High-resolution Time-frequency Analysis of Somatosensory Evoked Potential Components by Means of Matching Pursuit

摘要

This paper proposes to apply a high-resolution time-frequency analysis (TFA) algorithm,the matching pursuit (MP),to extract and identify detail components of somatosensory evoked potential (SEP) signals.Conventional TFA methods showed limited timefrequency resolution in short-period nonstationary SEP signals so that they cannot reveal detail components in time-frequency domain.The MP algorithm can decompose a SEP signal into a number of elementary components and provide a time-frequency parameter description of decomposed components.The stable components can be revealed by statistical analysis and classification of the extracted parameters.Experimental results on cortical SEP signals of rats show that a series of stable SEP components can be identified using the MP decomposition algorithm.