Monitoring in cardiovascular disease patients by nonlinear biomedical signal processing

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2011, Pages 6564-6567

  Voss, A ^a   Schulz, S ^a   Schroeder, R ^a  

^a UNIVERSITY OF APPLIED SCIENCES JENA   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATION FIELDS; BIOMEDICAL SIGNAL PROCESSING; BIOSIGNALS; CARDIO-VASCULAR DISEASE; CARDIOVASCULAR MONITORING; ESSENTIAL COMPONENT; NON-LINEAR DYNAMICS; VITAL SIGN;

BLOOD PRESSURE;

SIGNAL PROCESSING;

ACUTE DISEASE; AMBULATORY MONITORING; ARTICLE; BLOOD PRESSURE; CARDIOVASCULAR DISEASE; CARDIOVASCULAR SYSTEM; CORONARY ARTERY DISEASE; DISEASE COURSE; ELECTROCARDIOGRAPHY; HEART ARRHYTHMIA; HEART FAILURE; HEART INFARCTION; HEART RATE; HUMAN; INTENSIVE CARE; METHODOLOGY; NONLINEAR SYSTEM; PATHOLOGY; SIGNAL PROCESSING;

ACUTE DISEASE; ARRHYTHMIAS, CARDIAC; BLOOD PRESSURE; CARDIOVASCULAR DISEASES; CARDIOVASCULAR SYSTEM; CORONARY DISEASE; DISEASE PROGRESSION; ELECTROCARDIOGRAPHY; HEART FAILURE; HEART RATE; HUMANS; INTENSIVE CARE; MONITORING, AMBULATORY; MYOCARDIAL INFARCTION; NONLINEAR DYNAMICS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84055191691     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2011.6091619     Document Type: Conference Paper

References (26)

1. J. J. Coleman, R. E. Ferner, and S. J. Evans, "Monitoring for adverse drug reactions," Br J Clin Pharmacol, vol. 61, no. 4, pp. 371-8, Apr, 2006.
2. A. Voss, S. Schulz, R. Schroeder et al., "Methods derived from nonlinear dynamics for analysing heart rate variability," Philos Transact A Math Phys Eng Sci, vol. 367, no. 1887, pp. 277-96, Jan 28, 2009.
3. H. V. Huikuri, T. Makikallio, K. E. Airaksinen et al., "Measurement of heart rate variability: a clinical tool or a research toy?," J Am Coll Cardiol, vol. 34, no. 7, pp. 1878-83, Dec, 1999.
4. G. D. Clifford, W. J. Long, G. B. Moody et al., "Robust parameter extraction for decision support using multimodal intensive care data," Philos Transact A Math Phys Eng Sci, vol. 367, no. 1887, pp. 411-29, Jan 28, 2009.
5. T. H. Makikallio, S. Hoiber, L. Kober et al., "Fractal analysis of heart rate dynamics as a predictor of mortality in patients with depressed left ventricular function after acute myocardial infarction. TRACE Investigators. TRAndolapril Cardiac Evaluation," Am J Cardiol, vol. 83, no. 6, pp. 836-9, Mar 15, 1999.
6. H. V. Huikuri, T. H. Makikallio, C. K. Peng et al., "Fractal correlation properties of R-R interval dynamics and mortality in patients with depressed left ventricular function after an acute myocardial infarction," Circulation, vol. 101, no. 1, pp. 47-53, Jan 4-11, 2000.
7. J. M. Tapanainen, P. E. Thomsen, L. Kober et al., "Fractal analysis of heart rate variability and mortality after an acute myocardial infarction," Am J Cardiol, vol. 90, no. 4, pp. 347-52, Aug 15, 2002.
8. P. K. Stein, P. P. Domitrovich, H. V. Huikuri et al., "Traditional and nonlinear heart rate variability are each independently associated with mortality after myocardial infarction," J Cardiovasc Electrophysiol, vol. 16, no. 1, pp. 13-20, Jan, 2005.
9. A. Voss, K. Hnatkova, N. Wessel et al., "Multiparametric analysis of heart rate variability used for risk stratification among survivors of acute myocardial infarction," Pacing Clin Electrophysiol, vol. 21, no. 1 Pt 2, pp. 186-92, Jan, 1998.
10. P. K. Stein, R. E. Schmieg, Jr., A. El-Fouly et al., "Association between heart rate variability recorded on postoperative day 1 and length of stay in abdominal aortic surgery patients," Crit Care Med, vol. 29, no. 9, pp. 1738-43, Sep, 2001.
11. Z. K. Wu, S. Vikman, J. Laurikka et al., "Nonlinear heart rate variability in CABG patients and the preconditioning effect," Eur J Cardiothorac Surg, vol. 28, no. 1, pp. 109-13, Jul, 2005.
12. T. T. Laitio, H. V. Huikuri, E. S. Kentala et al., "Correlation properties and complexity of perioperative RR-interval dynamics in coronary artery bypass surgery patients," Anesthesiology, vol. 93, no. 1, pp. 69-80, Jul, 2000.
13. V. E. Papaioannou, N. Maglaveras, I. Houvarda et al., "Investigation of altered heart rate variability, nonlinear properties of heart rate signals, and organ dysfunction longitudinally over time in intensive care unit patients," J Crit Care, vol. 21, no. 1, pp. 95-103; discussion 103-4, Mar, 2006.
14. P. R. Norris, S. M. Anderson, J. M. Jenkins et al., "Heart rate multiscale entropy at three hours predicts hospital mortality in 3,154 trauma patients," Shock, vol. 30, no. 1, pp. 17-22, Jul, 2008.
15. P. Caminal, B. F. Giraldo, M. Vallverdu et al., "Symbolic dynamic analysis of relations between cardiac and breathing cycles in patients on weaning trials," Ann Biomed Eng, vol. 38, no. 8, pp. 2542-52, Aug.
16. R. Pfeifer, J. Hopfe, C. Ehrhardt et al., "Autonomic regulation during mild therapeutic hypothermia in cardiopulmonary resuscitated patients," Clin Res Cardiol, 2011 (in press), EPUB 2011/04/09.
17. J. E. Skinner, C. M. Pratt, and T. Vybiral, "A reduction in the correlation dimension of heartbeat intervals precedes imminent ventricular fibrillation in human subjects," Am Heart J, vol. 125, no. 3, pp. 731-43, Mar, 1993.
18. F. Lombardi, A. Porta, M. Marzegalli et al., "Heart rate variability patterns before ventricular tachycardia onset in patients with an implantable cardioverter defibrillator. Participating Investigators of ICD-HRV Italian Study Group," Am J Cardiol, vol. 86, no. 9, pp. 959-63, Nov 1, 2000.
19. N. Wessel, C. Ziehmann, J. Kurths et al., "Short-term forecasting of life-threatening cardiac arrhythmias based on symbolic dynamics and finite-time growth rates," Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics, vol. 61, no. 1, pp. 733-9, Jan, 2000.
20. M. Baumert, V. Baier, J. Haueisen et al., "Forecasting of lifethreatening arrhythmias using the compression entropy of heart rate," Methods Inf Med, vol. 43, no. 2, pp. 202-6, 2004.
21. O. Sayadi, and M. B. Shamsollahi, "Life-Threatening Arrhythmia Verification in ICU Patients Using the Joint Cardiovascular Dynamical Model and a Bayesian Filter," IEEE Trans Biomed Eng, Feb 14.
22. D. G. Shin, C. S. Yoo, S. H. Yi et al., "Prediction of paroxysmal atrial fibrillation using nonlinear analysis of the R-R interval dynamics before the spontaneous onset of atrial fibrillation," Circ J, vol. 70, no. 1, pp. 94-9, Jan, 2006.
23. S. Sovilj, A. Van Oosterom, G. Rajsman et al., "ECG-based prediction of atrial fibrillation development following coronary artery bypass grafting," Physiol Meas, vol. 31, no. 5, pp. 663-77, May.
24. A. W. Schoenenberger, P. Erne, S. Ammann et al., "Prediction of hypertensive crisis based on average, variability and approximate entropy of 24-h ambulatory blood pressure monitoring," J Hum Hypertens, vol. 22, no. 1, pp. 32-7, Jan, 2008.
25. R. Goya-Esteban, I. Mora-Jimenez, J. L. Rojo-Alvarez et al., "Heart rate variability on 7-day Holter monitoring using a bootstrap rhythmometric procedure," IEEE Trans Biomed Eng, vol. 57, no. 6, pp. 1366-76, Jun.
26. B. Retzlaff, R. Bauernschmitt, H. Malberg et al., "Depression of cardiovascular autonomic function is more pronounced after mitral valve surgery: evidence for direct trauma," Philos Transact A Math Phys Eng Sci, vol. 367, no. 1892, pp. 1251-63, Apr 13, 2009.