Paper Info
Title
Interscale wavelet maximum-a fine to coarse algorithm for wavelet analysis of the EMG interference pattern.
Abstract
A method has been developed, interscale wavelet maximum (ISWM), for characterising the electromyogram (EMG) interference pattern to assist in the diagnosis of neuromuscular disease. EMG signals are decomposed with the redundant dyadic wavelet transform and wavelet maxima (WM) are found. Thresholding methods are applied to remove WM due to noise and background activity. An efficient fine-to-coarse algorithm identifies the WM tree structure for the motor unit action potential rising edges. The WM for each tree are summed at each scale; the largest value is the ISWM. Highly significant differences in ISWM values have been found between healthy, myopathic, and neuropathic subjects that could make the technique a useful diagnostic tool.
Year
DOI
Venue
2002
10.1109/10.991161
IEEE transactions on bio-medical engineering
Keywords
Field
DocType
neuromuscular disease diagnosis,interscale wavelet maximum,wavelet transforms,thresholding methods,fine-to-coarse algorithm,medical signal processing,motor unit action potential rising edges,tree structure,electromyogram interference pattern,electromyography,time-frequency domain,time-frequency analysis
Signal processing,Computer science,Signal-to-noise ratio,Algorithm,Electronic engineering,Tree structure,Time–frequency analysis,Interference (wave propagation),Thresholding,Wavelet,Wavelet transform
Journal
Volume
Issue
ISSN
49
4
0018-9294
Citations 
PageRank 
References 
9
1.60
10
Authors
3
Name
Order
Citations
PageRank
Nikolaos S Arikidis191.60
Eric W Abel2142.09
Alan J. Forster313111.69