Estimation of evoked potentials using high order statistics-based adaptive filter

Bor-Shyh Lin, Bor Shing Lin, Shu Mei Wu, Jen Chien Chien, Fok Ching Chong

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

This paper is to present a high order statistics-based adaptive interference cancel filter (AIC-HOS) to process evoked potential (EP). In conventional ensemble averaging method, experiments have to conduct repetitively to record the required data. In normalized LMS adaptive filter, inappropriate step size always causes deficiency. This AIC-HOS system has none of the above disadvantages. This system was experimented in somatosensory evoked potential corrupted with EEG. Gradient type algorithm is used in this AIC-HOS structure to regulate the SNR of EEG and EP. This method is also simulated with visual evoked potential and audio evoked potential. The results obtained are satisfactory and acceptable in clinical usage. The AIC-HOS is superior to normalized LMS using adaptive filter in that it converges easily. Moreover, it is not sensitive to selection of step size in stabilities in convergency.

Original languageEnglish
Pages (from-to)2094-2096
Number of pages3
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2
DOIs
StatePublished - 1 Dec 2001
Event23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey
Duration: 25 Oct 200128 Oct 2001

Keywords

  • Adaptive filter
  • Evoked potential
  • High order statistics

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