Gaming controlling via brain-computer interface using multiple physiological signals

Shi An Chen, Chih Hao Chen, Jheng Wei Lin, Li-Wei Ko, Chin Teng Lin

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

using physiological signals to control braincomputer 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.

Original languageEnglish
Article number6974413
Pages (from-to)3156-3159
Number of pages4
JournalConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2014-January
Issue numberJanuary
DOIs
StatePublished - 1 Jan 2014
Event2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014 - San Diego, United States
Duration: 5 Oct 20148 Oct 2014

Keywords

  • Algorithm
  • Baseball
  • Electroencephalographic
  • Electrooculography
  • Eye movement detection
  • Signal processing methods
  • Wireless

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