DocumentCode :
764733
Title :
Time-frequency analysis of electrophysiology signals in epilepsy
Author :
Williams, William J. ; Zaveri, Hitten P. ; Sackellares, J. Chris
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Volume :
14
Issue :
2
fYear :
1995
Firstpage :
133
Lastpage :
143
Abstract :
Many of the most powerful and effective algorithms in signal processing start with the assumption of stationarity. In addition, the deterministic portion of the signal is often assumed to be composed of complex exponentials that are the solutions to linear time-invariant (LTI) differential equations. These assumptions are often valid enough to yield good results when the signals and systems involved result from engineering design which often assures compliance with these conceptualizations. Signals of biological origin often do not comply with these assumptions, however, resulting in disappointment when conventional techniques are used. Newly emerging techniques of time-frequency (t-f) analysis can provide new insights into the nature of biological signals. This article describes some results using reduced interference distributions (RIDs) in the analysis of biosignals recorded in human epilepsy. It is shown that RID analysis of these signals results in insights and research hypotheses which would be difficult or impossible to obtain using conventional techniques. This is not a general t-f review article, and it is beyond the scope of this article (and space limits) to discuss the many new t-f tools that are now appearing in the literature. This article demonstrates one application of RID analysis
Keywords :
electroencephalography; medical signal processing; time-frequency analysis; biosignals analysis; complex exponentials; electrophysiology signals time-frequency analysis; human epilepsy; linear time-invariant differential equations; reduced interference distributions; signal processing algorithms; Biomedical signal processing; Design engineering; Differential equations; Epilepsy; Humans; Interference; Signal analysis; Signal design; Signal processing algorithms; Time frequency analysis;
fLanguage :
English
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
Publisher :
ieee
ISSN :
0739-5175
Type :
jour
DOI :
10.1109/51.376750
Filename :
376750
Link To Document :
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