title: Using independent component analysis to remove artifact from electroencephalographic measured during stuttered speech.
abstract: The electro-encephalographic (EEG) activity of people who stutter could provide invaluable information about the association of neural processing and stuttering. However, the EEG has never been adequately studied during speech in which stuttering naturally occurs. This is owing, in part, to the masking of the EEG signal by artifact from sources such as the speech musculature and from ocular activity. The aim of this paper was to demonstrate the ability of independent component analysis (ICA) to remove artifact from the EEG of stuttering children recorded while they are speaking and stuttering. The EEG of 16 male children who stuttered and 16 who did not stutter was recorded during a reading task. The recorded EEG that contained artifact was then subjected to ICA. The results demonstrated that the EEG assessed during stuttered speech had substantially more noise than the EEG of speech that did not contain stuttering (p < 0.01). Furthermore, it was shown that ICA could effectively remove this artifact in all 16 children (p < 0.01). The results from one child highlight the findings that ICA can be used to remove dominant artifact that has prevented the study of EEG activity during stuttered speech in children.
authors.affiliation: Department of Health Sciences, University of Technology, Sydney Australia. yvonne.tran@uts.edu.au
authors.forename: Y
authors.initials: Y
authors.lastname: Tran
authors.forename: A
authors.initials: A
authors.lastname: Craig
authors.forename: P
authors.initials: P
authors.lastname: Boord
authors.forename: D
authors.initials: D
authors.lastname: Craig
mesh_terms: D000293:Adolescent; D000465:Algorithms; D016477:Artifacts; D002648:Child; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008297:Male; D012815:Signal Processing, Computer-Assisted; D013342:Stuttering / Q000503:physiopathology*