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• W1519382844 abstract "EEG-controlled gaming applications range widely from strictly medical to completely nonmedical applications. Games can provide not only entertainment but also strong motivation for practicing, thereby achieving better control with rehabilitation system. In this paper we present real-time control of video game with eye movements for asynchronous and noninvasive communication system using two temporal EEG sensors. We used wavelets to detect the instance of eye movement and time-series characteristics to distinguish between six classes of eye movement. A control interface was developed to test the proposed algorithm in real-time experiments with opened and closed eyes. Using visual feedback, a mean classification accuracy of 77.3% was obtained for control with six commands. And a mean classification accuracy of 80.2% was obtained using auditory feedback for control with five commands. The algorithm was then applied for controlling direction and speed of character movement in two-dimensional video game. Results showed that the proposed algorithm had an efficient response speed and timing with a bit rate of 30 bits/min, demonstrating its efficacy and robustness in real-time control." @default.
• W1519382844 created "2016-06-24" @default.
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• W1519382844 date "2015-01-01" @default.
• W1519382844 modified "2023-10-10" @default.
• W1519382844 title "Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors" @default.
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• W1519382844 doi "https://doi.org/10.1155/2015/653639" @default.
• W1519382844 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4672363" @default.
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