Electroencephalographic based brain computer interface for unspoken speech

TitreElectroencephalographic based brain computer interface for unspoken speech
Type de publicationCommunication
TypeCommunication avec actes dans un congrès
Année2017
LangueAnglais
Date du colloque12-14/09/2017
Titre du colloqueSenset 2017. International Conference on Sensors, Networks, Smart and Emerging Technologies
Titre des actes ou de la revue2017 Sensors Networks Smart and Emerging Technologies (SENSET)
Pagination1 - 4
AuteurAbdallah, Nassib, Daya, Bassam, Khawandi, Shadi, Chauvet, Pierre
PaysLiban
EditeurIEEE
VilleBeyrouth
Mots-clésarticial neural network, Biological neural networks, Brain Computer Interface methodology, brain-computer interfaces, data classification, database construction, Databases, electroencephalographic based brain computer interface, Electroencephalography, English words, feature extraction, features extraction, features vectors, neural nets, noise elimination methodology, signal classification, speech recognition, unspoken speech recognition
Résumé en anglais

This paper presents a Brain Computer Interface methodology for unspoken speech recognition based on Electroencephalography (EEG). Each phase within this approach is presented and discussed, followed by the noise elimination methodology and ends up by features extraction and data classification. The presented work consists of database construction with features vectors that will be classified into different classes by applying an articial neural network with three layers. The proposed approach provides results with high percentage of recognition (93% Testing, 95% Validation) when applied on two English words ON/OFF acquired from 2 different resources.

URL de la noticehttp://okina.univ-angers.fr/publications/ua17060
DOI10.1109/SENSET.2017.8125026