Time delay estimation of event related potential (ERP) signals

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Electroencephalogram (EEG) is a brain signal that has much information of human thought and health. For this reason, the current study on clinical brain research and brain machine interface (BMI) uses EEG signal in many applications. Due to the significant noise in EEG, signal processing to enhance signal to noise power ratio (SNR) is necessary for EEG research. The typical method is averaging many trials of ERP (event related potential) signal that represents a brain response of a particular stimulus or a task. The averaging, however, is very sensitive to timing error. In this study, we propose a time delay estimation based on simplified maximum likelihood (ML) criterion. The simulation result shows the performance of proposed scheme provides better performance than conventional schemes employing averaged signal as a reference.

Original languageEnglish
Title of host publicationISCE 2014 - 18th IEEE International Symposium on Consumer Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479945924
DOIs
StatePublished - 2014
Event18th IEEE International Symposium on Consumer Electronics, ISCE 2014 - Jeju, Korea, Republic of
Duration: 22 Jun 201425 Jun 2014

Publication series

NameProceedings of the International Symposium on Consumer Electronics, ISCE

Conference

Conference18th IEEE International Symposium on Consumer Electronics, ISCE 2014
Country/TerritoryKorea, Republic of
CityJeju
Period22/06/1425/06/14

Keywords

  • EEG
  • ERP
  • synchronization
  • time delay

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