Student´s Oral Presentation III: Emotional State Classification Using Low-Cost Single-Channel Electroencephalography
F. López: MSc student: Cognitive Neuroscience; Rodrigo Sanz: MSc student: Cognitive Neuroscience
Universidad de la República, Montevideo, Uruguay
Hosted by IIBCE on Brain Science
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Abstract
Although electroencephalography (EEG) has been used in clinical and research studies for almost a century, recent technological advances have made the equipment and processing tools more accessible outside laboratory settings. These low-cost alternatives can achieve satisfactory results in experiments such as detecting event-related potentials and classifying cognitive states. In our research, we use low-cost single-channel EEG to classify brain activity during the presentation of images of opposite emotional valence from the OASIS database. Emotional classification has already been achieved using research-grade and commercial-grade equipment, but our approach pioneers the use of educational-grade equipment for said task. EEG data is collected with a Backyard Brains SpikerBox, a low-cost and open-source bioamplifier that can record a single-channel electric signal from a pair of electrodes placed on the scalp, and used to train machine learning classifiers.
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