Hilbert–Huang Transformation-based subject-specific time–frequency-space pattern optimization for motor imagery electroencephalogram classification

• Published in: Measurement : journal of the International Measurement Confederation Vol. 223; p. 113673
• Main Authors: Liu, Xiaolin, Sun, Ying, Zheng, Dezhi, Na, Rui
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2023
• Subjects: Brain computer interface; Electroencephalogram; Hilbert–Huang transformation; Motor imagery classification; Time–frequency-space analysis; Hilbert–Huang transformation; Brain computer interface; Time–frequency-space analysis; Electroencephalogram; Motor imagery classification

The advancement of brain–computer interfaces (BCIs) has narrowed the gap between humans and computers, allowing intentional interaction by monitoring and translating brain signals in real time. Among BCI approaches, motor imagery electroencephalogram (MI-EEG) systems are popular due to their non-inv...