Yazarlar

• Kayikcioglu, Temel(2)
• Manshouri, Negin(2)
• Maleki, Masoud(1)
• Melek, Mesut(1)

• MakaleAçık Erişim2020/r/gumushane/14945
  Low-cost brain-computer interface using the emotiv epoc headset based on rotating vanes

  Melek, Mesut; Manshouri, Negin; Kayikcioglu, Temel

  In the brain-computer interface system (BCI), electroencephalography (EEG) signals are converted into digital signals and analyzed, allowing direct communication between humans and the electronic devices around them. The convenience of the user and the speed of communication with the surrounding devices are the most important challenges of BCI systems. The Emotiv Epoc headset minimizes the discomfort of the user thanks to its wet electrodes and easy handling. In the continuation of our previous works, in this paper, we developed our BCI system based on the gaze at the rotating vanes using the inexpensive Emotiv Epoc headset. In addition to user comfort, our design has an acceptable mean accuracy rate (ACC) and mean information transfer rate (ITR) compared to similar systems.

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• BildiriYalnız künye2018/r/gumushane/15021
  Fast and accurate classifier-based brain-computer interface system using single channel EEG data

  Maleki, Masoud; Manshouri, Negin; Kayikcioglu, Temel

  In brain-computer interface system (BCIs), direct communication between humans and computers is performed by analyzing neural signals and transforming them into digital signals. In the continuation of our previous works, in this paper, we advanced the proposed BCI system that was based on the gaze on rotating vanes. The speed of communication and convenience of the user are very important factors in BCI systems. Therefore, in this paper, for the convenience of the user, a single EEG channel was used. Also, for to increase the speed of the system, we tried to the classification of 0.5 sec epochs with a partial least squares regression (PLSR) as a fast classifier. In addition, we computed the information transfer rate (ITR) that has proved our proposed BCI system is fast and accurate. This system could be used in real-time implementations due to having high classification rate, speed and convenience of the user.

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