Motor imagery task discrimination using wide-band frequency spectra with slepian tapers

M. Kamrunnahar, A. Geronimo

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

Abstract

We here studied the efficacy of wide-band frequency spectra (WBFS) features using multi-taper (MT) spectral analysis in application to motor imagery based Brain Computer Interfaces. We acquired motor imagery task related human scalp electroencephalography (EEG) signals for left vs. right hand movements using 3 different pairs of visual arrow cues. Left vs. right movement imagery discrimination was conducted using a Naïve Bayesian classifier using WBFS features and commonly used Mu-Beta spectral features for EEG signals from central+parietal and central only electrode positions. Task discrimination accuracy results showed that WBFS features using MT spectral analysis provided significantly better performance (with a 95% confidence level) than that of using Mu-Beta spectral features commonly used. The use of central+parietal electrode signals improved discrimination accuracy significantly when compared to the accuracy using the central only signals, implying that sensory information enhanced task discrimination significantly.

Original languageEnglish (US)
Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Pages3349-3352
Number of pages4
DOIs
Publication statusPublished - Dec 1 2010
Event2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
Duration: Aug 31 2010Sep 4 2010

Publication series

Name2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Other

Other2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
CountryArgentina
CityBuenos Aires
Period8/31/109/4/10

    Fingerprint

All Science Journal Classification (ASJC) codes

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

Cite this

Kamrunnahar, M., & Geronimo, A. (2010). Motor imagery task discrimination using wide-band frequency spectra with slepian tapers. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 (pp. 3349-3352). [5627899] (2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10). https://doi.org/10.1109/IEMBS.2010.5627899