A design and implementation of multi-character classification scheme based on motor imagery EEG signals

• Published in: Neuroscience Vol. 538; pp. 22 - 29
• Main Authors: Pan, Hongguang, Zhang, Yibo, Li, Li, Qin, Xuebin
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 06.02.2024
• Subjects: electroencephalogram; K-nearst neighbors; kernel principal components analysis; Motor-imagery-based brain-computer interface; Motor-imagery-based brain-computer interface; K-nearst neighbors; kernel principal components analysis; electroencephalogram

•We design a multi-classification scheme based on 29 electroencephalogram characters.•We use three methods for feature extraction and compare the results.•We use four classifiers for 29 classification and compare the results.•The final 29 classification accuracy using KNN and KPC is 96.2%. In the fi...