Improved BCI performance with sequential hypothesis testing

Rong Liu, Geoffrey I. Newman, Sarah H. Ying, Nitish V. Thakor

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

Abstract

One of the primary challenges in noninvasive brain-computer interface (BCI) control is low information transfer rate (ITR). An approach that employs a power-based sequential hypothesis testing (SHT) technique is presented for real-time detection of motor commands. Electroencephalogram (EEG) recordings obtained during a BCI task were first analyzed with a hypothesis testing (HT) method. Using serial analysis we minimized the time to determine a cued motor imagery cursor control decision. Experimental results show that the accuracy of the SHT method was above 80% for all the subjects (n = 3). The average decision time was 3.4 s, as compared with 6.0 s for the HT method. Moreover, the proposed SHT method has three times the information transfer rate (ITR) compared with the HT method.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages4215-4218
Number of pages4
DOIs
StatePublished - Dec 26 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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