A Deep Learning Approach for Classification of Reaching Targets from EEG Images

Schubert R. Carvalho, Iraquitan Cordeiro Filho, Damares Oliveira De Resende, Ana Carolina Siravenha, Cleidson De Souza, Henrique Galvan Debarba, Bruno Gomes, Ronan Boulic

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16 Citationer (Scopus)

Abstract

In this paper, we propose a new approach for the classification of reaching targets before movement onset, during visually-guided reaching in 3D space. Our approach combines the discriminant power of two-dimensional Electroencephalography (EEG) signals (i.e., EEG images) built from short epochs, with the feature extraction and classification capabilities of deep learning (DL) techniques, such as the Convolutional Neural Networks (CNN). In this work, reaching motions are performed into four directions: left, right, up and down. To allow more natural reaching movements, we explore the use of Virtual Reality (VR) to build an experimental setup that allows the subject to perform self-paced reaching in 3D space while standing. Our results reported an increase both in classification performance and early detection in the majority of our experiments. To our knowledge this is the first time that EEG images and CNN are combined for the classification of reaching targets before movement onset.

OriginalsprogEngelsk
TitelProceedings - 30th Conference on Graphics, Patterns and Images, SIBGRAPI 2017
Antal sider7
ForlagIEEE Signal Processing Society
Publikationsdato3 nov. 2017
Sider178-184
Artikelnummer8097310
ISBN (Elektronisk)9781538622193
DOI
StatusUdgivet - 3 nov. 2017
Begivenhed30th Conference on Graphics, Patterns and Images, SIBGRAPI 2017 - Niteroi, Rio de Janeiro, Brasilien
Varighed: 17 okt. 201720 okt. 2017

Konference

Konference30th Conference on Graphics, Patterns and Images, SIBGRAPI 2017
Land/OmrådeBrasilien
ByNiteroi, Rio de Janeiro
Periode17/10/201720/10/2017
SponsorCapes, CNPq, Globo.com, IBM, NVIDIA
NavnProceedings - 30th Conference on Graphics, Patterns and Images, SIBGRAPI 2017

Bibliografisk note

Publisher Copyright:
© 2017 IEEE.

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