Automatic motion and noise artifact detection in holter ECG data using empirical mode decomposition and statistical approaches

IEEE Transactions on Biomedical Engineering

Volumn 59, Issue 6, 2012, Pages 1499-1506

  Lee, Jinseok ^a   McManus, David D ^b   Merchant, Sneh ^c   Chon, Ki H ^a  

^a Worcester Polytechnic Institute   (United States)

^b UNIVERSITY OF MASSACHUSETTS MEDICAL SCHOOL   (United States)

^c Scottcare Corporation   (United States)

Author keywords

Atrial fibrillation (AF); empirical mode decomposition (EMD); Holter recording; motion and noise (MN) artifact detection; statistical method

Indexed keywords

ARTIFACT DETECTION; ATRIAL FIBRILLATION; COMPUTATION TIME; DATA SEGMENT; ECG SIGNALS; EMPIRICAL MODE DECOMPOSITION; FIRST-ORDER; HEALTHY SUBJECTS; HIGHER FREQUENCIES; HOLTER ECG; HOLTER RECORDINGS; INTRINSIC MODE FUNCTIONS; MATLAB CODE; NOISE ARTIFACTS; REAL-TIME APPLICATION; SENSITIVITY AND SPECIFICITY; SHANNON ENTROPY; STATISTICAL APPROACH; STATISTICAL MEASURES; TRAINING DATA SETS;

ALGORITHMS; DISEASES; ELECTROCARDIOGRAPHY; STATISTICAL METHODS;

SIGNAL PROCESSING;

ARTICLE; ARTIFACT; ARTIFACT REDUCTION; CLASSIFICATION ALGORITHM; CLINICAL ARTICLE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; ENTROPY; FEMALE; HEART ATRIUM FIBRILLATION; HOLTER MONITORING; HUMAN; INTERMETHOD COMPARISON; MALE; MONITOR; MOTION; NOISE; NORMAL HUMAN; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SIGNAL NOISE RATIO; STATISTICAL ANALYSIS;

ALGORITHMS; ARTIFACTS; ATRIAL FIBRILLATION; COMPUTER SYSTEMS; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROCARDIOGRAPHY, AMBULATORY; HUMANS; MOTION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL-TO-NOISE RATIO;

EID: 84861371437     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2011.2175729     Document Type: Article

References (34)

1. S. Dash, K. H. Chon, S. Lu, and E. A. Raeder, "Automatic real time detection of atrial fibrillation," Ann. Biomed.Eng., vol. 37, no. 9, pp. 1701-1709, Sep. 2009.
2. E. J. Benjamin, P. A. Wolf, R. B. D'Agostino, H. Silbershatz, W. B. Kannel, and D. Levy, "Impact of atrial fibrillation on the risk of death: The framingham heart study," Circulation, vol. 98, no. 10, pp. 946-952, Sep. 1998. (Pubitemid 28446646)
3. S. T. Lawless, "Crying wolf: False alarms in a pediatric intensive care unit," Crit. Care Med., vol. 22, no. 6, pp. 981-985, Jun. 1994. (Pubitemid 24182730)
4. J. Muhlsteff, O. Such, R. Schmidt, M. Perkuhn, H. Reiter, J. Lauter, J. Thijs, G. Musch, and M. Harris, "Wearable approach for continuous ECG and activity patient-monitoring," in Proc. IEEE Conf. Eng. Med. Biol. Soc., 2004, vol. 3, pp. 2184-2187. (Pubitemid 40035854)
5. J. S. Paul, M. R. Reddy, and V. J. Kumar, "A transform domain SVD filter for suppression of muscle noise artefacts in exercise ECG's," IEEE Trans. Biomed. Eng., vol. 47, no. 5, pp. 654-663, May 2000. (Pubitemid 30316984)
6. N.V.Thakor andY. S. Zhu, "Applications of adaptive filtering toECGanalysis: Noise cancellation and arrhythmia detection," IEEE Trans. Biomed. Eng., vol. 38, no. 8, pp. 785-794, Aug. 1991.
7. G. Lu, J. S. Brittain, P. Holland, J. Yianni, A. L. Green, J. F. Stein, T. Z. Aziz, and S.Wang, "Removing ECGnoise from surfaceEMGsignals using adaptive filtering," Neurosci. Lett., vol. 462, no. 1, pp. 14-19, Oct. 2009.
8. D. L. Donoho, "De-noising by soft-thresholding," IEEE Trans. Inf. Theory, vol. 41, no. 1, pp. 613-627, May 1995.
9. M. Ayat, M. B. Shamsollahi, B. Mozaffari, and S. Kharabian, "ECG denoising using modulus maxima of wavelet transform," in Proc. IEEE Conf. Eng. Med. Biol. Soc., 2009, pp. 416-419.
10. O. Sayadi and M. B. Shamsollahi, "ECG denoising with adaptive bionic wavelet transform," in Proc. IEEE Conf. Eng. Med. Biol. Soc., 2006, pp. 6597-6600. (Pubitemid 46521437)
11. R. Sameni,M. B. Shamsollahi, C. Jutten, and G. D. Clifford, "A nonlinear Bayesian filtering framework for ECG denoising," IEEE Trans. Biomed. Eng., vol. 54, no. 12, pp. 2172-2185, Dec. 2007. (Pubitemid 350157787)
12. Y. Kishimoto, Y. Kutsuna, and K. Oguri, "Detecting motion artifact ECG noise during sleeping bymeans of a tri-axis accelerometer," in Proc. IEEE Conf. Eng. Med. Biol. Soc., 2007, pp. 2669-2672.
13. S. W. Yoon, S. D. Min, Y. H. Yun, S. Lee, and M. Lee, "Adaptive motion artifacts reduction using 3-axis accelerometer in e-textile ECG measurement system," J. Med. Syst., vol. 32, no. 2, pp. 101-106, Apr. 2008.
14. N. E. Huang, Z. Shen, S. R. Long, M. L. C. Wu, H. H. Shih, Q. N. Zheng, N. C. Yen, C. C. Tung, and H. H. Liu, "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis," in Proc. Royal Soc. London Series A, Math. Phys. Eng. Sci., Mar. 8, 1998, vol. 454, no. 1971, pp. 903-995. (Pubitemid 128733183)
15. N. ur Rehman and D. P. Mandic, "Empirical mode decomposition for trivariate signals," IEEE Trans. Signal Process., vol. 58, no. 3, pp. 1059-1068, Mar. 2010.
16. P. L. Lee, L. Z. Shang, Y. T.Wu, C. H. Shu, J. C. Hsieh, Y. Y. Lin, C. H. Wu, Y. L. Liu, C. Y. Yang, C. W. Sun, and K. K. Shyu, "Single-trial analysis of cortical oscillatory activities during voluntary movements using empirical mode decomposition (EMD)-based spatiotemporal approach," Ann. Biomed. Eng., vol. 37, no. 8, pp. 1683-1700, Aug. 2009.
17. B. Mijovic, M. De Vos, I. Gligorijevic, J. Taelman, and S. Van Huffel, "Source separation from single-channel recordings by combining empirical-mode decomposition and independent component analysis," IEEE Trans. Biomed. Eng., vol. 57, no. 9, pp. 2188-2196, Sep. 2010.
18. Y. Zhang, Y. Gao, L. Wang, J. Chen, and X. Shi, "The removal of wall components in Doppler ultrasound signals by using the empirical mode decomposition algorithm," IEEE Trans. Biomed. Eng., vol. 54, no. 9, pp. 1631-1642, Sep. 2007. (Pubitemid 47301042)
19. J. I. Salisbury and Y. Sun, "Assessment of chaotic parameters in nonstationary electrocardiograms by use of empirical mode decomposition," Ann. Biomed. Eng., vol. 32, no. 10, pp. 1348-1354, Oct. 2004.
20. G. Rilling and P. Flandrin, "One or two frequencies? The empirical mode decomposition answers," IEEE Trans. Signal Process., vol. 56, no. 1, pp. 85-95, Jan. 2008.
21. Z.Wu,N. E.Huang, S. R. Long, and C.K. Peng, "On the trend, detrending, and variability of nonlinear and nonstationary time series," in Proc. Natl. Acad. Sci. USA, Sep. 2007, vol. 104, no. 38, pp. 14889-14894. (Pubitemid 47619564)
22. C. Huang, S. Ye, H. Chen, D. Li, F. He, and Y. Tu, "A novel method for detection of the transition between atrial fibrillation and sinus rhythm," IEEE Trans. Biomed. Eng., vol. 58, no. 4, pp. 1113-1119, Apr. 2011.
23. N. Kikillus, G. Hammer, N. Lentz, F. Stockwald, and A. Bolz, "Three different algorithms for identifying patients suffering from atrial fibrillation during atrial fibrillation free phases of the ECG," Comput. Cardiol., vol. 34, pp. 801-804, 2007.
24. K. Tateno and L. Glass, "Automatic detection of atrial fibrillation using the coefficient of variation and density histograms of RR and deltaRR intervals," Med. Biol. Eng. Comput., vol. 39, no. 6, pp. 664-671, Nov. 2001. (Pubitemid 34065852)
25. L. Jordaens, R. Tavernier, N. Gorgov, H. Kindt, C. Dimmer, and D. L. Clement, "Signal-averaged P wave: Predictor of atrial fibrillation," J. Cardiovasc. Electrophysiol., vol. 9, no. 8, pp. S30-S34, Aug. 1998. (Pubitemid 28394714)
26. L. Clavier, J. M. Boucher, R. Lepage, J. J. Blanc, and J. C. Cornily, "Automatic P-wave analysis of patients prone to atrial fibrillation," Med. Biol. Eng. Comput., vol. 40, no. 1, pp. 63-71, Jan. 2002. (Pubitemid 34233060)
27. J. Boyle, N. Bidargaddi, A. Sarela, andM. Karunanithi, "Automatic detection of respiration rate from ambulatory single-lead ECG," IEEE Trans. Inf. Technol. Biomed., vol. 13, no. 6, pp. 890-896, Nov. 2009.
28. S. Babaeizadeh, S. H. Zhou, S. D. Pittman, and D. P. White, "Electrocardiogram-derived respiration in screening of sleep-disordered breathing," J. Electrocardiol, Sep. 2011.
29. P. K. Stein, S. P. Duntley, P. P. Domitrovich, P. Nishith, and R. M. Carney, "A simple method to identify sleep apnea using Holter recordings," J. Cardiovasc. Electrophysiol, vol. 14, no. 5, pp. 467-473, May 2003. (Pubitemid 36583905)
30. C. T. Chan, P. Hanly, J. Gabor, P. Picton, A. Pierratos, and J. S. Floras, "Impact of nocturnal hemodialysis on the variability of heart rate and duration of hypoxemia during sleep," Kidney Int., vol. 65, no. 2, pp. 661-665, Feb. 2004. (Pubitemid 38130663)
31. Y. Bai, R. T. Mahon, J. C. White, P. R. Brink, and K. H. Chon, "Impairment of the autonomic nervous function during decompression sickness in swine," J. Appl. Physiol., vol. 106, no. 3, pp. 1004-1009, Mar. 2009.
32. K. H. Chon, S. Dash, and K. Ju, "Estimation of respiratory rate from photoplethysmogram data using time-frequency spectral estimation," IEEE Trans. Biomed. Eng., vol. 56, no. 8, pp. 2054-2063, Aug. 2009.
33. N. Selvaraj, J. Lee, and K. H. Chon, "Time-varying methods for characterizing nonstationary dynamics of physiological systems," Methods Inf. Med., vol. 49, no. 5, pp. 435-442, 2010.
34. B. Yang and K. H. Chon, "A novel approach to monitor nonstationary dynamics in physiological signals: Application to blood pressure, pulse oximeter, and respiratory data," Ann. Biomed. Eng., vol. 38, no. 11, pp. 3478-3488, Nov. 2010.