Improving brain-computer interface performance with optimized frequency interaction and enhancement techniques: CFC-PSO-XGBoost (CPX)

•Leveraged Cross-Frequency Coupling (CFC) for enhanced MI-BCI classification.•Phase-Amplitude Coupling (PAC) extracted CFC features from spontaneous EEG.•Particle Swarm Optimization (PSO) optimized channel selection for classification.•Achieved 76.7 % accuracy, outperforming traditional MI-BCI metho...

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Vydané v:	Medical engineering & physics Ročník 143; s. 104392
Hlavní autori:	Xiao, Xiao, Li, Haoyue
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Elsevier Ltd 01.09.2025
Predmet:	Adult Boosting Machine Learning Algorithms Brain-computer interface Brain-Computer Interfaces Cross-frequency coupling Electroencephalography Female Humans Imagination Male Motor imagery Phase-Amplitude Coupling, Particle Swarm Optimization Signal Processing, Computer-Assisted Young Adult Brain-computer interface Cross-frequency coupling Motor imagery Phase-Amplitude Coupling, Particle Swarm Optimization
ISSN:	1350-4533, 1873-4030, 1873-4030
On-line prístup:	Získať plný text
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