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http://dx.doi.org/10.5391/JKIIS.2012.22.4.429

ERS Feature Extraction using STFT and PSO for Customized BCI System  

Kim, Yong-Hoon (중앙대학교 전자전기공학부)
Kim, Jun-Yeup (중앙대학교 전자전기공학부)
Park, Seung-Min (중앙대학교 전자전기공학부)
Ko, Kwang-Eun (중앙대학교 전자전기공학부)
Sim, Kwee-Bo (중앙대학교 전자전기공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.22, no.4, 2012 , pp. 429-434 More about this Journal
Abstract
This paper presents a technology for manipulating external devices by Brain Computer Interface (BCI) system. Recently, BCI based rehabilitation and assistance system for disabled people, such as patient of Spinal Cord Injury (SCI), general paralysis, and so on, is attracting tremendous interest. Especially, electroencephalogram (EEG) signal is used to organize the BCI system by analyzing the signals, such as evoked potential. The general findings of neurophysiology support an availability of the EEG-based BCI system. We concentrate on the event-related synchronization of motor imagery EEG signal, which have an affinity with an intention for moving control of external device. To analyze the brain activity, short-time Fourier transform and particle swarm optimization are used to optimal feature selection from the preprocessed EEG signals. In our experiment, we can verify that the power spectral density correspond to range mu-rhythm(${\mu}8$~12Hz) have maximum amplitude among the raw signals and most of particles are concentrated in the corresponding region. Result shows accuracy of subject left hand 40% and right hand 38%.
Keywords
Event-Related Synchronization; Brain Computer Interface; Particle Swarm Optimization;
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