Elképzelt motoros tevékenységek EEG-alapú osztályozása neurális hálózatok használatával
EEG-based classification of motor imagery activities using neural networks
Keywords:
EEG, neural network, classification, activity recognition, data segmentation, neurális hálózat, osztályozás, tevékenységfelismerés, adatszegmentálásAbstract
EEG-based classification of motor imagary activities is often performed using neural networks. In this article, we examined the effect of data segmentation and different neural network structures. By applying proper window size and using a purely convolutional neural network, we achieved 97.7% recognition accuracy on data from twenty subjects in three classes, which outperforms several networks used in previous research.
Kivonat
Az elképzelt motoros tevékenységek EEG-alapú osztályozását gyakran neurális hálózatok segítségével végzik. Ebben a cikkben az adatszegmentáció és különböző neurális hálózati struktúrák hatását vizsgáltuk. Megfelelő ablakméret alkalmazásával és egy tisztán konvolúciós neurális háló használatával 97,7%-os felismerési pontosságot értünk el húsz alany adatain három osztályban, ami több, a korábbi kutatásokban használt hálózatot felülmúl.
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