The differential method of phase space matrix for AF/VF discrimination application

Medical Engineering and Physics

Volumn 32, Issue 5, 2010, Pages 444-453

  Liu, Chien Sheng ^a   Tseng, Wei Kung ^b   Lee, Jen Kuang ^c   Hsiao, Tze Chien ^d   Lin, Chii Wann ^a,e  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b I SHOU UNIVERSITY   (Taiwan)

^c NATIONAL TAIWAN UNIVERSITY HOSPITAL   (Taiwan)

^d NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

^e NATIONAL TAIWAN UNIVERSITY   (Taiwan)

Author keywords

Atrial fibrillation; Electrocardiography; Phase space matrix; Real time analysis; Ventricular fibrillation

Indexed keywords

ATRIAL FIBRILLATION; MATRIX; PHASE SPACES; REAL TIME ANALYSIS; VENTRICULAR FIBRILLATION;

ALGORITHMS; ELECTROCARDIOGRAPHY; HEALTH RISKS; MATRIX ALGEBRA; PHASE SPACE METHODS; REAL TIME CONTROL;

COMPUTATION THEORY;

ADULT; ARTICLE; CLASSIFICATION ALGORITHM; CLINICAL ARTICLE; COMPLEX PHASE SPACE DIFFERENCE ALGORITHM; CONTROLLED STUDY; DATA BASE; ELECTROCARDIOGRAPHY; FEMALE; HEART ATRIUM FIBRILLATION; HEART VENTRICLE FIBRILLATION; HUMAN; MALE; NORMAL VALUE; PERFORMANCE MEASUREMENT SYSTEM; PRIORITY JOURNAL; PROCESS OPTIMIZATION; QUANTITATIVE STUDY; RISK ASSESSMENT; SENSITIVITY AND SPECIFICITY; SIGNAL DETECTION; SINUS RHYTHM;

ALGORITHMS; ATRIAL FIBRILLATION; DIAGNOSIS, COMPUTER-ASSISTED; DISCRIMINANT ANALYSIS; ELECTROCARDIOGRAPHY; HUMANS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; VENTRICULAR FIBRILLATION;

EID: 77952880423     PISSN: 13504533     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.medengphy.2010.04.001     Document Type: Article

References (44)

1. Abidi S.S.R. An intelligent tele-healthcare environment offering person-centric and wellness-maintenance services. J Med Syst 2001, 25(3):147-165.
2. Callaway C.W., Sherman L.D., Mosesso V.N., Dietrich J.T.J., Holt E., Clarkson M.C. Scaling exponent predicts defibrillation success for out-of-hospital ventricular fibrillation cardiac arrest. Circulation 2001, 103:1656-1661.
3. Gillberg J. Detection of cardiac tachyarrhythmias in implantable devices. J Electrocardiol 2007, 40:S123-S128.
4. Israel C.W. How to avoid inappropriate therapy. Curr Opin Cardiol 2008, 23:65-71.
5. Husser D., Stridh M., Sörnmo L., Toepffer I., Klein H.U., Olsson S.B., et al. Electroatriography - time-frequency analysis of atrial fibrillation from modified 12-lead ECG configurations for improved diagnosis and therapy. Med Hypotheses 2007, 68:568-573.
6. Karrakchou M., Vibe-Rheymer K., Vesin J.-M., Pruvot E., Kunt M. Improving cardiovascular monitoring through modern techniques. IEEE Eng Med Biol Mag 1996, 15(5):68-78.
7. Malik M., Bigger J.T., Camm A.J., Kleiger R.E., Malliani A., Moss A.J., et al. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Eur Heart J 1996, 17(3):354-381.
8. Thakor N.V., Zhu Y.-S., Pan K.-Y. Ventricular tachycardia and fibrillation detection by a sequential hypothesis testing algorithm. IEEE Trans Biomed Eng 1990, 37(9):837-843.
9. Zhang X.-S., Zhu Y.-S., Thakor N.V., Wang Z.-Z. Detecting ventricular tachycardia and fibrillation by complexity measure. IEEE Trans Biomed Eng 1999, 46(5):548-555.
10. Amann A., Tratnig R., Unterkofler K. Detecting ventricular fibrillation by time-delay methods. IEEE Trans Biomed Eng 2007, 54(1):174-177.
11. Abarbanel H.D.I., Kennel M.B. Local false nearest neighbors and dynamical dimensions from observed chaotic data. Phys Rev E 1993, 47(5):3057-3068.
12. S B, R R, D C, J M. Algorithm sequential decision-making in the frequency domain for life threatening ventricular arrhythmias and imitative artifacts: a diagnostic system. J Biomed Eng 1989;11(4):320-8.
13. Asl B.M., Setarehdan S.K., Mohebbi M. Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal. Artif Intell Med 2008, 44:51-64.
14. Khadra L., Al-Fahoum A.S., Binajjaj S. A quantitative analysis approach for cardiac arrhythmia classification using higher order spectral techniques. IEEE Trans Biomed Eng 2005, 52(11):1840-1845.
15. Wang G., Huang H., Xie H., Wang Z., Hu X. Multifractal analysis of ventricular fibrillation and ventricular tachycardia. Med Eng Phys 2007, 29:375-379.
16. Hong-Wei L., Ying S., Min L., Pi-Ding L., Zheng Z. A probability density function method for detecting atrial fibrillation using R-R intervals. Med Eng Phys 2009, 31:116-123.
17. Acharya U.R., Sankaranarayanan M., Nayak J., Xiang C., Tamura T. Automatic identification of cardiac health using modeling techniques: a comparative study. Inf Sci 2008, 178:4571-4582.
18. Kannathal N., Lim C.M., Acharya U.R., Sadasivan P.K. Cardiac state diagnosis using adaptive neuro-fuzzy technique. Med Eng Phys 2006, 28:809-815.
19. Sarkar S., Ritscher D., Mehra R. A detector for a chronic implantable atrial tachyarrhythmia monitor. IEEE Trans Biomed Eng 2008, 55(3):1219-1224.
20. Lemay M., Prudat Y., Jacquemet V., Vesin J.-M. Phase-rectified signal averaging used to estimate the dominant frequencies in ECG signals during atrial fibrillation. IEEE Trans Biomed Eng 2008, 55(11):2538-2547.
21. Climent A.M., Guillem Mi{dotless}dlS, Husser D., Castells F., Millet J., Bollmann A. Poincaŕe surface profiles of RR intervals: a novel noninvasive method for the evaluation of preferential AV nodal conduction during atrial fibrillation. IEEE Trans Biomed Eng 2009, 56(2):433-442.
22. Amann A., Tratnig R., Unterkofler K. Reliability of old and new ventricular fibrillation detection algorithms for automated external defibrillators. Biomed Eng OnLine 2005, 4(60):15.
23. Übeyli E.D. Statistics over features of ECG signals. Expert Syst Appl 2009, 36:8758-8767.
24. Übeyli E.D. Adaptive neuro-fuzzy inference system for classification of ECG signals using Lyapunov exponents. Comput Meth Programs Biomed 2009, 93:313-321.
25. Übeyli E.D. Implementing wavelet transform/mixture of experts network for analysis of electrocardiogram beats. Expert Syst 2008, 25(2):150-162.
26. Takens F. Detecting strange attractors in turbulence. In: Lecture notes in mathematics. Springer Berlin/Heidelberg, 1981, 10.1007/BFb0091903.
27. Richter M., Schreiber T. Phase space embedding of electrocardiograms. Phys Rev E 1998, 58(5):6392-6399.
28. Cvikl M., Jager F., Zemva A. Hardware implementation of a modified delay-coordinate mapping-based QRS complex detection algorithm. EURASIP J Adv Signal Process 2007, 2007(1):104.
29. Ravelli F., Antolini R. Complex dynamics underlying the human electrocardiogram. Biol Cybern 1992, 67:57-65.
30. Fojt O., Holcik J. Applying nonlinear dynamics to ECG signal processing. IEEE Eng Med Biol 1998, 17:96-101.
31. Massachusetts Institute of Technology. MIT-BIH arrhythmia database [Online]. Available: http://www.physionet.org/physiobank/database/mitdb.
32. Goldberger A.L., Amaral L.A.N., Glass L., Hausdorff J.M., Ivanov PCh, Mark R.G., et al. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 2000, 101(23):e215-e220.
33. Massachusetts Institute of Technology. CU database [Online]. Available: http://www.physionet.org/physiobank/database/cudb.
34. Nolle F.M., Badura F.K., Catlett J.M., Bowser R.W., Sketch M.H. CREI-GARD, a new concept in computerized arrhythmia monitoring systems. Comput Cardiol 1986, 13:515-518.
35. Massachusetts Institute of Technology. SCDH database [Online]. http://www.physionet.org/pn3/sddb.
36. Porta A., Rienzo M.D., Wessel N., Kurths J. Addressing the complexity of cardiovascular regulation. Philos Trans R Soc A: Math Phys Eng Sci 2009, 367:1215-1218.
37. Hegger R., Kantz H. Improved false nearest neighbor method to detect determinism in time series data. Phys Rev E 1999, 60(4):4970-4973.
38. Rhodes C., Morari M. False-nearest-neighbors algorithm and noise-corrupted time series. Phys Rev E 1997, 55(5):6162-6170.
39. Fraser A.M., Swinney H.L. Independent coordinates for strange attractors from mutual information. Phys Rev A 1986, 33:1134-1140.
40. Sörnmo L. Time-varying digital filtering of ECG baseline wander. Med Biol Eng Comput 1993, 51(5):503-508.
41. Wu Y., Rangayyan R.M., Zhou Y., Ng S.-C. Filtering electrocardiographic signals using an unbiased and normalized adaptive noise reduction system. Med Eng Phys 2009, 31:17-26.
42. Blanco-Velascoa M., Wengb B., Barner K.E. ECG signal denoising and baseline wander correction based on the empirical mode decomposition. Comput Biol Med 2008, 38:1-13.
43. Sayadi O., Shamsollahi M.B. Model-based fiducial points extraction for baseline wandered electrocardiograms. IEEE Trans Biomed Eng 2008, 55(1):347-351.
44. Liu CS, Lin YC, Chuang YH, Hsiao TC, Lin CW. Chaotic Phase Space Difference (CPSD) algorithm for real-time detection of VF, VT and PVC ECG signals. In: 4th European conference of the international federation for medical and biological engineering. Springer Berlin/Heidelberg; 2009, 10.1007/978-3-540r-r89208-3.