DocumentCode
973241
Title
Multiresolution wavelet analysis of evoked potentials
Author
Thakor, Nitish V. ; Xin-Rong, Guo ; Yi-Chun, Sun ; Hanley, Daniel F.
Author_Institution
Dept. of Biomed. Eng., Johns Hopkins Univ., Baltimore, MD, USA
Volume
40
Issue
11
fYear
1993
Firstpage
1085
Lastpage
1094
Abstract
Neurological injury, such as from cerebral hypoxia, appears to cause complex changes in the shape of evoked potential (EP) signals. To characterize such changes we analyze EP signals with the aid of scaling functions called wavelets. In particular, we consider multiresolution wavelets that are a family of orthonormal functions. In the time domain, the multiresolution wavelets analyze EP signals at coarse or successively greater levels of temporal detail. In the frequency domain, the multiresolution wavelets resolve the EP signal into independent spectral bands. In an experimental demonstration of the method, somatosensory EP signals recorded during cerebral hypoxia in anesthetized cats are analyzed. Results obtained by multiresolution wavelet analysis are compared with conventional time-domain analysis and Fourier series expansions of the same signals. Multiresolution wavelet analysis appears to be a different, sensitive way to analyze EP signal features and to follow the EP signal trends in neurologic injury. Two characteristics appear to be of diagnostic value: the detail component of the MRW displays an early and a more rapid decline in response to hypoxic injury while the coarse component displays an earlier recovery upon reoxygenation.
Keywords
bioelectric potentials; biology computing; frequency-domain analysis; medical signal processing; somatosensory phenomena; time-domain analysis; wavelet transforms; anesthetized cats; cerebral hypoxia; coarse component; diagnostic value; evoked potentials; frequency domain; independent spectral bands; multiresolution wavelet analysis; neurological injury; orthonormal functions; reoxygenation; scaling functions; somatosensory EP signals; time domain; Displays; Frequency domain analysis; Independent component analysis; Injuries; Shape; Signal analysis; Signal resolution; Time domain analysis; Wavelet analysis; Wavelet domain; Algorithms; Animals; Brain Ischemia; Cats; Evoked Potentials, Somatosensory; Signal Processing, Computer-Assisted; Software Design;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/10.245625
Filename
245625
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