BCI-Based Smart Room Control using EEG Signals


  • Oger Zaya Amanuel Department of Mechatronics Engineering/ Al-Khwarizmi College of Engineering/ University of Baghdad
  • Yarub Alazzawi Department of Mechatronics Engineering/ Al-Khwarizmi College of Engineering/ University of Baghdad




In this paper, we implement and examine a Simulink model with electroencephalography (EEG) to control many actuators based on brain waves. This will be in great demand since it will be useful for certain individuals who are unable to access some control units that need direct contact with humans. In the beginning, ten volunteers of a wide range of (20-66) participated in this study, and the statistical measurements were first calculated for all eight channels. Then the number of channels was reduced by half according to the activation of brain regions within the utilized protocol and the processing time also decreased. Consequently, four of the participants (three males and one female) were chosen to examine the Simulink model during different actions. The model contained: input signals, data selection according to the activation regions in the brain, features extraction, classification according to the frequency ranges of each action, and an interface with an embedded system to control the actuators.



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How to Cite

BCI-Based Smart Room Control using EEG Signals. (2022). Al-Khwarizmi Engineering Journal, 18(4), 60-72. https://doi.org/10.22153/kej.2022.09.004