Skip to main navigation Skip to search Skip to main content

Initial assessment of artifact filtering for rsvp keyboard™

  • Marzieh Haghighi
  • , Murat Akcakaya
  • , Umut Orhan
  • , Deniz Erdogmus
  • , Barry Okeny
  • , Melanie Fried-Okeny

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

RSVP KeyboardTM is an electroencephalography (EEG)-based spelling interface that uses evoked response potential classification with the help of language models. As in any brain computer interface, severe physiological and environmental signal artifacts that affect signal quality in EEG are a detriment to performance. To alleviate the negative effects of such artifacts on RSVP KeyboardTM, we implemented a filter that is based on an existing methodology from the literature. Using statistical modeling of pre-recorded EEG that includes three types of artifacts intentionally generated by operators, we perform Monte Carlo simulations of copy-phrase tasks and analyze the effect of artifact filtering on estimated typing performance. The presented results demonstrate an evidence against the usability of the tested method for online artifact reduction applications.

Original languageEnglish (US)
Title of host publication2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013
PublisherIEEE Computer Society
ISBN (Print)9781479930074
DOIs
StatePublished - 2013
Event2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013 - Brooklyn, NY, United States
Duration: Dec 7 2013Dec 7 2013

Publication series

Name2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013

Conference

Conference2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013
Country/TerritoryUnited States
CityBrooklyn, NY
Period12/7/1312/7/13

Keywords

  • Artifact Filtering
  • EEG
  • ERP. Language Model
  • Independent Component Analysis
  • Kernel Density Estimate

ASJC Scopus subject areas

  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'Initial assessment of artifact filtering for rsvp keyboard™'. Together they form a unique fingerprint.

Cite this