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Convolutional Network for EEG-Based Biometric

2018; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-319-75193-1_72

1611-3349

Thiago Schons, Gladston Moreira, Pedro Silva, Vitor N. Coelho, Eduardo Luz,

Functional Brain Connectivity Studies

The global expansion of biometric systems promotes the emergence of new and more robust biometric modalities. In that context, electroencephalogram (EEG) based biometric interest has been growing in recent years. In this study, a novel approach for EEG representation, based on deep learning, is proposed. The method was evaluated on a database containing 109 subjects, and all 64 EEG channels were used as input to a Deep Convolution Neural Network. Data augmentation techniques are explored to train the deep network and results showed that the method is a promising path to represent brain signals, overcoming baseline methods published in the literature.