PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
Tytuł artykułu

The use of recurrence plots and beat recordings in chronic heart failure detection

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Chronic heart failure is a syndrome consisting in clinical symptoms that arise as a result of complications of many disease entities. According to the definition it is a condition in which, as a consequence of permanent heart dysfunction, cardiac output is reduced in relation to tissues’ metabolic demand. This results in subjective symptoms or proper cardiac output is sustained over higher filling pressure of the left heart ventricle. The occurrence of disease among adults in Europe and North America is 0.4-2%. Heart dysfunction detected by echocardiography appears with the frequency of 3%, and in people over 60 years of age it doubles with each decade of life, reaching 10% after 80 years of age. The aim of the study is to make an acquisition of fremitus in apex beat place and quantitative evaluation of some of their features which are correlated with the advanced syndrome. We have built the apparatus for the heart signal recording and proposed the original method of its analysis based on the theory of chaos and recurrence plots. It gave us, on the group of 85 patients, sensitivity equal to 0.896 specificity equal to 0.676 and the accuracy of diagnostics of the chronic heart failure equal up to 80%.
Rocznik
Strony
339--345
Opis fizyczny
Bibliogr. 24 poz., fot., rys., wykr.
Twórcy
  • Faculty of Mechatronics, Department of Metrology and Biomedical Engineering, Warsaw University of Technology, 8 A. Boboli St., 02‒525 Warsaw, Poland
autor
  • Faculty of Mechatronics, Department of Metrology and Biomedical Engineering, Warsaw University of Technology, 8 A. Boboli St., 02‒525 Warsaw, Poland
autor
  • EMC St.Anne’s Hospital in Piaseczno, Internal Medicine Department, 39 A. Mickiewicza St., 05-500 Piaseczno, Poland
Bibliografia
  • [1] ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure 2012, European Heart Journal, doi:10.1093/ eurheartk/ehs104.
  • [2] B.P. Griffin, E.J. Topol, G. Opolski and T. Pasierski, Cardiology Handbook Cleveland Clinic, Medipage, 2006.
  • [3] M. Jamroży, K. Lewenstein and T. Leyko, “Early detection of Cardiac Insufficienty”, Recent Advances in Mechatronics, 407-412 (2009).
  • [4] M. Jamroży and K. Lewenstein, “Apparatus System for Detection of Cardiac Insufficiency”., Mechatronics Recent Technological and Scientific Advances, 663-672 (2011).
  • [5] F. Censi, G. Calcagnini and S. Cerutti, “Proposed corrections for the quantification of coupling patterns by recurrence plots.”, IEEE Trans Biomed Eng. 2004. May;51 (5):856‒859.
  • [6] J.C. Sprott, Chaos and time-series analysis, OXFORD University Press, 2003.
  • [7] G.H. Schuster, Deterministic chaos: introduction, Wydawnictwo Naukowe PWN, Warszawa 1995.
  • [8] H.D.I. Abarbanel, Analysis of observed chaotic data, Institute for Nonlinear Science, Springer 1996.
  • [9] R. Maestri, G.D. Pianna, A. Accardo and P. Allegrini, “Nonlinear Indices of Heart Rate Variability in Chronic Heart Failure Patients: Redundancy and Comparative Clinical Value” J Cardiocasc Electrophysiol Vol. 18, 425-433, (2007).
  • [10] G.D. Addio, M. Cesarelli, M. Romano and G. Cobri, R. Maestri, “Correlation between Fractal Behavior of HRV and Neurohormonal and Functional Idexes in Chronic Heart Failire” MEDICON 2010, IFMBE Proceedings 29, 53-56, 2010.
  • [11] H. Kantz and T. Schreiber, Nonlinear time series analysis, Cambridge University Press, 1997.
  • [12] R. Prado and M. West., Time series: modeling, computation, and inference, CRC Press, 2010.
  • [13] Y. Peng, Z. Sun, “Characterization of QT and RR interval series during acute myocardial ischemia by means of recurrence quantification analysis.”, Med Biol Eng Comput. 2011 Jan;49 (1):25‒31.
  • [14] K. Klimaszewska and J.J. Zebrowski, “Detection of the type of intermittency using characteristic patterns in recurrence plots.”, Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Aug;80 (2 Pt 2):026214.
  • [15] K.C. Chua, V. Chandran, U.R. Acharya, C.M. Lim, “Computerbased analysis of cardiac state using entropies, recurrence plots and Poincare geometry”, J Med Eng Technol. 2008, Jul-Aug;32 (4):263‒72.
  • [16] http://www.recurrence-plot.tk/
  • [17] A. Arcentales, B.F. Giraldo, P. Caminal and S. Benito, A Voss, “Recurrence quantification analysis of heart rate variability and respiratory flow series in patients on weaning trials”, Conf Proc IEEE Eng Med Biol Soc. 2011:2724‒7.
  • [18] C.D. Nguyen, S.J. Wilson and S. Crozier, “Automated quantification of the synchrogram by recurrenceplot analysis”, IEEE Trans Biomed Eng. 2012, Apr;59 (4):946‒55.
  • [19] M. Mohebbi, H. Ghassemian and B. Mohammadzadeh, “Structures of the Recurrence Plot of Heart Rate Variability Signal as a Tool for Predicting the Onset of Paroxysmal Atrial Fibrillation”, J Med Signals Sens. May-Aug; 1 (2): 113-121 (2011).
  • [20] K. Lewenstein, Artificial neural networks in the diagnostics of coronary artery diseases based on ECG exercise tests, Oficyna Wydaw. PW, Warsaw 2002.
  • [21] M. Jamrozy, K. Lewenstein and T. Leyko, “Automatic analysis of recurrence plot for the needs of the analysis of infrasonic signals from the human heart”, Mechatronics 2013 - Recent Technological and Scientific Advances, Springer 2013.
  • [22] G.D. Altman and J.M. Bland, “Measurement in medicine: the analysis of method comparison studies”, The Statistician 32: 307-317, 1983.
  • [23] R. Tadeusiewicz and M. Ogiela, “Structural approach to medical image understanding”, Bull. Pol. Ac.: Tech. 52 (2), 131-139 (2004).
  • [24] M. Tycler, M. Turzowa et al., “Use of body surface maps for model based assessment of local pathological changes on the heart”, Bull. Pol. Ac.: Tech. 53 (3), 207-215 (2005).
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-96157e4d-6900-4532-b008-0a5a09662b78
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.