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Title: Spectral analysis of multiunit action potential trains of muscle sympathetic nerve activity in humans
Authors: R. J. Brychta
W. Charoensuk
L. Bernardi
R. Furlan
R. G. Shiavi
A. Diedrich
Vanderbilt University
Mahidol University
Universita degli Studi di Pavia
Universita degli Studi di Milano
Vanderbilt University Medical Center
5824 Stevenson Center
Keywords: Computer Science;Medicine
Issue Date: 1-Dec-2002
Citation: Computers in Cardiology. Vol.29, (2002), 457-460
Abstract: The application of conventional signal processing methods used to obtain an integrated signal from muscle sympathetic nerve activity (MSNA) reduces the amount of information and may confound the spectral characteristics. We present a novel alternative method of processing the raw MSNA signal using a wavelet transform denoising technique that enables detection of individual action potentials and facilitates spectral analysis. A spike density function (SDF) is generated from the denoised signal by replacing the detected action potentials with delta functions and convolving with a 3 Hz Gaussian filter. This method was validated using data from a sinusoidal neck suction (NS) experiment in humans. The results of the analysis indicate that the oscillations of sympathetic nerve firings closely followed the NS frequency. In conclusion, the SDF representation allows for a novel and insightful analysis of spectral components of action potential trains in raw MSNA.
ISSN: 02766574
Appears in Collections:Scopus 2001-2005

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