Multi-stimulus Least-squares Transformation with Online Adaptation Scheme to Reduce Calibration Effort for SSVEP-based BCIs

Steady-state visual evoked potential (SSVEP), one of the most popular electroencephalography (EEG)-based brain-computer interface (BCI) paradigms, can achieve high performance using calibration-based recognition algorithms. As calibration-based recognition algorithms are time-consuming to collect ca...

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Veröffentlicht in:	IEEE transactions on neural systems and rehabilitation engineering 2024-01, Vol.32, p.1-1
Hauptverfasser:	Li, Dandan, Wang, Xuedong, Dou, Mingliang, Zhao, Yao, Cui, Xiaohong, Xiang, Jie, Wang, Bin
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Algorithms Brain Brain-computer interface Brain-Computer Interfaces Calibration Computer applications Correlation coefficient Datasets EEG Electroencephalography Electroencephalography - methods Evoked Potentials, Visual Filters Human-computer interface Humans Implants Least squares multi-stimulus least squares transform online adaptation scheme Photic Stimulation - methods Recognition Spatial filtering Spatial filters steady-state visual evoked potential Task analysis Transfer learning Visual evoked potentials Visualization
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