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Creators/Authors contains: "Ganesan, Karthikeyan"

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  1. ; ; (, Abstract Book of the 8th International Brain-Computer Interface Meeting)
    Brain Computer Interfaces (BCIs) traditionally deploy visual or auditory stimuli to elicit brain signals. However, these stimuli are not very useful in situations where the visual or auditory senses are involved in other decision making processes. In this paper, we explore the use of vibrotactile stimuli on the fi ngers as a viable replacement. Using a fi ve-level Wavelet Packet feature extraction on the obtained EEG signals, along with a kernel Support Vector Machine (SVM) algorithm, we were able to achieve 83% classi cation accuracy for binary user choices. This new BCI paradigm shows potential for use in situations where visual and auditory stimuli are not feasible. 
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