Enhanced Online Continuous Brain-Control by Deep Learning-Based EEG Decoding

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 33; pp. 2834 - 2846
• Main Authors: Wang, Jiaheng, Yao, Lin, Wang, Yueming
• Format: Journal Article
• Language: English
• Published: United States IEEE 2025
• Subjects: Adult; Algorithms; Brain - physiology; Brain modeling; Brain-computer interface; Brain-Computer Interfaces; Decoding; Deep Learning; EEG; Electroencephalography; Electroencephalography - methods; Female; Hands; Humans; Imagination - physiology; Iron; Machine learning; Male; Manipulators; motor imagery; Neural Networks, Computer; online continuous control; Online Systems; Support vector machines; Training; Young Adult

Objective: A growing amount of deep learning models for motor imagery (MI) decoding from electroencephalogram (EEG) have demonstrated their superiority over traditional machine learning approaches in offline dataset analysis. However, current online MI-based brain-computer interfaces (BCIs) still pr...