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The ability to acquire Electroencephalogram (EEG) signals from the brain has led to the development of Brain Computer Interfaces (BCI), which capture signals generated by the physical processes in the brain and use them to control external devices. In this paper, we establish an application to control a robot on the Arduino platform by the use of a BCI system, which does not require training for individual...
A Brain Computer Interfaces (BCI) system enables users to control devices by acquiring and processing brain activity. An important component of a BCI system is feature extraction, which is responsible for representing brain signals in terms of essential components called features. This paper presents a comparison of the following feature extraction techniques for BCI; Common Spatial Patterns (CSP),...
Eye blinks and lateral eye movements are prominent in EEG signals which are obtained by placing electrodes in the frontal region of the brain. This paper presents a machine learning approach to detect eye movements and blinks from EEG data and map them as intents to control external devices like a computer desktop or a wheel chair.
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