Ensemble empirical mode decomposition based feature enhancement of cardio signals

Medical Engineering and Physics

Volumn 35, Issue 8, 2013, Pages 1059-1069

  Janušauskas, Arturas ^a   Marozas, Vaidotas ^a   Lukoševičius, Arunas ^a  

^a KAUNAS UNIVERSITY OF TECHNOLOGY   (Lithuania)

Author keywords

Discrete wavelet transform; ECG; Ensemble empirical mode decomposition; Feature enhancement; Impedance cardiogram

Indexed keywords

BIOLOGICAL SIGNALS; CLINICAL PRACTICES; CLINICAL SITUATIONS; CROSS-CORRELATION COEFFICIENT; ENSEMBLE EMPIRICAL MODE DECOMPOSITION; ESTIMATION ERRORS; FEATURE ENHANCEMENT; NOISE SUPPRESSION;

DISCRETE WAVELET TRANSFORMS; GAUSSIAN NOISE (ELECTRONIC); SIGNAL TO NOISE RATIO;

ELECTROCARDIOGRAPHY;

ARTICLE; ARTIFACT REDUCTION; CONTROLLED STUDY; CORRELATION COEFFICIENT; DISCRETE WAVELET TRANSFORM; ELECTROCARDIOGRAM; ENSEMBLE EMPIRICAL MODE DECOMPOSITION; INTERMETHOD COMPARISON; NOISE REDUCTION; PRIORITY JOURNAL; QRS COMPLEX; SIGNAL DETECTION; SIGNAL NOISE RATIO; SIGNAL PROCESSING; WAVELET ANALYSIS; ALGORITHM; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; ELECTROCARDIOGRAPHY; EVALUATION STUDY; HUMAN; IMPEDANCE CARDIOGRAPHY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; CARDIOGRAPHY, IMPEDANCE; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROCARDIOGRAPHY; HUMANS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84879020550     PISSN: 13504533     EISSN: 18734030     Source Type: Journal    
DOI: 10.1016/j.medengphy.2012.10.007     Document Type: Article

References (33)

1. Gargasas L., JanuŠauskas A., LukoŠevičius A., Vainoras A., Ruseckas R., Korsakas S., et al. Development of methods for monitoring of electrocardiograms, impedance cardiograms and seismocardiograms. Stud Health Technol Inform: Trans Healthcare Inform Technol 2004, 105:131-141.
2. Friesen G.M., Jannet T.C., Jadallah M.A., Yates S.L., Quint R., Nagle H.T. A comparison of the noise sensitivity of nine QRS detection algorithms. IEEE Trans Biomed Eng 1990, 37:85-98.
3. Daskalov I.K., Dotsinsky I.A., Christov I.I. Developments in ECG acquisition preprocessing parameter measurement and recording. IEEE Eng Med Biol 1998, March/April:50-58.
4. Blanco-Velasco M., Weng B., Barner K.E. A new ECG enhancement algorithm for stress ECG tests. Comput Cardiol 2006, 33:917-920.
5. Wu Y., Rangayyan R.M., Zhou Y., Ng S.-C. Filtering electrocardiographic signals using unbiased and normalized adaptive noise reduction system. Med Eng Phys 2009, 31:17-26.
6. Lemay M., Vesin J.M. QRST cancellation based on the empirical mode decomposition. Proc Comput Cardiol 2006, 33:561-564.
7. Chouhan V.S., Mehta S.S. Threshold-based detection of p and t-wave in ECG using new feature signal. IJCSNS Int J Comput Sci Netw Sec 2008, 8(2):144-153.
8. Hu X., Nenov V. A single-lead ECG enhancement algorithm using a regularized data-driven filter. IEEE Trans Biomed Eng 2006, 53(2):347-351.
9. Kaur M., Singh B., Seema Comparisons of different approaches for removal of baseline wander from ECG signal. Proc conf ICWET 2011, 30-36.
10. Rahman M.Z., Shaik R.A., Reddy D.V.R.K. Noise cancelation in ECG signal using computationally simplified adaptive filtering techniques: application to biotelemetry. Signal Proc J (SPIJ) 2009, 3(5):120-131.
11. Chawla M.P.S. A comparative analysis of principal component and independent component techniques for electrocardiograms. Neural Comput Applicat 2009, 18:359-556. 10.1007/s00521-008-0195-1.
12. Romero I. PCA-based noise reduction in ambulatory ECGs. Comput Cardiol 2010, 37:677-680.
13. Eilevstjonn J., Husoy J.K., Eftestol T., Aase A.O., Steen P.A. Multichannel adaptive filtering using an efficient matching pursuit-like algorithm for removal of CPR artifacts in ECG signals. Proc IEEE conf acoustics, speech, and signal processing (ICASSP) 2002, p. IV-3864-7. 10.1109/ICASSP.2002.5745500.
14. Vullings R., Vries B., Bergmans J.W.M. An adaptive Kalman filter for ECG signal enhancement. IEEE Trans Biomed Eng 2011, 58(4):1094-1721.
15. Cao X., Li Z. Denoising of ECG signal based on a comprehensive framework. Conf multimed techn (ICMT) 2010, 10.1109/ICMULT.2010.5631239.
16. Sararu C., State L., Miroiu M. Independent component analysis and complex wavelet decomposition for classifying medical data. Int J Appl Math Inform 2010, 2(4):25-32.
17. Manthalkar R., Ardhapurkas S., Gajre S. Wavelet based ECG denoising by employing Cauchy distribution at subbands. Proc signal processing ICSP 2010, 1718-1721. 10.1109/ICOSP.2010.5656454.
18. Wu Z., Huang N.E. Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv Adapt Data Anal 2009, 1(1):1-41.
19. Tang J., Zou Q., Tang Y., Liu B., Zhang X. Hilbert-Huang transform for ECG de-noising. Proc Bioinform Biomed Eng ICBBE 2007, 2007:664-667.
20. JanuŠauskas A., Marozas V., LukoŠevičius A., Sörnmo L. Detection of hearing loss in audiological frequencies from transient evoked otoacoustic emissions. Informatica 2010, 21(2):191-204.
21. Tang S., Ma H., Su L. Filter principle of Hilbert-Huang transform and its application in time series analysis. Proc 8th international conference on signal processing 2006, 4.
22. Huang N., Shen Z., Long S., Wu M., Shih H., Zheng Q., et al. The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc London 1998, 454:903-995.
23. Kizhner S., Blank K., Flatley P., Huang E.N., Petrick D., Hestnes P. On certain theoretical developments underlying the Hilbert-Huang transform. Proc IEEE aerospace conf 2006, 10.1109/AERO.2006.1656061.
24. Yen J.R., Shieh J.S., Huang N.E. Complementary ensemble empirical mode decomposition: a novel noise enhanced data analysis method. Adv Adapt Data Anal 2010, 2(2):135-156.
25. Tsui P.H., Chang C.C., Chang C.C., Huang N.E., Ho M.C. An adaptive threshold filter for ultrasound signal rejection. Ultrasonic 2009, 49:413-418.
26. Tsui P.H., Chang C.C., Huang N.E. Noise-modulated empirical mode decomposition. Adv Adapt Data Anal 2010, 2(1):25-37.
27. Blanco-Velasco M., Weng B., Barner K.E. A new ECG enhancement algorithm for stress ECG tests. Comput Cardiol 2006, 33:917-920.
28. Narsimha B., Suresh E., Punnamchandar K., Sanjeeva Reddy M. Denoising and QRS detection of ECG signals using empirical mode decomposition. Proc commun sig proc (ICCSP) 2011, 439-442. 10.1109/ICCSP.2011.5739355.
29. Chang K.M., Liu S.H. Gaussian noise filtering from ECG by Wiener filter and ensemble mode decomposition. J Signal Process Syst 2010, 10.1007/s11265-009-0447-z.
30. Chang K.M. Arrhythmia ECG noise reduction by ensemble empirical mode decomposition. Sensors 2010, 10:6063-6080. 10.3390/s100606063.
31. Strang G., Nguyen T. Wavelets and filter banks 1996, Wellesley-Cambridge Press, Wellesley, USA, ISBN-10: 0961408871/ISBN-13: 978-0961408879. 2nd ed.
32. Sabarimalai Manikandan M., Soman K.P. Anovel method for detecting R-peaks in electrocardiogram (ECG)signal. Biomed Signal Process Control 2011, 10.1016/j.bspc.2011.03.004.
33. Agrafioti F., Hatzinakos D. An enhanced EMD algorithm for ECG signal processing. Proc dig sig process (DSP) 2011, 1-6. 10.1109/ICDSP.2011.6004922.