Title :
Eye-moving assisted EEG acquisition and EEG feature detection
Author :
Sun, Yao ; Luo, Zhi-zeng ; Meng, Jun
Author_Institution :
Robot Res. Inst., Hangzhou Dianzi Univ., Hangzhou, China
Abstract :
Brain-computer interface research focused on using scalp electroencephalogram(EEG) to control outer device. The key problem is to optimize the method of signal acquisition and signal procession in the BCI research field. Appropriate method is helpful to recognize the person´s intent by EEG rapidly and accurately. A novel EEG acquisition method is proved in this paper. It is to acquire EEG assisted by eye-moving. Without external stimulus or specialized training, the eye-moving assisted method can enhance the feature of EEG. The single trial, single channel eye-moving assisted motor imagery EEG and simply motor imagery EEG are acquired. Various types of eye-moving assisted EEG can be distinguished visually. The nonlinear features of various EEG are detected and analyzed. The results show that the nonlinear features of eye-moving assisted motor imagery EEG are more significance.
Keywords :
brain-computer interfaces; electroencephalography; eye; feature extraction; medical control systems; medical signal detection; EEG feature detection; brain-computer interface; eye-moving assisted EEG acquisition; motor imagery EEG; nonlinear feature detection; scalp electroencephalogram; signal acquisition; signal processing; Biomedical engineering; Brain computer interfaces; Conferences; Electroencephalography; Feature extraction; Prosthetics; Robots; EEG; acquisition; feature detection;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554123