An automatic algorithm for blink-artifact suppression based on iterative template matching: Application to single channel recording of cortical auditory evoked potentials
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Date
2017Author
Valderrama, J
de la Torre, A
Van Dun, Bram
Dillon, Harvey
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Show full item recordAbstract
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 e cient
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. 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 Multiwindow
Summation of Derivatives within a Window (MSDW) technique using both
synthesized and real EEG data. 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 signi cant quality improvement in the resulting responses. The proposed
ITMS algorithm is easy to be implemented, as can be observed in the Matlab script
provided as supporting material.