Comparative analysis of two-group supervised classification algorithms in the study of P300-based brain-computer interface
Artykuł w czasopiśmie
MNiSW
5
spoza listy
| Status: | |
| Autorzy: | Plechawska-Wójcik Małgorzata, Kaczorowska Monika, Michalik Bernadetta |
| Dyscypliny: | |
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| Rok wydania: | 2019 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Wolumen/Tom: | 252 |
| Numer artykułu: | 3010 |
| Strony: | 1 - 6 |
| Web of Science® Times Cited: | 1 |
| Bazy: | Web of Science |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | TAK |
| Nazwa konferencji: | III International Conference of Computational Methods in Engineering Science (CMES’18) |
| Skrócona nazwa konferencji: | CMES’18 |
| URL serii konferencji: | LINK |
| Termin konferencji: | 22 listopada 2018 do 24 listopada 2018 |
| Miasto konferencji: | Kazimierz Dolny |
| Państwo konferencji: | POLSKA |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Witryna wydawcy |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Data opublikowania w OA: | 14 stycznia 2019 |
| Abstrakty: | angielski |
| The main goal of the paper is to perform a comparative accuracy analysis of the two-group classification of EEG data collected during the P300-based brain-computer interface tests. The brain-computer interface is a technology that allows establishing communication between a human brain and external devices. BCIs may be applied in medicine to improve the life of disabled people and as well for entertainment. The P300 is an event-related potential (ERP) appearing about 300 ms after the occurrence of the stimulus of visual, auditory or sensory nature. It is based on the phenomenon observed in anticipation for a target event among non-target events. The 21-channel 201 Mitsar amplifier was used during the experiment to store EEG data from seven electrodes placed on the dedicated cap. The study was conducted on a group of five persons using P300 scenario available in OpenVibe software. The experiment was based on three steps the classifier learning process, comparison and averaging of the obtained result and the final test of the classifier. The comparative analysis was performed with the application of two supervised classification methods: Linear Discriminant Analysis (LDA) and Multi-layer Perceptron (MLP). The preliminary data analysis, extraction and feature selection was performed prior to the classification. |
