http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Feature extraction of EEG during motor imagery and cognition by using morphological MRA
Tomonari Yamaguchi,Mitsuhiko Fujio,Katsuhiro Inoue,Gert Pfurtscheller 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
Electroencephalograph (EEG) recordings during right and left hand motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. Recently, we have proposed the detection method of Error Potential in order to add the fail safe function to BCI system. In this paper, feature extraction method based on morphological multi-resolution analysis is introduced to extract features concerned with motor imagery and cognition simultaneously from EEG signals. Morphological filter is composed of nonlinear operation between signal and structural function. We propose some design methods of structural function that decide the filter characteristic of morphology. These algorithms are compared to DWT from the view point of filter characteristics. Consequently, effectiveness of our method is confirmed.
Feature Extraction from EEG Signals in P300 Spelling System
Kana Omori,Tomonari Yamaguchi,Katsuhiro Inoue 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
Recently, there are many studies on brain computer interface (BCI) system and some use EEG response at oddball paradigms. The aim of this paper is to extract feature (i.e. P300 response) from the EEG signals to improve the spelling system. We propose the method to analyze the averaged EEG signal concerned time and spatial. It is confirmed that the processing period with feature extraction is able to be shortened by averaging multi-channels. Effective information is obtained from the EEG signal near of the center part.