Enhancement of performance of an EEG-based brain-computer interface by means of a Time-Frequency approach

N. Yamawaki, Christopher T Wilke, Z. M. Liu, Bin He

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

We have developed a novel Time-Frequency approach of classification of motor imagery (MI) tasks for brain-computer interface (BCI) applications. Through off-line data analysis on data collected during a "cursor control" experiment, we evaluated the capability of our proposed method in revealing the major features of the EEG control and enhancing MI classification accuracy. The pilot results in two human subjects are promising, with a mean accuracy rate of 87.9%, suggesting the feasibility of defining a new and more reliable EEG-based BCI.

Original languageEnglish (US)
Pages94-96
Number of pages3
DOIs
StatePublished - Dec 1 2005
Event2nd International IEEE EMBS Conference on Neural Engineering, 2005 - Arlington, VA, United States
Duration: Mar 16 2005Mar 19 2005

Other

Other2nd International IEEE EMBS Conference on Neural Engineering, 2005
CountryUnited States
CityArlington, VA
Period3/16/053/19/05

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    Yamawaki, N., Wilke, C. T., Liu, Z. M., & He, B. (2005). Enhancement of performance of an EEG-based brain-computer interface by means of a Time-Frequency approach. 94-96. Paper presented at 2nd International IEEE EMBS Conference on Neural Engineering, 2005, Arlington, VA, United States. https://doi.org/10.1109/CNE.2005.1419561