Assessment of the classification capability of prediction and approximation methods for HRV analysis

Computers in Biology and Medicine

Volumn 37, Issue 5, 2007, Pages 642-654

  Manis, George ^a   Nikolopoulos, Stavros ^b   Alexandridi, Anastasia ^c   Davos, Constantinos ^c  

^a UNIVERSITY OF IOANNINA   (Greece)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^c BIOMEDICAL RESEARCH FOUNDATION   (Greece)

Author keywords

Approximation; Cardiogram classification; ECG; Heart rate variability; Mean error; Prediction

Indexed keywords

BIOELECTRIC POTENTIALS; ELECTROCARDIOGRAPHY; LEAST SQUARES APPROXIMATIONS; MEDICAL COMPUTING; NEURAL NETWORKS; PATIENT MONITORING; WAVELET TRANSFORMS;

APPROXIMATION METHODS; CARDIOGRAM CLASSIFICATION; HEART RATE VARIABILITY (HRV); MEAN ERROR;

CARDIOVASCULAR SYSTEM;

ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; FEMALE; HEART RATE VARIABILITY; HUMAN; MALE; MATHEMATICAL COMPUTING; NORMAL HUMAN; PREDICTION; PRIORITY JOURNAL; WAVEFORM;

ADULT; AGE FACTORS; AGED; CORONARY DISEASE; ELECTROCARDIOGRAPHY; ELECTROCARDIOGRAPHY, AMBULATORY; FEMALE; FORECASTING; FOURIER ANALYSIS; HEART FAILURE, CONGESTIVE; HEART RATE; HUMANS; LEAST-SQUARES ANALYSIS; LINEAR MODELS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); TIME FACTORS;

EID: 33947125598     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2006.06.008     Document Type: Article

References (38)

1. M.C. Teich, S.B. Lowen, B.M. Jost, K. Vibe-Rheymer, C. Heneghan, in: M. Akay (Ed.), Heart-Rate Variability: Measures and Models, Nonlinear Biomedical Signal Processing, vol. II, IEEE Press, New York, 2001, pp. 159-213 (Chapter 6).
2. Task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, Heart rate variability: standards of measurement, physiological interpretation, and clinical use, Circulation 93 (1996) 1043-1065.
3. Nikolopoulos S., Alexandridi A., Nikolakeas S., and Manis G. Experimental analysis of heart rate variability of long-recording electrocardiograms in normal subjects and coronary patients. J. Biomed. Inform. 36 3 (2003) 202-217
4. Makikallio T.H., Tapanainen J.M., Tulppo M.P., and Huikuri H.V. Clinical applicability of heart rate variability analysis by methods based on nonlinear dynamics. Card Electrophysiol. Rev. 6 3 (2002) 250-255
5. Goldberger A.L. Non-linear dynamics for clinicians: chaos theory, fractals, and complexity at the bedside. Lancet 11 (1996) 1312-1314
6. Pumprla J., Howorka K., Groves D., Chester M., and Nolan J. Functional assessment of heart rate variability: physiological basis and practical applications. Int. J. Cardiol. 84 (2002) 1-14
7. Eckberg D.L. Sympathovagal balance. A critical appraisal. Circulation 96 9 (1997) 3224-3232
8. Nabors-Oberg R.E., Niaura R.S., Sollers III J.J., and Thayer J.F. The effects of controlled smoking on heart period variability. IEEE Eng. Med. Biol. 21 4 (2002) 65-70
9. Nolan J., Batin P.D., Andrews R., Lindsay S.J., and Brooksby P. Prospective study of heart rate variability and mortality in chronic heart failure: results of the United Kingdom heart failure evaluation and assessment of risk trial (UK-HEART). Circulation 98 15 (1998) 1510-1516
10. Kleiger R.E., and Miller J.P. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am. J. Cardiol. 59 (1978) 256-262
11. Binder T., Frey B., Porenta G., Heinz G., Wutte M., Kreiner G., Grossinger H., Scmidinger H., Pacher R., and Weber H. Prognostic value of heart rate variability in patients awaiting cardiac transplantation. PACE 15 (1992) 2215-2220
12. Sugihara G., Allan W., Sobel D., and Allan K.D. Nonlinear control of heart rate variability in human infants. Proc. Natl. Acad. Sci. USA 93 6 (1996) 2608-2613
13. Hastings H.M., Evans S.J., Quan W., Chong M.L., and Nwasokwa O. Nonlinear dynamics in ventricular fibrillation. Proc. Natl. Acad. Sci. USA 93 19 (1996) 10495-10499
14. Fortrat J.O., Yamamoto Y., and Hughson R.L. Respiratory influences on non-linear dynamics of heart rate variability in humans. Biol. Cybernet. 77 1 (1997) 1-10
15. Porta A., Baselli G., Guzzetti S., Pagani M., Malliani A., and Cerutti S. Prediction of short cardiovascular variability signals based on conditional distribution. IEEE Trans. Biomed. Eng. 47 12 (2000) 1555-1564
16. McCarty R., Atkinson A., Tiller W.A., Rein G., and Watkins A.D. The effects of emotions on short-term power spectrum analysis of heart rate variability. Am. J. Cardiol. 76 14 (1995) 1089-1093
17. Mateo J., and Laguna P. Improved heart rate variability signal analysis from the beat occurrence times according to the IPMF model. IEEE Trans. Biomed. Eng. 47 8 (2000) 985-996
18. Sosnowski M., MacFarlane P.W., Zbignew C., Skrzypek-Wanha J., Boczkowska-Gaik E., and Tendera M. Age-adjustment of HRV measures and its prognostic value for risk assessment in patients late after myocardial infarction. Int. J. Cardiol. 86 (2002) 258-294
19. Alexandridi A., and Manis G. Hardware design for the computation of heart rate variability. J. Med. Eng. Tech. 26 (2002) 49-62
20. Friedman B.H., Allen M.T., Christie C.I., and Santucci A.K. Validity concerns of common heart-rate variability indices. IEEE Eng. Med. Biol. 21 4 (2002) 35-40
21. R. Kozma, N.K. Kasabov, J.A. Swope, M.J.A. Williams, Combining neuro-fuzzy and chaos methods for intelligent time series analysis-case study of heart rate variability, in: Proceeding of the IEEE International Conference on Systems, Man and Cybernetics, Orlando, FL, USA, vol. 4, 1997, pp. 3025-3029.
22. J. Swope, N. Kasabov, M. Williams, Neuro-fuzzy modelling of heart rate signals and applications to diagnostics, Fuzzy Systems in Medicine, Physica-Verlag, Wurzburg, 2000, pp. 519-542.
23. Sayers B. Analysis of heart rate variability. Ergonomics 16 (1973) 17-32
24. Chess G.F., Tam R.M., and Calarescu F.R. Influence of cardiac neural inputs on rhythmic variations of heart period in the cat. Amer. J. Physiol. 128 (1975) 775-789
25. Akselrod S., Gordon D., Ubel F.A., Shannon D.C., Barger A.C., and Cohen R.J. Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat to beat cardiovascular control. Science 213 (1981) 220-222
26. Grassberger P., and Procaccia I. Characterization of strange attractors. Phys. Rev. Lett. 50 (1983) 346-349
27. F. Takens, Detecting strange attractors in turbulence, Dynamical Systems and Turbulence, Springer, Warwick, 1980, pp. 66-381.
28. S.M. Pincus, Approximate entropy: a complexity measure for biologic time series data, in: Proceedings of the IEEE 17th Annual Northeast Bioengineering Conference, IEEE Press, New York, 1991, pp. 35-36.
29. G. Manis, A. Alexandridi, S. Nikolopoulos, Diagnosis of cardiac pathology through prediction and approximation methods, in: Proceedings of the International Symposium on Signal Processing and its Applications, Paris, France, 2003.
30. A. Alexandridi, C.D. Stylios, G. Manis, Neural networks and fuzzy logic approximation and prediction for HRV analysis, European Symposium on Intelligent Technologies, Hybrid Systems and their Implementation on Smart Adaptive Systems, Finland, 2003.
31. G. Manis, S. Nikolopoulos, A. Alexandridi, Prediction techniques and HRV analysis, MEDICON, Naples, Italy, 2004.
32. PhysioBank: Physiologic signal archives for biomedical research, 〈http://www.physionet.org〉.
33. Iyengar N., Peng C.-K., Morin R., Goldberger A.L., and Lipsitz L.A. Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics. Am. J. Physiol. 271 (1996) 1078-1084
34. Wolpert D.M., and Miall R.C. Detecting chaos with neural networks. Proc. R. Soc. Lond. B 242 (1990) 82-86
35. Sugihara G., and May R. Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Nature 344 (1990) 734-741
36. Peng C.-K., Buldyrev S.V., Havlin S., Simons M., Stanley H.E., and Goldberger A.L. On the mosaic organization of DNA sequences. Phys. Rev. E 49 (1994) 1685-1689
37. Baim D.S., Colucci W.S., Monrad E.S., Smith H.S., Wright R.F., Lanoue A., Gauthier D.F., Ransil B.J., Grossman W., and Braunwald E. Survival of patients with severe congestive heart failure treated with oral milrinone. J. Am. College Cardiol. 7 3 (1986) 661-670
38. M.C.Teich, Multiresolution wavelet analysis of heart-rate variability for heart-failure and heart-transplant patients, in: Proceedings of the International Conference of the IEEE Society of Engineering in Medicine and Biology, vol. 20, 1998, pp. 1136-1141.