Classify four imagined objects with eeg signals
EEG signals contain information directly related to cognitive activity. This paper presents a method to classify the images a person imagines via the information provided by the EEG signals. The images relating to the objects `tree', `house', `plane' and `dog' have been reconstructed. We have used a...
| Authors: | ; ; ; |
|---|---|
| Format: | Article |
| Status: | Accepted version |
| Publication date: | 2021 |
| Country: | España |
| Institution: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repository: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/19329 |
| Online Access: | http://hdl.handle.net/10256/19329 |
| Access Level: | Open access |
| Keyword: | Intel·ligència artificial Aprenentatge automàtic Artificial intelligence Machine learning |
| _version_ | 1878732044179079168 |
|---|---|
| author | Llorella Costa, Fabio Ricardo |
| author2 | Íáñez, Eduardo Azorín, José M. Patow, Gustavo |
| author2_role | author author author |
| author_browse | Azorín, José M. Llorella Costa, Fabio Ricardo Patow, Gustavo Íáñez, Eduardo |
| author_facet | Llorella Costa, Fabio Ricardo Íáñez, Eduardo Azorín, José M. Patow, Gustavo |
| author_role | author |
| collection | Recercat. Dipósit de la Recerca de Catalunya |
| description | EEG signals contain information directly related to cognitive activity. This paper presents a method to classify the images a person imagines via the information provided by the EEG signals. The images relating to the objects `tree', `house', `plane' and `dog' have been reconstructed. We have used a convolutional network to obtain the reconstruction of the images and a genetic algorithm to find the parameters of the network. The results obtained have been evaluated by means of a Chebychev metric of comparison of images, and this shows that the reconstruction is performed with a success of 57% over chance, with an accuracy in the classification of 60% and a kappa value of 0.40, demonstrating that the classification of five mental states where four of them come from the visual imagery is possible |
| eu_rights_str_mv | openAccess |
| format | article |
| id | ES_3bbf4b8236c53da646477449e9cc28ce |
| institution | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| instname_str | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| network_acronym_str | ES |
| network_name_str | España |
| oai_identifier_str | oai:recercat.cat:10256/19329 |
| publishDate | 2021 |
| publishDateSort | 2021 |
| publisher | Springer |
| publisherStr | Springer |
| reponame_str | Recercat. Dipósit de la Recerca de Catalunya |
| spelling | Classify four imagined objects with eeg signals Llorella Costa, Fabio Ricardo Íáñez, Eduardo Azorín, José M. Patow, Gustavo Intel·ligència artificial Aprenentatge automàtic Artificial intelligence Machine learning EEG signals contain information directly related to cognitive activity. This paper presents a method to classify the images a person imagines via the information provided by the EEG signals. The images relating to the objects `tree', `house', `plane' and `dog' have been reconstructed. We have used a convolutional network to obtain the reconstruction of the images and a genetic algorithm to find the parameters of the network. The results obtained have been evaluated by means of a Chebychev metric of comparison of images, and this shows that the reconstruction is performed with a success of 57% over chance, with an accuracy in the classification of 60% and a kappa value of 0.40, demonstrating that the classification of five mental states where four of them come from the visual imagery is possible This work was partially funded by the project TIN2017-88515-C2-2-R from Ministerio de Ciencia, Innovaci´on y Universidades, Spain Springer http://hdl.handle.net/10256/19329 |
| spellingShingle | Classify four imagined objects with eeg signals Llorella Costa, Fabio Ricardo Intel·ligència artificial Aprenentatge automàtic Artificial intelligence Machine learning |
| status_str | acceptedVersion |
| title | Classify four imagined objects with eeg signals |
| title_full | Classify four imagined objects with eeg signals |
| title_fullStr | Classify four imagined objects with eeg signals |
| title_full_unstemmed | Classify four imagined objects with eeg signals |
| title_short | Classify four imagined objects with eeg signals |
| title_sort | Classify four imagined objects with eeg signals |
| topic | Intel·ligència artificial Aprenentatge automàtic Artificial intelligence Machine learning |
| topic_facet | Intel·ligència artificial Aprenentatge automàtic Artificial intelligence Machine learning |
| url | http://hdl.handle.net/10256/19329 |