An automatic algorithm for blink-artifact suppression based on iterative template matching: Application to single channel recording of cortical auditory evoked potentials
Valderrama, Joaquin T
de la Torre, Angel
Van Dun, Bram
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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. 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 signi cant quality improvement in the resulting responses, i.e. in a cohort of 30 adults, the mean correlation coe cient improved from 0.37 to 0.65 when the blink-artifacts were detected and suppressed by ITMS. Signi cance: ITMS is an e cient solution to the problem of denoising blinkartifacts in single-channel EEG applications, both in clinical and research elds. The proposed ITMS algorithm is stable; automatic, since it does not require human intervention; low-invasive, because the EEG segments not contaminated by blinkartifacts remain unaltered; and easy to implement, as can be observed in the Matlab script implemeting the algorithm provided as supporting material.