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A visual keyboard system using hybrid dual frequency SSVEP based brain computer interface with VOG integration
Published in Institute of Electrical and Electronics Engineers Inc.
2018
Pages: 258 - 263
Abstract
The focus of this paper is to increase the number of targets and classification rate in the SSVEP-BCI visual keyboard system. The dual frequency steady state visual evoked potential (SSVEP) and video-oculography (VOG) based hybrid system has been developed in this study. The visual stimuli (targets) were designed using dual frequency SSVEP method. This method could create more targets through a suitable combination of limited number of frequencies. The keyboard screen was divided into three sections (left, middle and right), and each section visual stimuli/keys were designed with a unique set of frequencies. The webcam based video-oculography was used to detect the direction of the eye gaze. This selection reduces the issue of misclassification of SSVEP frequencies. Extended multivariate synchronization index (EMSI) method is used for SSVEP frequency recognition. Both online and offline experiments were conducted on 10 subjects and an average online detection accuracy of 94.987% was obtained with the information transfer rate (ITR) of 82.786 bits/minutes. ©2018 IEEE.
About the journal
JournalData powered by TypesetProceedings - 2018 International Conference on Cyberworlds, CW 2018
PublisherData powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
Open AccessNo
Concepts (13)
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    Computer keyboards
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    Hybrid systems
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    Interface states
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    Video recording
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    CLASSIFICATION RATES
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    INFORMATION TRANSFER RATE
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    Misclassifications
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    ON-LINE DETECTION
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    STEADY STATE VISUAL EVOKED POTENTIALS
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    SYNCHRONIZATION INDEX
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    VIDEO OCULOGRAPHY
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    VISUAL STIMULUS
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    BRAIN COMPUTER INTERFACE