Feature extraction for single trial record of visual mismatch negativity by use of independent component analysis

T. Sugi, K. Kimura, S. Nishida, T. Maekawa, K. Ogata, Y. Goto, S. Tobimatsu, M. Nakamura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Signal averaging method is usually utilized for extracting the characteristics of event related potentials (ERPs). However, the amplitude and duration of ERPs are not constant for each stimulus due to the fluctuation of the subject's state, accordingly the appropriate selection of available data is crucial for realizing the accurate averaging. Independent component analysis (ICA) is one of powerful tool for signal processing, and some application to analyze the neurological signal processing such as electroencephalogram (EEG), evoked potentials (EPs), ERPs and so on were done. In this study, ICA was applied to process the visual mismatch negativity (V-MMN) for extracting the features and for selecting the appropriate single trial data for averaging. From the grand average waveform of V-MMN, signal separation matrix was determined by use of ICA. Characteristic parameters for evaluating single trial data were calculated from the decomposed components of ERPs. Then, the available single trial data was selected based on the value of evaluation parameter. Waveforms of selective averaging method and conventional averaging method were compared and the effectiveness of the proposed method was examined.

Original languageEnglish
Title of host publication2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007
Pages1458-1462
Number of pages5
DOIs
Publication statusPublished - 2007
Event2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007 - Beijing, China
Duration: May 23 2007May 27 2007

Publication series

Name2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007

Other

Other2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007
CountryChina
CityBeijing
Period5/23/075/27/07

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Medicine(all)

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