Classification of Imaginary Tasks from Three Channels of EEG by Using an Artificial Neural Network

J. Deng*, B. He

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

We used an Artificial Neural Network to recognize imaginary left or right hand movements from scalp recorded EEG signals. Subjects were asked to imagine moving their left or right hand when indicated by a visual cue. Three channels were used in the present study to test the feasibility of a practical Brain Computer Interface system. C3, C4, and Fz were selected based on the fact that they showed distinct difference between power spectrum density (PSD) of imaginary left and right hand movements. The PSD features of the three channels were fed onto the artificial neural network and the output was left or right imaginary movement. Testing results in three subjects with 90 trials show an average success rate of 72.2%.

Original languageEnglish (US)
Pages (from-to)2289-2291
Number of pages3
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume3
StatePublished - 2003
EventA New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico
Duration: Sep 17 2003Sep 21 2003

Keywords

  • Artificial Neural Network (ANN)
  • Brain computer interface (BCI)
  • Electroencephalogram (EEG)
  • Movement imagination

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Classification of Imaginary Tasks from Three Channels of EEG by Using an Artificial Neural Network'. Together they form a unique fingerprint.

Cite this