A robust algorithm for removing artifacts in EEG recorded during FMRI/EEG study

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The main purpose of this study was to propose a robust algorithm for removing artifacts from the electroencephalographic (EEG) data collected during magnetic resonance imaging (MRI). The core idea of the proposed method was to remove the main gradient artifacts by the maximum cross-correlation method and to remove the residual artifacts by the rolling-ball algorithm and lowpass filtering. The results showed that the proposed algorithm had a better performance and was robust in the sense that its performance was maintained when the sampling rate of EEG data was decreased from 10. KHz to 200. Hz.

Original languageEnglish
Pages (from-to)458-467
Number of pages10
JournalComputers in Biology and Medicine
Volume42
Issue number4
DOIs
Publication statusPublished - 2012 Apr 1

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Artifacts
Correlation methods
Magnetic resonance
Magnetic Resonance Imaging
Sampling
Imaging techniques

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Health Informatics

Cite this

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A robust algorithm for removing artifacts in EEG recorded during FMRI/EEG study. / Huang, Chih Hsu; Ju, Ming-Shaung; Lin, Chou-Ching.

In: Computers in Biology and Medicine, Vol. 42, No. 4, 01.04.2012, p. 458-467.

Research output: Contribution to journalArticle

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