Adaptive Filtering of Heart Rate Signals for an Improved Measure of Cardiac Autonomic Control
In order to provide accurate heart rate variability
indices of sympathetic and parasympathetic activity, the low
frequency and high frequency components of an RR heart rate signal
must be adequately separated. This is not always possible by just
applying spectral analysis, as power from the high and low frequency
components often leak into their adjacent bands. Furthermore,
without the respiratory spectra it is not obvious that the low
frequency component is not another respiratory component, which
can appear in the lower band. This paper describes an adaptive filter,
which aids the separation of the low frequency sympathetic and high
frequency parasympathetic components from an ECG R-R interval
signal, enabling the attainment of more accurate heart rate variability
measures. The algorithm is applied to simulated signals and heart rate
and respiratory signals acquired from an ambulatory monitor
incorporating single lead ECG and inductive plethysmography
sensors embedded in a garment. The results show an improvement
over standard heart rate variability spectral measurements.
[1] M. H. Crawford, S. Bernstein, P. Deedwania, "ACC/AHA guidelines for
ambulatory electrocardiography," Circulation, vol. 100, pp. 886-893,
1999.
[2] P. Grossman, M. Kollai, "Individual differences in respiratory sinus
arrhythmia, intraindividual variations and tonic parasympathetic control
of the heart," Psychophysiology, vol. 30, pp. 486-495, 1993.
[3] D. L. Eckberg, "Sympathovagal balance: a critical appraisal,"
Circulation, vol. 96, pp. 3224-3232, 1997.
[4] 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.
[5] A. Malliani, M. Pagani, F. Lombardi, S. Cerruti, "Cardiovascular neural
regulation explored in the frequency domain," Circulation, vol. 84, pp.
482-492, 1991.
[6] 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.
[7] G. Paolisso, D. Manzella, N. Ferrara et al, "Glucose ingestion affects
cardiac ANS in healthy subjects with different amounts of body fat,"
Am. J. Physiol., vol. 273, pp. E471-E478, 1997.
[8] 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.
[9] 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.
[10] 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.
[11] 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.
[12] I. Korhonen, J. Karhu, L. Mainardi, S. M. Jakob, "Quantification of
haemodynamic response to auditory stimulus in intensive care," Comput.
Meth. Prog. Biomed., vol. 63, pp. 211-218, 2000.
[13] K. Han, J. H. Nagel, B. E. Hurwitz., & N. Schneiderman,
"Decomposition of heart rate variability by adaptive filtering for
estimation of cardiac vagal tone," In J.H. Nagel & W.M. Smith (Eds.),
Nagel & W.M. Smith (Eds.), Bioelectric Phenomena,
Electrocardiography, Electromagnetic Interactions, Neuromuscular
Systems, IEEE Publishing Services, New York, vol. 12, no. 2, pp. 660-
661, 1991.
[14] J. H. Nagel, K. Han, B. E. Hurwitz, "Assessment and diagnostic
applications of heart rate variability," Biomed. Eng. Appl. Basis.
Commun. vol. 5, pp. 147-158, 1993.
[15] 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.
[16] 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.
[17] 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.
[18] 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.
[19] E. Tabachnik, N. Muller, B. Toye and H. Levison, " Measurement of
ventilation in children using the respiratory inductive plethysmograph,"
J. Pediatr., vol. 99, pp. 895-899, 1981.
[20] M. A. Sackner et al, "Calibration of respiratory inductive
plethyomograph during natural breathing," J. Appl. Physiol. vol. 66, pp.
410-420, 1989.
[21] M. A. Sackner et al, "Qualitative diagnostic calibration technique," J.
Appl. Physiol., vol. 87, 869-870, 1999.
[22] J. Pan and W. J. Tompkins, "A real-time QRS detection algorithm,"
IEEE Trans. Biomed. Eng., vol. 32, no. 3, pp. 230-236, 1985.
[23] 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.
[24] 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.
[25] B. Widrow et al., "Adaptive noise cancelling: principles and
applications," Proc. IEEE, vol. 63, pp. 1692-1176, 1975.
[26] S. Kay, L. Marple, Spectrum Analysis- A modem Pespective. Proc. of
the IEEE, vol. 69, no. 11, pp. 1380-1419, Nov. 1981.
[27] B. Widrow et al., "Neural nets for adaptive filtering and adaptive pattern
recognition," IEEE Computer, vol. 21, no. 3, pp. 25-39, Mar 1988.
[1] M. H. Crawford, S. Bernstein, P. Deedwania, "ACC/AHA guidelines for
ambulatory electrocardiography," Circulation, vol. 100, pp. 886-893,
1999.
[2] P. Grossman, M. Kollai, "Individual differences in respiratory sinus
arrhythmia, intraindividual variations and tonic parasympathetic control
of the heart," Psychophysiology, vol. 30, pp. 486-495, 1993.
[3] D. L. Eckberg, "Sympathovagal balance: a critical appraisal,"
Circulation, vol. 96, pp. 3224-3232, 1997.
[4] 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.
[5] A. Malliani, M. Pagani, F. Lombardi, S. Cerruti, "Cardiovascular neural
regulation explored in the frequency domain," Circulation, vol. 84, pp.
482-492, 1991.
[6] 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.
[7] G. Paolisso, D. Manzella, N. Ferrara et al, "Glucose ingestion affects
cardiac ANS in healthy subjects with different amounts of body fat,"
Am. J. Physiol., vol. 273, pp. E471-E478, 1997.
[8] 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.
[9] 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.
[10] 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.
[11] 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.
[12] I. Korhonen, J. Karhu, L. Mainardi, S. M. Jakob, "Quantification of
haemodynamic response to auditory stimulus in intensive care," Comput.
Meth. Prog. Biomed., vol. 63, pp. 211-218, 2000.
[13] K. Han, J. H. Nagel, B. E. Hurwitz., & N. Schneiderman,
"Decomposition of heart rate variability by adaptive filtering for
estimation of cardiac vagal tone," In J.H. Nagel & W.M. Smith (Eds.),
Nagel & W.M. Smith (Eds.), Bioelectric Phenomena,
Electrocardiography, Electromagnetic Interactions, Neuromuscular
Systems, IEEE Publishing Services, New York, vol. 12, no. 2, pp. 660-
661, 1991.
[14] J. H. Nagel, K. Han, B. E. Hurwitz, "Assessment and diagnostic
applications of heart rate variability," Biomed. Eng. Appl. Basis.
Commun. vol. 5, pp. 147-158, 1993.
[15] 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.
[16] 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.
[17] 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.
[18] 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.
[19] E. Tabachnik, N. Muller, B. Toye and H. Levison, " Measurement of
ventilation in children using the respiratory inductive plethysmograph,"
J. Pediatr., vol. 99, pp. 895-899, 1981.
[20] M. A. Sackner et al, "Calibration of respiratory inductive
plethyomograph during natural breathing," J. Appl. Physiol. vol. 66, pp.
410-420, 1989.
[21] M. A. Sackner et al, "Qualitative diagnostic calibration technique," J.
Appl. Physiol., vol. 87, 869-870, 1999.
[22] J. Pan and W. J. Tompkins, "A real-time QRS detection algorithm,"
IEEE Trans. Biomed. Eng., vol. 32, no. 3, pp. 230-236, 1985.
[23] 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.
[24] 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.
[25] B. Widrow et al., "Adaptive noise cancelling: principles and
applications," Proc. IEEE, vol. 63, pp. 1692-1176, 1975.
[26] S. Kay, L. Marple, Spectrum Analysis- A modem Pespective. Proc. of
the IEEE, vol. 69, no. 11, pp. 1380-1419, Nov. 1981.
[27] B. Widrow et al., "Neural nets for adaptive filtering and adaptive pattern
recognition," IEEE Computer, vol. 21, no. 3, pp. 25-39, Mar 1988.
@article{"International Journal of Medical, Medicine and Health Sciences:60190", author = "Desmond B. Keenan and Paul Grossman", title = "Adaptive Filtering of Heart Rate Signals for an Improved Measure of Cardiac Autonomic Control", abstract = "In order to provide accurate heart rate variability
indices of sympathetic and parasympathetic activity, the low
frequency and high frequency components of an RR heart rate signal
must be adequately separated. This is not always possible by just
applying spectral analysis, as power from the high and low frequency
components often leak into their adjacent bands. Furthermore,
without the respiratory spectra it is not obvious that the low
frequency component is not another respiratory component, which
can appear in the lower band. This paper describes an adaptive filter,
which aids the separation of the low frequency sympathetic and high
frequency parasympathetic components from an ECG R-R interval
signal, enabling the attainment of more accurate heart rate variability
measures. The algorithm is applied to simulated signals and heart rate
and respiratory signals acquired from an ambulatory monitor
incorporating single lead ECG and inductive plethysmography
sensors embedded in a garment. The results show an improvement
over standard heart rate variability spectral measurements.", keywords = "Heart rate variability, vagal tone, sympathetic,
parasympathetic, spectral analysis, adaptive filter.", volume = "2", number = "7", pages = "232-7", }
