A collaborative BCI system based on P300 signals as a new tool for life log indexing

• Published in: 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) pp. 2843 - 2846
• Main Author: Touyama, Hideaki
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-10-2014
• Subjects: Accuracy; Big data; Collaboration; Collaborative Brain-Computer Interface (BCI); ElectroEncephaloGram (EEG); Electroencephalography; Event-Related Potential (ERP); Feature extraction; Global Positioning System; Global Positioning System (GPS); Indexing; Life Log; P300; Signal processing
• ISSN: 1062-922X; 2577-1655
• DOI: 10.1109/SMC.2014.6974360

Analyses on single-trial ElectroEncephaloGram (EEG) have been investigated toward realizing real-time Brain-Computer Interface (BCI). In general, the information transfer rates of current BCI systems with single-trial EEG are generally lower than those with averaging EEG. In recent years, the concept of collaborative EEG analyses has been proposed with the purpose of improving the BCI performances with collaborative single-trial EEGs of individuals. In this paper, a collaborative BCI system is developed based on P300 evoked potentials. The collaborative BCI system with Global Positioning System (GPS) can be operated with three subjects by using three wearable EEG recording devices and wireless communications. As the results, the P300 waveforms could be observed and it was found that the collaborative P300 analyses could improve the BCI performances than individual P300 analyses. The result of this study is to be applied to P300-based big data mining and life log indexing, in particular, in outdoor environment.