Classification of motor imagery using multisource joint transfer learning

• Published in: Review of scientific instruments Vol. 92; no. 9; pp. 094106 - 94118
• Main Authors: Wang, Fei, Ping, Jingyu, Xu, Zongfeng, Bi, Jinying
• Format: Journal Article
• Language: English
• Published: United States American Institute of Physics 01.09.2021
• Subjects: Algorithms; Brain-Computer Interfaces; Calibration; Covariance matrix; Electroencephalography; Human-computer interface; Humans; Image classification; Imagination; Knowledge management; Machine Learning; Scientific apparatus & instruments

As an important way for human-computer interaction, the motor imagery brain–computer interface (MI-BCI) can decode personal motor intention directly by analyzing electroencephalogram (EEG) signals. However, a large amount of labeled data has to be collected for each new subject since EEG patterns va...