chaos 17:015117-1–015117-11

    Google Scholar 

  4. Porta A, Guzzetti S, Furlan R, Gnecchi-Ruscone T, Montano N, Malliani A (2007) Complexity and nonlinearity in short-term heart period variability: comparison of methods based on local nonlinear prediction. IEEE Trans Biomed Eng 54:94–106

    Article  PubMed  Google Scholar 

  5. Pincus SM (1995) Approximated entropy (ApEn) as a complexity measure. Chaos 5:110–117

    Article  PubMed  Google Scholar 

  6. Pikkujämsä SM, Mäkikallio TH, Sourander LB et al (1999) Cardiac interbeat interval dynamics from childhood to senescence: comparison of conventional and new measures based on fractals and chaos theory. Circulation 100:393–399

    PubMed  Google Scholar 

  7. Kaplan DT, Furman M, Pincus SM, Ryan SM, Lipsitz LA, Goldberger AL (1991) Aging and the complexity of cardiovascular dynamics. Biophys J 59:945–949

    Article  PubMed  CAS  Google Scholar 

  8. Lipsitz LA, Mietus J, Moody GB, Goldberger AL (1990) Spectral characteristics of heart rate variability before and during postural tilt: relations to aging and risk of syncope. Circulation 81:1803–1810

    Article  PubMed  CAS  Google Scholar 

  9. Lipsitz LA, Goldberger AL (1992) Loss of “complexity” and aging: potential applications of fractals and chaos theory to senescence. JAMA 267:1806–1809

    Article  PubMed  CAS  Google Scholar 

  10. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996) Heat rate variability. Standards of measurement, physiological interpretation, and clinical use. Circulation 93:1043–1065

    Article  Google Scholar 

  11. Melo RC, Quitério RJ, Takahashi ACM, Martins LEB, Silva E, Catai AM (2008) High eccentric training reduces the heart rate variability in healthy older men. Br J Sports Med 42(1):59–63

    Article  PubMed  CAS  Google Scholar 

  12. Porta A, Tobaldini E, Guzzetti S, Furlan R, Montano N, Gnecchi-Ruscone T (2007) Assessment of cardiac autonomic modulation during graded head-up tilt by symbolic analysis of heart rate variability. Am J Physiol Heart Circ Physiol 293:H702–H708

    Article  PubMed  CAS  Google Scholar 

  13. Mäkikallio TH, Tapanainen JM, Tulppo MP, Huikuri HV (2002) Clinical applicability of heart rate variability analysis by methods based on nonlinear dynamics. Card Electrophysiol Rev 6:250–255

    Article  PubMed  Google Scholar 

  14. Huikuri HV, Mäkikallio TH, Perkiömäki J (2003) Measurement of heart rate variability by methods based on nonlinear dynamics. J Electrocardiol 36:95–99

    Article  PubMed  Google Scholar 

  15. Huikuri HV, Makikallio TH, Peng CK, Goldberger AL, Hintze U, Moller M (2000) Fractalcorrelation properties of R–R interval dynamics and mortality in patients with depressed left ventricular function after an acute myocardial infarction. Circulation 101:47–53

    PubMed  CAS  Google Scholar 

  16. Maestri R, Pinna GD, Accardo A et al (2007) Nonlinear indices of heart rate variability in chronic heart failure patients: redundancy and comparative clinical value. J Cardiovasc Electrophysiol 18:425–433

    Article  PubMed  Google Scholar 

  17. Mäkikallio TM, Huikuri HV, Hintze U et al (2001) Fractal analysis and time and frequency domain measures of heart rate variability as predictors of mortality in patients with heart failure. Am J Cardiol 87:178–182

    Article  PubMed  Google Scholar 

  18. Maestri R, Pinna GD, Porta A et al (2007) Assessing nonlinear properties of heart rate variability from short-term recordings: are these measurements reliable? Physiol Meas 28:1067–1077

    Article  PubMed  Google Scholar 

  19. Porta A, Baselli G, Liberati D et al (1998) Measuring regularity by means of a corrected conditional entropy in sympathetic outflow. Biol Cybern 78:71–78

    Article  PubMed  CAS  Google Scholar 

  20. Porta A, Baselli G, Guzzetti S, Pagani M, Malliani A, Cerutti S (2000) Prediction of short cardiovascular variability signals based on conditional distribution. IEEE Trans Biomed Eng 47:1555–1564

    Article  PubMed  CAS  Google Scholar 

  21. Guzzetti S, Borroni E, Garbelli PE et al (2005) Symbolic dynamics of heart rate variability aprobe to investigate cardiac autonomic modulation. Circulation 112:465–470

    Article  PubMed  Google Scholar 

  22. Porta A, Gnecchi-Ruscone T, Tobaldini E, Guzzetti S, Furlan R, Montano N (2007) Progressive decrease of heart period variability entropy-based complexity during graded head-uptilt. J Appl Physiol 103:1143–1149

    Article  PubMed  Google Scholar 

  23. Silva E, Catai AM, Trevelin LC et al (1994) Design of a computerized system to evaluate the cardiac function during dynamic exercise (abstract). Phys Med Biol 33:409

    Google Scholar 

  24. Porta A, Guzzetti S, Montano N, Furlan R, Pagani M, Malliani A, Cerutti S (2001) Entropy, entropy rate and pattern classification as tools to typify complexity in short heart periodvariability series. IEEE Trans Biomed Eng 48:1282–1291

    Article  PubMed  CAS  Google Scholar 

  25. Porta A, Di Rienzo M, Wesswl N, Kurths J (2009) Adressing the complexity of cardiovascular regulation. Pjil Trans R Soc A 367:1215–1218

    Article  Google Scholar 

  26. Chaves PHM, Varadhan R, Lipsitz LA et al (2008) Physiological complexity underlying heart rate dynamics and frailty status in community-dwelling older women. J Am Geriatr Soc 56:1698–1703

    Article  PubMed  Google Scholar 

  27. Fried LP, Xue Q, Cappola AR et al (2009) Nonlinear multisystem physiological dysregulation associated with frailty in older women: implications for etiology and treatment. J Gerontol A Biol Sci Med Sci 64(10):1049–1057

    Article  PubMed  Google Scholar 

  28. Lipstiz LA (2004) Physiological complexity, aging, and the path to frailty. Sci Aging Knowl Environ 2004(16):pe16

  29. Fried LP, Tangen CM, Walston J (2001) Frailty in older adults: evidence for a phenotype. J Gerontol Med Sci 56(3):M146–M156

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (06/52860-0 to A.C.M.T. and 05/54838-9 to A.M.C.), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (PDEE/1228/08-0 to A.C.M.T.) and grant number PRIN 2007 to N.M.

Conflict of interest

The authors declare that they have no conflict of interest related to the publication of this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anielle C. M. Takahashi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Takahashi, A.C.M., Porta, A., Melo, R.C. et al. Aging reduces complexity of heart rate variability assessed by conditional entropy and symbolic analysis. Intern Emerg Med 7, 229–235 (2012). https://doi.org/10.1007/s11739-011-0512-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11739-011-0512-z

Keywords

Navigation