Electroencephalograph (eeg) Based Brain Computer Interface (bci) for Controlling Real Time Robot Arm
نویسندگان
چکیده
In this paper, development of non-invasive neural signals to drive a 2R robotic arm is presented. A brain computer interface based on steady state visual evoked potentials (SSVEP) is used. For stimulation stimuli arrow with different colours (red, black and violet) is used that flicker with different frequencies of 6.5 and 8.2 Hz respectively. PYTHON is used for online signal acquisition and MATLAB signal processing and analysis tool is used to analyse signals. Emotiv EPOC and Arduino are used as hardware devices to receive and transmit signals respectively. At last, signals are given as a commands through Arduino to a hardware experimental setup. The goal of our study is to control navigation of robot “turn right”, “turn left” through neural signals acquired by EEG database.
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