An automatic algorithm for blink-artifact suppression based on iterative template matching: application to single channel recording of cortical auditory evoked potentials

Joaquin T. Valderrama, Angel De La Torre, Bram Van Dun

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Objective. Artifact reduction in electroencephalogram (EEG) signals is usually necessary to carry out data analysis appropriately. Despite the large amount of denoising techniques available with a multichannel setup, there is a lack of efficient algorithms that remove (not only detect) blink-artifacts from a single channel EEG, which is of interest in many clinical and research applications. This paper describes and evaluates the iterative template matching and suppression (ITMS), a new method proposed for detecting and suppressing the artifact associated with the blink activity from a single channel EEG. Approach. The approach of ITMS consists of (a) an iterative process in which blink-events are detected and the blink-artifact waveform of the analyzed subject is estimated, (b) generation of a signal modeling the blink-artifact, and (c) suppression of this signal from the raw EEG. The performance of ITMS is compared with the multi-window summation of derivatives within a window (MSDW) technique using both synthesized and real EEG data. Main results. Results suggest that ITMS presents an adequate performance in detecting and suppressing blink-artifacts from a single channel EEG. When applied to the analysis of cortical auditory evoked potentials (CAEPs), ITMS provides a significant quality improvement in the resulting responses, i.e. in a cohort of 30 adults, the mean correlation coefficient improved from 0.37 to 0.65 when the blink-artifacts were detected and suppressed by ITMS. Significance. ITMS is an efficient solution to the problem of denoising blink-artifacts in single-channel EEG applications, both in clinical and research fields. The proposed ITMS algorithm is stable; automatic, since it does not require human intervention; low-invasive, because the EEG segments not contaminated by blink-artifacts remain unaltered; and easy to implement, as can be observed in the Matlab script implemeting the algorithm provided as supporting material.

Original languageEnglish
Article number016008
Pages (from-to)1-15
Number of pages15
JournalJournal of Neural Engineering
Volume15
Issue number1
DOIs
Publication statusPublished - Feb 2018

Keywords

  • artifact removal
  • single channel EEG
  • quality enhancement
  • blinking
  • braincomputer interface (BCI) games
  • PREPULSE INHIBITION
  • EEG
  • ICA
  • MODEL
  • CHILDREN
  • REMOVAL
  • brain-computer interface (BCI) games
  • OCULAR ARTIFACT
  • EOG CORRECTION
  • EYE-MOVEMENT ARTIFACTS

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