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Time-frequency component analysis of somatosensory evoked potentials in rats
- Source :
- BioMedical Engineering OnLine, Vol 8, Iss 1, p 4 (2009)
- Publication Year :
- 2009
- Publisher :
- BMC, 2009.
-
Abstract
- Abstract Background Somatosensory evoked potential (SEP) signal usually contains a set of detailed temporal components measured and identified in a time domain, giving meaningful information on physiological mechanisms of the nervous system. The purpose of this study is to measure and identify detailed time-frequency components in normal SEP using time-frequency analysis (TFA) methods and to obtain their distribution pattern in the time-frequency domain. Methods This paper proposes to apply a high-resolution time-frequency analysis algorithm, the matching pursuit (MP), to extract detailed time-frequency components of SEP signals. The MP algorithm decomposes a SEP signal into a number of elementary time-frequency components and provides a time-frequency parameter description of the components. A clustering by estimation of the probability density function in parameter space is followed to identify stable SEP time-frequency components. Results Experimental results on cortical SEP signals of 28 mature rats show that a series of stable SEP time-frequency components can be identified using the MP decomposition algorithm. Based on the statistical properties of the component parameters, an approximated distribution of these components in time-frequency domain is suggested to describe the complex SEP response. Conclusion This study shows that there is a set of stable and minute time-frequency components in SEP signals, which are revealed by the MP decomposition and clustering. These stable SEP components have specific localizations in the time-frequency domain.
- Subjects :
- Medical technology
R855-855.5
Subjects
Details
- Language :
- English
- ISSN :
- 1475925X
- Volume :
- 8
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BioMedical Engineering OnLine
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.8b75d0d63cb6401aac515e49075bdf86
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/1475-925X-8-4