Multiresolution Wavelet Analysis of Evoked Potentials

Nitish V. Thakor, Guo Xin-rong, Sun Yi-Chun, Daniel F. Hanley

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)1085-1094
Number of pages10
JournalIEEE Transactions on Biomedical Engineering
Volume40
Issue number11
DOIs
StatePublished - Nov 1993

ASJC Scopus subject areas

  • Biomedical Engineering

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