Document Detail


Spike detection in human muscle sympathetic nerve activity using a matched wavelet approach.
MedLine Citation:
PMID:  20831884     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
Sympathetic nerve recordings associated with blood pressure regulation can be recorded directly using microneurography. A general characteristic of this signal is spontaneous burst activity of spikes (action potentials) separated by silent periods against a background of considerable Gaussian noise. During measurement with electrodes, the raw muscle sympathetic nerve activity (MSNA) signal is amplified, band-pass filtered, rectified and integrated. This integration process removes information regarding action potential content and their discharge properties. This paper proposes a new method for detecting action potentials from the raw MSNA signal to enable investigation of post-ganglionic neural discharge properties. The new method is based on the design of a mother wavelet that is matched to an actual mean action potential template extracted from a real raw MSNA signal. To detect action potentials, the new matched wavelet is applied to the MSNA signal using a continuous wavelet transform following a thresholding procedure and finding of a local maxima that indicates the location of action potentials. The performance of the proposed method versus two previous wavelet-based approaches was evaluated using (1) real MSNA recorded from seven healthy participants and, (2) simulated MSNA. The results show that the new matched wavelet performs better than the previous wavelet-based methods that use a non-matched wavelet in detecting action potentials in the MSNA signal.
Authors:
Aryan Salmanpour; Lyndon J Brown; J Kevin Shoemaker
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2010-09-08
Journal Detail:
Title:  Journal of neuroscience methods     Volume:  193     ISSN:  1872-678X     ISO Abbreviation:  J. Neurosci. Methods     Publication Date:  2010 Nov 
Date Detail:
Created Date:  2010-11-02     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7905558     Medline TA:  J Neurosci Methods     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  343-55     Citation Subset:  IM    
Copyright Information:
Copyright © 2010 Elsevier B.V. All rights reserved.
Affiliation:
Department of Electrical and Computer Engineering, University of Western Ontario, London, Ontario, Canada.
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MeSH Terms
Descriptor/Qualifier:
Grant Support
ID/Acronym/Agency:
//Canadian Institutes of Health Research

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