Title :
Hybrid EEG-NIRS based BCI for quadcopter control
Author :
M. Jawad Khan;Keum-Shik Hong;Noman Naseer;M. Raheel Bhutta
Author_Institution :
School of Mechanical Engineering, Pusan National University, Busan, Republic of Korea
fDate :
7/1/2015 12:00:00 AM
Abstract :
In this paper, we have proposed a novel control strategy for a quadcopter control using brain signals. A brain-computer interface (BCI) technology is developed using hybrid electroencephalography - near-infrared spectroscopy (EEG-NIRS) system and two commands are used to operate the quadcopter. An active brain signal upon the user´s own will is generated using a motor imagery task and a reactive brain signal is generated by visual flickering of light. The reactive command is used for the triggering control of the quadcopter and the active command is used to navigate the quadcopter in the forward direction. Linear discriminant analysis is used to classify the brain activity in offline environment. The results indicate that the proposed scheme is suitable for the BCI control applications.
Keywords :
"Electroencephalography","Brain-computer interfaces","Accuracy","Spectroscopy","Visualization","Robots","Electrodes"
Conference_Titel :
Society of Instrument and Control Engineers of Japan (SICE), 2015 54th Annual Conference of the
DOI :
10.1109/SICE.2015.7285434