Abstract
Brain computer interfaces (BCI) are applications that allows user to interact with their environment through their brain waves patterns, in this context the detection of eye blinks seems a good way to perform basic interactions. Electroencephalography (EEG) are methods that allows recording of brain waves through invasives or non invasives methods, in the cases of BCI application the lesser the invasiveness the higher the applicability. As this work will focus on pattern recognition within brain waves we developped a machine learning based approach to detect and classify different actions. Additionnaly the differentiation for each eye allows better interactivity for BCI applications.
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