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Author:

Huang, Rui (Huang, Rui.) | Heng, Fei (Heng, Fei.) | Hu, Bin (Hu, Bin.) | Peng, Hong (Peng, Hong.) | Zhao, Qinglin (Zhao, Qinglin.) | Shi, Qiuxia (Shi, Qiuxia.) | Han, Jun (Han, Jun.)

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EI Scopus

Abstract:

This paper presents a method to remove ocular artifacts from electroencephalograms (EEGs) which can be used in biomedical analysis in portable environment. An important problem in EEG analysis is how to remove the ocular artifacts which wreak havoc among analyzing EEG signals. In this paper, we propose a combination of Wavelet Transform with effective threshold and adaptive filter which can extract the reference signal according to ocular artifacts distributing in low frequency domain mostly, and adaptive filter based on Least Mean Square (LMS) algorithm is used to remove ocular artifacts from recorded EEG signals. The results show that this method can remove ocular artifacts and superior to a comparison method on retaining uncontaminated EEG signal. This method is applicable to the portable environment, especially when only one channel EEG are recorded. © 2014 Springer International Publishing.

Keyword:

Frequency domain analysis Wavelet transforms Signal processing Biomedical signal processing Adaptive filters Medical informatics Adaptive filtering Bioelectric phenomena Electroencephalography

Author Community:

  • [ 1 ] [Huang, Rui]School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  • [ 2 ] [Heng, Fei]School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  • [ 3 ] [Hu, Bin]School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  • [ 4 ] [Hu, Bin]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 5 ] [Peng, Hong]School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  • [ 6 ] [Zhao, Qinglin]School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  • [ 7 ] [Shi, Qiuxia]School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  • [ 8 ] [Han, Jun]Chinese Academy of Sciences, China

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Source :

ISSN: 0302-9743

Year: 2014

Volume: 8609 LNAI

Page: 122-131

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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