Detection and Correction of Ectopic Beats for HRV Analysis Applying Discrete Wavelet Transforms
The clinical usefulness of heart rate variability is
limited to the range of Holter monitoring software available. These
software algorithms require a normal sinus rhythm to accurately
acquire heart rate variability (HRV) measures in the frequency
domain. Premature ventricular contractions (PVC) or more
commonly referred to as ectopic beats, frequent in heart failure,
hinder this analysis and introduce ambiguity. This investigation
demonstrates an algorithm to automatically detect ectopic beats by
analyzing discrete wavelet transform coefficients. Two techniques
for filtering and replacing the ectopic beats from the RR signal are
compared. One technique applies wavelet hard thresholding
techniques and another applies linear interpolation to replace ectopic
cycles. The results demonstrate through simulation, and signals
acquired from a 24hr ambulatory recorder, that these techniques can
accurately detect PVC-s and remove the noise and leakage effects
produced by ectopic cycles retaining smooth spectra with the
minimum of error.
[1] M. H. Crawford, S. Bernstein, P. Deedwania, "ACC/AHA guidelines for
ambulatory electrocardiography," Circulation, vol. 100, pp. 886-893,
1999.
[2] N. Montano, T. Gnecchi Ruscone, A. Porta, F. Lombardi, M. Pagani, A.
Malliani, "Power spectrum analysis of heart rate variability to assess the
changes in sympathovagal balance during graded orthostatic tilt,"
Circulation, vol. 90, pp. 1826-1831, 1994.
[3] A. Malliani, M. Pagani, F. Lombardi, S. Cerruti, "Cardiovascular neural
regulation explored in the frequency domain," Circulation, vol. 84, pp.
482-492, 1991.
[4] M. Pagani, N. Montano, A. Porta, "Relationship between spectral
components of cardiovascular variabilities and direct measures of
muscle sympathetic nerve activity in humans," Circulation, vol. 95, pp.
1441-1448, 1997.
[5] G. Paolisso, D. Manzella, N. Ferrara, et al. "Glucose Ingestion Affects
Cardiac ANS in Healthy Subjects with Different Amounts of Body Fat,"
American Journal of Physiology, vol. 273, pp. E471-E478, 1997.
[6] A. Ravogli, G. Parati, E. Tortorici et al, "Early cardiovascular alterations
in young obese subjects: evidence from 24-hour blood pressure and
heart rate monitoring," Europ. Heart J., vol. 98, pp. 3405A, 1998.
[7] R. M. Carney, J. A. Blumenthal, P. K. Stein, L. Watkins, D. Catellier, L.
F. Berkman, S. M. Czajkowski, C. O'Connor, P. H. Stone, K. E.
Freedland, "Depression, Heart Rate Variability, and Acute Myocardial
Infarction," Circulation, vol. 104, no. 17, pp. 2024 - 2028, 2001.
[8] P. Grossman, J. A. Van Beek, "A Comparison of Three Quantification
Methods for Estimation of Respiratory Sinus Arrhythmia,"
Psychophysiology, vol. 27, no. 6, pp. 702-714, 1990.
[9] K. Kotani, I. Hidaka, Y. Yamamoto, S. Ozono, "Analysis of Respiratory
Sinus Arrhythmia with Respect to Respiratory Phase," Methods of
Information in Medicine, vol. 39, pp. 153-156, 2000.
[10] J. Mateo, P. Gasc├│n, L. Lasaosa, "Analysis of Heart Rate Variability in
the Presence of Ectopic Beats Using the Heart Timing Signal," IEEE
Transactions on Biomedical Engineering, vol. 50, no. 3, pp. 334-343,
2003.
[11] M. A. Murda'h,, W. J. McKenna, A. J. Camm, "Repolarization
Alternans: Techniques, Mechanisms, and Cardiac Vulnerability," Pacing
Clinical Electrophysioly, vol. 20, pp. 2641-2657, 1997.
[12] P. Laguna, R. Jané, P. Caminal, "Adaptive estimation of QRS complex
by the Hermite model for classification and ectopic beat detection,"
Medical and Biological Engineering and Computing, vol. 34, pp. 58-68,
1996.
[13] M. A. Salo, T. Seppänen, H. V. Huikuri, "Ectopic Beats in Heart Rate
Variability Analysis: Effects of Editing on Time and Frequency Domain
Measures," Annals of Noninvasive Electrocardiology, vol. 6, no. 1, pp.
5-17, 2001.
[14] K. Konno and J. Mead, "Measurement of the separate volume changes
of rib cage and abdomen during breathing," J. Appl. Physiol., vol. 22,
pp. 407-422, 1967.
[15] J. Sackner, A. Nixon, B. Davis, N. Atkins, and M. Sackner, "Noninvasive
measurement of ventilation during exercise using a respiratory
inductive plethysmograph. I," Am. Rev. Respir. Dis., vol. 122, pp. 867-
871, 1980.
[16] J. A. Adams, I. A. Zabaleta, D. Stroh, M. A. Sackner, "Measurement of
breath amplitudes: comparison of three noninvasive respiratory monitors
to integrated pneumotachograph," Pediatr. Pulmonol., vol. 16, pp. 254-
258, 1993.
[17] M. A. Sackner, and B. P. Krieger, "Non-invasive respiratory
monitoring," In: Heart-Lung Interactions in Health and Disease, edited
by S.M. Scharf, and S. S. Cassidy, New York: Marcel Dekker, pp. 663-
805, 1989.
[18] M. A. Sackner et al, "Calibration of respiratory inductive
plethyomograph during natural breathing," J. Appl. Physiol. vol. 66, pp.
410-420, 1989.
[19] M. A. Sackner et al, "Qualitative diagnostic calibration technique," J.
Appl. Physiol., vol. 87, 869-870, 1999.
[20] J. Pan and W. J. Tompkins, "A real-time QRS detection algorithm,"
IEEE Trans. Biomed. Eng., vol. 32, no. 3, pp. 230-236, 1985..
[21] P. D. Welch, "The Use of Fast Fourier Transform for the Estimation of
Power Spectra: A Method Based on Time Averaging Over Short,
Modified Periodograms," IEEE Trans. Audio Electroacoustics, vol. AU-
15, pp. 70-73, 1967.
[22] A. J. Camm, M. Malik, "Heart Rate Variability: Standards of
Measurement, Physiological Interpretation and Clinical Use," Task
Force of the Working Groups on Arrhythmias and Computers in
Cardiology of the ESC and the North American Society of Pacing and
Electrophysiology (NASPE). European Heart Journal, vol. 93, pp.
1043-1065, 1996.
[23] I. Daubechies, "Orthogonal bases of compactly supported wavelets,"
Communications on Pure and Applied Mathematics, vol. 41, pp. 909-
996, 1988.
[24] D. L. Donoho, I. M. Johnstone, "Wavelet Shrinkage: Asymptopia?,"
Journal of the Royal Statistical Societ, Series B, vol. 57, pp. 301-369,
1995.
[25] D. L. Donoho, I. M. Johnstone, "Ideal time-frequency denoising,
Technical Report," Department of Statistics, Standford University, 1994.
[26] D. L. Donoho, I. M. Johnstone, "Ideal Spatial Adaptation via Wavelet
Shrinkage," Biometrika, vol. 81, pp. 425-455, 1994.
[27] D. L. Donoho, "De-noising by Soft Thresholding," IEEE Transactions
on Information Technology, vol. 41, pp. 613-627, 1995.
[1] M. H. Crawford, S. Bernstein, P. Deedwania, "ACC/AHA guidelines for
ambulatory electrocardiography," Circulation, vol. 100, pp. 886-893,
1999.
[2] N. Montano, T. Gnecchi Ruscone, A. Porta, F. Lombardi, M. Pagani, A.
Malliani, "Power spectrum analysis of heart rate variability to assess the
changes in sympathovagal balance during graded orthostatic tilt,"
Circulation, vol. 90, pp. 1826-1831, 1994.
[3] A. Malliani, M. Pagani, F. Lombardi, S. Cerruti, "Cardiovascular neural
regulation explored in the frequency domain," Circulation, vol. 84, pp.
482-492, 1991.
[4] M. Pagani, N. Montano, A. Porta, "Relationship between spectral
components of cardiovascular variabilities and direct measures of
muscle sympathetic nerve activity in humans," Circulation, vol. 95, pp.
1441-1448, 1997.
[5] G. Paolisso, D. Manzella, N. Ferrara, et al. "Glucose Ingestion Affects
Cardiac ANS in Healthy Subjects with Different Amounts of Body Fat,"
American Journal of Physiology, vol. 273, pp. E471-E478, 1997.
[6] A. Ravogli, G. Parati, E. Tortorici et al, "Early cardiovascular alterations
in young obese subjects: evidence from 24-hour blood pressure and
heart rate monitoring," Europ. Heart J., vol. 98, pp. 3405A, 1998.
[7] R. M. Carney, J. A. Blumenthal, P. K. Stein, L. Watkins, D. Catellier, L.
F. Berkman, S. M. Czajkowski, C. O'Connor, P. H. Stone, K. E.
Freedland, "Depression, Heart Rate Variability, and Acute Myocardial
Infarction," Circulation, vol. 104, no. 17, pp. 2024 - 2028, 2001.
[8] P. Grossman, J. A. Van Beek, "A Comparison of Three Quantification
Methods for Estimation of Respiratory Sinus Arrhythmia,"
Psychophysiology, vol. 27, no. 6, pp. 702-714, 1990.
[9] K. Kotani, I. Hidaka, Y. Yamamoto, S. Ozono, "Analysis of Respiratory
Sinus Arrhythmia with Respect to Respiratory Phase," Methods of
Information in Medicine, vol. 39, pp. 153-156, 2000.
[10] J. Mateo, P. Gasc├│n, L. Lasaosa, "Analysis of Heart Rate Variability in
the Presence of Ectopic Beats Using the Heart Timing Signal," IEEE
Transactions on Biomedical Engineering, vol. 50, no. 3, pp. 334-343,
2003.
[11] M. A. Murda'h,, W. J. McKenna, A. J. Camm, "Repolarization
Alternans: Techniques, Mechanisms, and Cardiac Vulnerability," Pacing
Clinical Electrophysioly, vol. 20, pp. 2641-2657, 1997.
[12] P. Laguna, R. Jané, P. Caminal, "Adaptive estimation of QRS complex
by the Hermite model for classification and ectopic beat detection,"
Medical and Biological Engineering and Computing, vol. 34, pp. 58-68,
1996.
[13] M. A. Salo, T. Seppänen, H. V. Huikuri, "Ectopic Beats in Heart Rate
Variability Analysis: Effects of Editing on Time and Frequency Domain
Measures," Annals of Noninvasive Electrocardiology, vol. 6, no. 1, pp.
5-17, 2001.
[14] K. Konno and J. Mead, "Measurement of the separate volume changes
of rib cage and abdomen during breathing," J. Appl. Physiol., vol. 22,
pp. 407-422, 1967.
[15] J. Sackner, A. Nixon, B. Davis, N. Atkins, and M. Sackner, "Noninvasive
measurement of ventilation during exercise using a respiratory
inductive plethysmograph. I," Am. Rev. Respir. Dis., vol. 122, pp. 867-
871, 1980.
[16] J. A. Adams, I. A. Zabaleta, D. Stroh, M. A. Sackner, "Measurement of
breath amplitudes: comparison of three noninvasive respiratory monitors
to integrated pneumotachograph," Pediatr. Pulmonol., vol. 16, pp. 254-
258, 1993.
[17] M. A. Sackner, and B. P. Krieger, "Non-invasive respiratory
monitoring," In: Heart-Lung Interactions in Health and Disease, edited
by S.M. Scharf, and S. S. Cassidy, New York: Marcel Dekker, pp. 663-
805, 1989.
[18] M. A. Sackner et al, "Calibration of respiratory inductive
plethyomograph during natural breathing," J. Appl. Physiol. vol. 66, pp.
410-420, 1989.
[19] M. A. Sackner et al, "Qualitative diagnostic calibration technique," J.
Appl. Physiol., vol. 87, 869-870, 1999.
[20] J. Pan and W. J. Tompkins, "A real-time QRS detection algorithm,"
IEEE Trans. Biomed. Eng., vol. 32, no. 3, pp. 230-236, 1985..
[21] P. D. Welch, "The Use of Fast Fourier Transform for the Estimation of
Power Spectra: A Method Based on Time Averaging Over Short,
Modified Periodograms," IEEE Trans. Audio Electroacoustics, vol. AU-
15, pp. 70-73, 1967.
[22] A. J. Camm, M. Malik, "Heart Rate Variability: Standards of
Measurement, Physiological Interpretation and Clinical Use," Task
Force of the Working Groups on Arrhythmias and Computers in
Cardiology of the ESC and the North American Society of Pacing and
Electrophysiology (NASPE). European Heart Journal, vol. 93, pp.
1043-1065, 1996.
[23] I. Daubechies, "Orthogonal bases of compactly supported wavelets,"
Communications on Pure and Applied Mathematics, vol. 41, pp. 909-
996, 1988.
[24] D. L. Donoho, I. M. Johnstone, "Wavelet Shrinkage: Asymptopia?,"
Journal of the Royal Statistical Societ, Series B, vol. 57, pp. 301-369,
1995.
[25] D. L. Donoho, I. M. Johnstone, "Ideal time-frequency denoising,
Technical Report," Department of Statistics, Standford University, 1994.
[26] D. L. Donoho, I. M. Johnstone, "Ideal Spatial Adaptation via Wavelet
Shrinkage," Biometrika, vol. 81, pp. 425-455, 1994.
[27] D. L. Donoho, "De-noising by Soft Thresholding," IEEE Transactions
on Information Technology, vol. 41, pp. 613-627, 1995.
@article{"International Journal of Medical, Medicine and Health Sciences:59200", author = "Desmond B. Keenan", title = "Detection and Correction of Ectopic Beats for HRV Analysis Applying Discrete Wavelet Transforms", abstract = "The clinical usefulness of heart rate variability is
limited to the range of Holter monitoring software available. These
software algorithms require a normal sinus rhythm to accurately
acquire heart rate variability (HRV) measures in the frequency
domain. Premature ventricular contractions (PVC) or more
commonly referred to as ectopic beats, frequent in heart failure,
hinder this analysis and introduce ambiguity. This investigation
demonstrates an algorithm to automatically detect ectopic beats by
analyzing discrete wavelet transform coefficients. Two techniques
for filtering and replacing the ectopic beats from the RR signal are
compared. One technique applies wavelet hard thresholding
techniques and another applies linear interpolation to replace ectopic
cycles. The results demonstrate through simulation, and signals
acquired from a 24hr ambulatory recorder, that these techniques can
accurately detect PVC-s and remove the noise and leakage effects
produced by ectopic cycles retaining smooth spectra with the
minimum of error.", keywords = "Heart rate variability, vagal tone, sympathetic,parasympathetic, wavelets, ectopic beats, spectral analysis.", volume = "2", number = "10", pages = "354-7", }
