Classification of visual stimuli using brain-computer interfaces by synchronously decoding reactive EEG signals: A novel approach

Artificial intelligence and machine learning have been on a sharp rise in the last few years. One reason behind their popularity, is their usefulness as they can be seen in multiple fields including medicine and biology. Brain-computer interfaces are one of the many systems that have been developed and enhanced due to machine learning. In this work, we classify visual stimuli using an electroencephalogram-based brain-computer interface. The experimental results, applied on small data sets, are promising.