Multi-Scale Feature Extraction to Improve P300 Detection in Brain–Computer Interfaces

• Published in: Electronics (Basel) Vol. 14; no. 3; p. 447
• Main Authors: Usman, Muhammad, Lin, Chun-Ling, Chen, Yao-Tien
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2025
• Subjects: Accuracy; Adaptability; Artificial neural networks; Brain research; Classification; Comparative analysis; Competition; Datasets; Deep learning; Discriminant analysis; Electroencephalography; Feature extraction; Human-computer interface; Machine learning; Methods; Neural networks; Signal to noise ratio

P300 detection is a difficult task in brain–computer interface (BCI) systems due to the low signal-to-noise ratio (SNR). In BCI systems, P300 waves are generated in electroencephalogram (EEG) signals using various oddball paradigms. Convolutional neural networks (CNNs) have previously shown excellen...