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A novel method for device-related electroencephalography artifact suppression to explore cochlear implant-related cortical changes in single-sided deafness

Title
A novel method for device-related electroencephalography artifact suppression to explore cochlear implant-related cortical changes in single-sided deafness
Authors
Kim, K[Kim, Kyungsoo]Punte, AK[Punte, Andrea Kleine]Mertens, G[Mertens, Griet]Van de Heyning, P[Van de Heyning, Paul]Park, KJ[Park, Kyung-Joon]Choi, H[Choi, Hongsoo]Choi, JW[Choi, Ji-Woong]Song, JJ[Song, Jae-Jin]
DGIST Authors
Kim, K[Kim, Kyungsoo]; Park, KJ[Park, Kyung-Joon]Choi, H[Choi, Hongsoo]Choi, JW[Choi, Ji-Woong]
Issue Date
2015-11-30
Citation
Journal of Neuroscience Methods, 255, 22-28
Type
Article
Article Type
Article
Keywords
Acoustic StimulationAdverse EffectsArtifactArtifact ReductionArtifactsAuditory Evoked PotentialAuditory PerceptionAuditory StimulationBrainBrain MappingCase ReportCochlea ProsthesisCochlear ImplantCochlear ImplantationCochlear ImplantsDeafnessElectroencephalographyEnergyEvoked Auditory ResponseEvoked Potentials, AuditoryFunctional LateralityHearingHearing ImpairmentHemispheric DominanceHumanHumansIndependent Component AnalysisPathophysiologyPhysiologyPriority JournalProceduresSignal ProcessingSignal Processing, Computer-AssistedTinnitus
ISSN
0165-0270
Abstract
Background: Quantitative electroencephalography (qEEG) is effective when used to analyze ongoing cortical oscillations in cochlear implant (CI) users. However, localization of cortical activity in such users via qEEG is confounded by the presence of artifacts produced by the device itself. Typically, independent component analysis (ICA) is used to remove CI artifacts in auditory evoked EEG signals collected upon brief stimulation and it is effective for auditory evoked potentials (AEPs). However, AEPs do not reflect the daily environments of patients, and thus, continuous EEG data that are closer to such environments are desirable. In this case, device-related artifacts in EEG data are difficult to remove selectively via ICA due to over-completion of EEG data removal in the absence of preprocessing. New methods: EEGs were recorded for a long time under conditions of continuous auditory stimulation. To obviate the over-completion problem, we limited the frequency of CI artifacts to a significant characteristic peak and apply ICA artifact removal. Results: Topographic brain mapping results analyzed via band-limited (BL)-ICA exhibited a better energy distribution, matched to the CI location, than data obtained using conventional ICA. Also, source localization data verified that BL-ICA effectively removed CI artifacts. Comparison with existing method: The proposed method selectively removes CI artifacts from continuous EEG recordings, while ICA removal method shows residual peak and removes important brain activity signals. Conclusion: CI artifacts in EEG data obtained during continuous passive listening can be effectively removed with the aid of BL-ICA, opening up new EEG research possibilities in subjects with CIs. © 2015 Elsevier B.V.
URI
http://hdl.handle.net/20.500.11750/1560
DOI
10.1016/j.jneumeth.2015.07.020
Publisher
ELSEVIER SCIENCE BV
Related Researcher
  • Author Choi, Hong Soo Bio-Micro Robotics Lab
  • Research Interests Micro/Nano robot; Neural prostheses; MEMS; BMI; MEMS/NEMS; BioMEMS; MEMS 초음파 트랜스듀스; 인공와우
Files:
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Collection:
Information and Communication EngineeringCSI(Cyber-Physical Systems Integration) Lab1. Journal Articles
Robotics EngineeringBio-Micro Robotics Lab1. Journal Articles


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