Online cue-based discrimination of left / right hand movement imagination

Brain Computer Interface (BCI) is a system in which people can interact with electronic devices without using any body movement but only the brain activity itself. In this system, the brain signals obtained from the scalp surface are analysed from the EEG records. Aiming the discrimination of left a...

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Published in2010 15th National Biomedical Engineering Meeting pp. 1 - 4
Main Authors Akıncı, Berna, Gençer, Nevzat Güneri
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2010
Subjects
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ISBN1424463807
9781424463800
DOI10.1109/BIYOMUT.2010.5479773

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Abstract Brain Computer Interface (BCI) is a system in which people can interact with electronic devices without using any body movement but only the brain activity itself. In this system, the brain signals obtained from the scalp surface are analysed from the EEG records. Aiming the discrimination of left and right hand movement imaginations (2 classes), an online cue-based BCI system has been developed in this study. In the offline analysis, feature extraction is performed by using Distinctive-Sensitive Learning Vector Quantization and Time-Frequency Analysis methods and training model is created from these features. This model is used in online classification and the result is given as a feedback. Using these methods, the cross-validation accuracy of the offline system is found to be 87% which yields an online prediction accuracy of 97% on a single subject.
AbstractList Brain Computer Interface (BCI) is a system in which people can interact with electronic devices without using any body movement but only the brain activity itself. In this system, the brain signals obtained from the scalp surface are analysed from the EEG records. Aiming the discrimination of left and right hand movement imaginations (2 classes), an online cue-based BCI system has been developed in this study. In the offline analysis, feature extraction is performed by using Distinctive-Sensitive Learning Vector Quantization and Time-Frequency Analysis methods and training model is created from these features. This model is used in online classification and the result is given as a feedback. Using these methods, the cross-validation accuracy of the offline system is found to be 87% which yields an online prediction accuracy of 97% on a single subject.
Author Akıncı, Berna
Gençer, Nevzat Güneri
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  givenname: Nevzat Güneri
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  fullname: Gençer, Nevzat Güneri
  email: ngencer@metu.edu.tr
  organization: Elektr. ve Elektron. Muhendisligi Bolumu, Orta Dogu Teknik Univ., Ankara, Turkey
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Snippet Brain Computer Interface (BCI) is a system in which people can interact with electronic devices without using any body movement but only the brain activity...
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SubjectTerms Brain Computer Interface
Brain computer interfaces
Brain modeling
cue-based BCI
EEG
Electroencephalography
Feature extraction
Feedback
motor imagery
online
Performance analysis
Scalp
Signal analysis
Time frequency analysis
Vector quantization
Title Online cue-based discrimination of left / right hand movement imagination
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