Paper Info
Title
Microelectrode Signals Segmentation Using Stationary Wavelet Transform
Abstract
We present a methodology for the automatic segmentation of extracellular microelectrode recordings (MER) based on stationary wavelet transform and modified F test which identify segments with equal time - frequency behavior. The method was tested using synthetic signals and then applied to real MER signals, achieving artifact removal and showing a superior performance than segmentation based on time representation.
Year
DOI
Venue
2008
10.1109/BMEI.2008.363
BMEI (2)
Keywords
Field
DocType
stationary wavelet transform,real mer signal,time representation,equal time,microelectrode signals segmentation,stationary wavelet,automatic segmentation,modified f test,frequency behavior,artifact removal,extracellular microelectrode recording,superior performance,mer,segmentation,wavelet transforms,signal generators,time frequency,frequency,microelectrodes,neurosurgery
Computer vision,Pattern recognition,Segmentation,F-test,Computer science,Signal generator,Artificial intelligence,Stationary wavelet transform,Microelectrode,Wavelet transform
Conference
ISSN
Citations 
PageRank 
1948-2914
0
0.34
References 
Authors
4
3
Name
Order
Citations
PageRank
Cristian Guarnizo131.40
Álvaro Á. Orozco21612.88
German Castellanos-Dominguez325851.21