Skip to content


  • Research Article
  • Open Access

Diurnal Changes of Heart Rate and Sympathovagal Activity for Temporal Patterns of Transient Ischemic Episodes in 24-Hour Electrocardiograms

EURASIP Journal on Advances in Signal Processing20072007:032386

  • Received: 26 April 2006
  • Accepted: 11 January 2007
  • Published:


We test the hypothesis that different temporal patterns of transient ST segment changes compatible with ischemia (ischemic episodes) are a result of different physiologic mechanisms responsible for ischemia. We tested the hypothesis using records of the Long-Term ST Database. Each record was divided into three intervals of records: morning, day, and night intervals; and was inserted into one of three sets according to the temporal pattern of ischemia: salvo, periodic, and sporadic pattern. We derived time- and frequency-domain parameters of the heart rate time series in selected intervals in the neighborhood of ischemic episodes. We used the adaptive autoregressive method with a recursive least-square algorithm for consistent spectral tracking of heart rate time series and to study frequency-domain sympathovagal behavior during ischemia. The results support the hypothesis that there are at least two distinct populations, which differ according to mechanisms and temporal patterns of ischemia.


  • Ischemia
  • Temporal Pattern
  • Physiologic Mechanism
  • Distinct Population
  • Diurnal Change


Authors’ Affiliations

Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, 1000, Slovenia


  1. Andrews TC, Stone PH: Recent developments in the understanding and management of angina pectoris in patients with stable coronary artery disease. Current Opinion in Cardiology 1991,6(4):503-510. 10.1097/00001573-199108000-00004View ArticleGoogle Scholar
  2. Quyyumi AA: Current concepts of pathophysiology, circadian patterns, and vasoreactive factors associated with myocardial ischemia detected by ambulatory electrocardiography. Cardiology Clinics 1992,10(3):403-415.Google Scholar
  3. Jager F, Moody GB, Mark RG: Characterization of transient ischemic and non-ischemic ST segment changes. Proceedings of 22th Annual Meeting on Computers in Cardiology, September 1995, Vienna, Austria 721-724.Google Scholar
  4. Taddei A, Distante G, Emdin M, et al.: The European ST-T database: standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography. European Heart Journal 1992,13(9):1164-1172.Google Scholar
  5. Jager F, Moody GB, Antolič G, Mašič D, Mark RG: Sympatho-vagal correlates of transient ischemia in ambulatory patients. Proceedings of 24th Annual Meeting on Computers in Cardiology, September 1997, Lund, Sweden 387-390.Google Scholar
  6. Jager F, Taddei A, Moody GB, et al.: Long-term ST database: a reference for the development and evaluation of automated ischaemia detectors and for the study of the dynamics of myocardial ischaemia. Medical and Biological Engineering and Computing 2003,41(2):172-182. 10.1007/BF02344885View ArticleGoogle Scholar
  7. Smrdel A, Jager F: Diurnal changes of heart rate and sympatho-vagal activity for temporal patterns of transient ischemia. Proceedings of 32th Annual Meeting on Computers in Cardiology, September 2005, Lyon, France 857-860.Google Scholar
  8. Bianchi AM, Mainardi L, Petrucci E, Signorini MG, Mainardi M, Cerutti S: Time-variant power spectrum analysis for the detection of transient episodes in HRV signal. IEEE Transactions on Biomedical Engineering 1993,40(2):136-144. 10.1109/10.212067View ArticleGoogle Scholar
  9. Akay M: Biomedical Signal Processing. Academic Press, San Diego, Calif, USA; 1994.Google Scholar
  10. Bluman AG: Elementary Statistics: A Brief Version. 3rd edition. MacGraw-Hill, New York, NY, USA; 2006.Google Scholar
  11. Press WH, Teukolsky SA, Vetterling WT, Flannery BP: Numerical Recipes in C++, the Art of Scientific Computing. 2nd edition. Cambridge University Press, Cambridge, Mass, USA; 2002.MATHGoogle Scholar
  12. Gamero LG, Vila J, Palacios F: Wavelet transform analysis of heart rate variability during mycardial ischaemia. Medical and Biological Engineering and Computing 2002,40(1):72-78. 10.1007/BF02347698View ArticleGoogle Scholar
  13. Parker JD, Testa MA, Jimenez AH, et al.: Morning increase in ambulatory ischemia in patients with stable coronary artery disease: importance of physical activity and increased cardiac demand. Circulation 1994,89(2):604-614.View ArticleGoogle Scholar
  14. van Boven AJ, Brouwer J, Crijns HJGM, Haaksma J, Lie KI: Differential autonomic mechanisms underlying early morning and daytime transient myocardial ischaemia in patients with stable coronary artery disease. British Heart Journal 1995,73(2):134-138. 10.1136/hrt.73.2.134View ArticleGoogle Scholar
  15. Quyyumi AA, Panza JA, Diodati JG, Lakatos E, Epstein SE: Circadian variation in ischemic threshold: a mechanism underlying the circadian variation in ischemic events. Circulation 1992,86(1):22-28.View ArticleGoogle Scholar
  16. Goseki Y, Matsubara T, Takahashi N, Takeuchi T, Ibukiyama C: Heart rate variability before the occurrence of silent myocardial ischemia during ambulatory monitoring. American Journal of Cardiology 1994,73(12):845-849. 10.1016/0002-9149(94)90807-9View ArticleGoogle Scholar
  17. Cerutti S, Bianchi AM, Mainardi LT: Advanced spectral methods for detecting dynamic behaviour. Autonomic Neuroscience: Basic and Clinical 2001,90(1-2):3-12. 10.1016/S1566-0702(01)00261-2View ArticleGoogle Scholar
  18. Kop WJ, Verdino RJ, Gottdiener JS, O'Leary ST, Bairey Merz CN, Krantz DS: Changes in heart rate and heart rate variability before ambulatory ischemic events. Journal of the American College of Cardiology 2001,38(3):742-749. 10.1016/S0735-1097(01)01451-6View ArticleGoogle Scholar
  19. Bertolet BD, Pepine CJ: The vascular endothelium as a key to understanding coronary spasm and syndrome X. Current Opinion in Cardiology 1991,6(4):496-502. 10.1097/00001573-199108000-00003View ArticleGoogle Scholar


© A. Smrdel and F. Jager 2007