Title
Gaming controlling via brain-computer interface using multiple physiological signals
Abstract
Using physiological signals to control brain-computer interface (BCI) becomes more popular. Among many kinds of physiological signals, Electrooculography (EOG) signal is more stable which can be used to control BCI systems based on eye movement detection and signal processing methods. Also, the use of electroencephalographic (EEG) signals has become the most common approach for a BCI because of their usability and strong reliability. In this paper, we described a signal processing method, which uses a wireless EEG-based BCI system designed to be worn near forehead that can detect both EEG and EOG signals, for detecting eye movements to have 9 direction controls (via EOG) and one action of execution (via EEG). This system included a wireless EEG signal acquisition device, a mechanism that can be worn stably, and an application program (APP) with signal processing algorithms. This algorithm and its classification procedure provided an effective method for identifying eye movements and attention. Finally, we designed a baseball game to test the BCI system. The results demonstrated that player can control the game well with high accuracy.
Year
DOI
Venue
2014
10.1109/SMC.2014.6974413
SMC
Keywords
Field
DocType
game control,electroencephalographic,medical signal detection,eye movement detection,baseball,physiology,signal processing methods,electroencephalography,brain-computer interfaces,wireless,gaze tracking,electrooculography,eog signal,electrooculography signal,application program,app,baseball game,electro-oculography,signal classification,eeg signals,wireless eeg signal acquisition device,brain-computer interface control,brain-computer interface,physiological signals,algorithm,wireless eeg-based bci system,electroencephalographic signals,computer games
Computer vision,Signal processing,Wireless,Computer science,Usability,Brain–computer interface,Speech recognition,Electrooculography,Eye movement,Baseball game,Artificial intelligence,Electroencephalography
Conference
ISSN
Citations 
PageRank 
1062-922X
0
0.34
References 
Authors
4
5
Name
Order
Citations
PageRank
Shi-An Chen16611.51
Chih-Hao Chen200.34
Jheng-Wei Lin300.68
Li-Wei Ko451958.70
Chin-Teng Lin53840392.55