Proposing an eye blink artifact rejection technique from single-channel EEG signal using positive semi-definite tensor factorization

Suguru Kanoga, Yasue Mitsukura

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this paper, we aim to propose an eye blink artifact rejection technique for single-channel electroencephalographic (EEG) devices. Independent component analysis (ICA) is usually employed for eye blink artifact rejection. However, ICA cannot be used for the artifact rejection when we recorded EEG signals by single-channel EEG devices, since this method requires multichannel signals for source estimation. On the other hand, single-channel EEG devices have been attracted attention since 2000 because of its usability for measurement and portability. In this paper, we propose positive semi-definite tensor factorization (PSDTF) with 2 step learning method as a new eye blink artifact rejection technique for single-channel EEG analysis. We investigate its validity using signal-to-noise ratio (SNR) between eye blink artifact signals estimated by our proposed method or ICA. Average value of SNR across subjects and trials is 16.13 dB. For the value, the validity of our proposed method for eye blink artifact rejection of single-channel EEG signals was confirmed.

Original languageEnglish
Pages (from-to)848-855
Number of pages8
JournalIEEJ Transactions on Electronics, Information and Systems
Volume135
Issue number7
DOIs
Publication statusPublished - 2015 Jul 1

Fingerprint

Independent component analysis
Factorization
Tensors
Signal to noise ratio

Keywords

  • EEG signal
  • Eye blink artifact
  • ICA
  • Positive semi-definite tensor factorization
  • Single-channel EEG device

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

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abstract = "In this paper, we aim to propose an eye blink artifact rejection technique for single-channel electroencephalographic (EEG) devices. Independent component analysis (ICA) is usually employed for eye blink artifact rejection. However, ICA cannot be used for the artifact rejection when we recorded EEG signals by single-channel EEG devices, since this method requires multichannel signals for source estimation. On the other hand, single-channel EEG devices have been attracted attention since 2000 because of its usability for measurement and portability. In this paper, we propose positive semi-definite tensor factorization (PSDTF) with 2 step learning method as a new eye blink artifact rejection technique for single-channel EEG analysis. We investigate its validity using signal-to-noise ratio (SNR) between eye blink artifact signals estimated by our proposed method or ICA. Average value of SNR across subjects and trials is 16.13 dB. For the value, the validity of our proposed method for eye blink artifact rejection of single-channel EEG signals was confirmed.",
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