Spike detection in human muscle sympathetic nerve activity using the kurtosis of stationary wavelet transform coefficients

The accurate assessment of autonomic sympathetic function is important in the diagnosis and study of various autonomic and cardiovascular disorders. Sympathetic function in humans can be assessed by recording the muscle sympathetic nerve activity, which is characterized by synchronous neuronal discharges separated by periods of neural silence dominated by colored Gaussian noise. The raw nerve activity is generally rectified, integrated, and quantified using the integrated burst rate or area. We propose an alternative quantification involving spike detection using a two-stage stationary wavelet transform (SWT) de-noising method. The SWT coefficients are first separated into noise-related and burst-related coefficients on the basis of their local kurtosis. The noise-related coefficients are then used to establish a threshold to identify spikes within the bursts. This method demonstrated better detection performance than an unsupervised amplitude discriminator and similar wavelet-based methods when confronted with simulated data of varying burst rate and signal to noise ratio. Additional validation on data acquired during a graded head-up tilt protocol revealed a strong correlation between the mean spike rate and the mean integrate burst rate (r=0.85) and burst area rate (r=0.91). In conclusion, the kurtosis-based wavelet de-noising technique is a potentially useful method of studying sympathetic nerve activity in humans.

[1]  Thomas W. Parks,et al.  A translation-invariant wavelet representation algorithm with applications , 1996, IEEE Trans. Signal Process..

[2]  V G Macefield,et al.  Firing properties of single vasoconstrictor neurones in human subjects with high levels of muscle sympathetic activity , 1999, The Journal of physiology.

[3]  Karim G. Oweiss,et al.  Spike sorting: a novel shift and amplitude invariant technique , 2002, Neurocomputing.

[4]  R Furlan,et al.  Chronic orthostatic intolerance: a disorder with discordant cardiac and vascular sympathetic control. , 1998, Circulation.

[5]  M Pagani,et al.  Absence of low-frequency variability of sympathetic nerve activity in severe heart failure. , 1997, Circulation.

[6]  Joel W. Burdick,et al.  Spike detection using the continuous wavelet transform , 2005, IEEE Transactions on Biomedical Engineering.

[7]  Sung June Kim,et al.  A wavelet-based method for action potential detection from extracellular neural signal recording with low signal-to-noise ratio , 2003, IEEE Transactions on Biomedical Engineering.

[8]  J. Stoker,et al.  The activity of single vasoconstrictor nerve units in hypertension. , 2003, Acta physiologica Scandinavica.

[9]  B. Wallin,et al.  Peripheral sympathetic neural activity in conscious humans. , 1988, Annual review of physiology.

[10]  A. Mark,et al.  The sympathetic nervous system in hypertension: a potential long-term regulator of arterial pressure. , 1996, Journal of hypertension. Supplement : official journal of the International Society of Hypertension.

[11]  J. N. Langley.  THE AUTONOMIC NERVOUS SYSTEM , 1903 .

[12]  B. Wallin,et al.  Sympathetic nerve activity and insulin in obese normotensive and hypertensive men. , 1996, Hypertension.

[13]  V G Macefield,et al.  Firing properties of single muscle vasoconstrictor neurons in the sympathoexcitation associated with congestive heart failure. , 1999, Circulation.

[14]  Richard G. Shiavi,et al.  Wavelet Methods for Spike Detection in Mouse Renal Sympathetic Nerve Activity , 2007, IEEE Transactions on Biomedical Engineering.

[15]  David L. Donoho,et al.  De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.

[16]  I. Johnstone,et al.  Wavelet Threshold Estimators for Data with Correlated Noise , 1997 .

[17]  T Mano,et al.  A new method of quantifying human muscle sympathetic nerve activity for frequency domain analysis. , 1996, Electroencephalography and clinical neurophysiology.

[18]  C. L. Nikias,et al.  Higher-order spectra analysis : a nonlinear signal processing framework , 1993 .

[19]  A. Porta,et al.  Relationship between spectral components of cardiovascular variabilities and direct measures of muscle sympathetic nerve activity in humans. , 1997, Circulation.

[20]  B. Wallin,et al.  A Quantitative Study of Muscle Nerve Sympathetic Activity in Resting Normotensive and Hypertensive Subjects , 1979, Hypertension.

[21]  A. Porta,et al.  Oscillatory patterns in sympathetic neural discharge and cardiovascular variables during orthostatic stimulus. , 2000, Circulation.

[22]  D. G. Ece,et al.  Power-quality event analysis using higher order cumulants and quadratic classifiers , 2006, IEEE Transactions on Power Delivery.

[23]  P. Vielva,et al.  Detection of Non-Gaussianity in the Wilkinson Microwave Anisotropy Probe First-Year Data Using Spherical Wavelets , 2004 .

[24]  A B Vallbo,et al.  Pulse and respiratory grouping of sympathetic impulses in human muscle-nerves. , 1968, Acta physiologica Scandinavica.

[25]  Jean-Luc Starck,et al.  Cosmological Non-Gaussian Signature Detection: Comparing Performance of Different Statistical Tests , 2005, EURASIP J. Adv. Signal Process..

[26]  I. Biaggioni,et al.  Primer on the Autonomic Nervous System: Second Edition , 2004 .

[27]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  B. Silverman,et al.  Wavelets in statistics: beyond the standard assumptions , 1999, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[29]  Gilles Laurent,et al.  Using noise signature to optimize spike-sorting and to assess neuronal classification quality , 2002, Journal of Neuroscience Methods.

[30]  A. Vallbo,et al.  Somatosensory, proprioceptive, and sympathetic activity in human peripheral nerves. , 1979, Physiological reviews.

[31]  Nozomu Hoshimiya,et al.  Detection of nerve action potentials under low signal-to-noise ratio condition , 2001, IEEE Transactions on Biomedical Engineering.

[32]  J. Letelier,et al.  Spike sorting based on discrete wavelet transform coefficients , 2000, Journal of Neuroscience Methods.

[33]  B. Wallin,et al.  Balance between cardiac output and sympathetic nerve activity in resting humans: role in arterial pressure regulation , 2005, The Journal of physiology.

[34]  J. Moors,et al.  A quantile alternative for kurtosis , 1988 .

[35]  K. Hagbarth,et al.  General characteristics of sympathetic activity in human skin nerves. , 1972, Acta physiologica Scandinavica.

[36]  Raffaello Furlan,et al.  Spectral analysis of multiunit action potential trains of muscle sympathetic nerve activity in humans , 2002, Computers in Cardiology.

[37]  B. Wallin,et al.  The variability of muscle nerve sympathetic activity in resting recumbent man , 1977, The Journal of physiology.

[38]  P. Vielva,et al.  Detection of non-Gaussianity in the WMAP 1-year data using spherical wavelets , 2003 .

[39]  Stéphane Mallat,et al.  Zero-crossings of a wavelet transform , 1991, IEEE Trans. Inf. Theory.

[40]  Richard G. Shiavi,et al.  Analysis of raw microneurographic recordings based on wavelet de-noising technique and classification algorithm: wavelet analysis in microneurography , 2003, IEEE Transactions on Biomedical Engineering.

[41]  S. Sengupta.  Introduction to Applied Statistical Signal Analysis , 1991 .