Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain–computer interface
Aarthy Nagarajan,
Neethu Robinson,
Kai Keng Ang
et al.
Abstract:Objective: Motor imagery (MI) brain-computer interfaces (BCI) based on electroencephalogram (EEG) have been developed primarily for stroke rehabilitation, however, due to limited stroke data, current deep learning methods for cross-subject classification rely on healthy data. This study aims to assess the feasibility of applying MI-BCI models pre-trained using data from healthy individuals to detect MI in stroke patients. Approach: We introduce a new transfer learning approach where features from two-class MI … Show more
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