J Neural Eng 2021 Jun 10. Epub 2021 Jun 10.
Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Avenue, University Town, Xili, Nanshan, Shenzhen, Guangdong, Shenzhen, Guangdong, 518055, CHINA.
Background And Objective: Non-invasive multichannel Electroencephalography (EEG) recordings provide an alternative source of neural information from which motor imagery (MI) patterns associated with limb movement intent can be decoded for use as control inputs for rehabilitation robots. The presence of multiple inherent dynamic artifacts in EEG signals, however, poses processing challenges for brain-computer interface (BCI) systems. A large proportion of the existing EEG signal preprocessing methods focus on isolating single artifact per time from an ensemble of EEG trials and require calibration and/or reference electrodes, resulting in increased complexity of their application to MI-EEG controlled rehabilitation devices in practical settings. Read More