Transfer Learning

Design a Novel BCI for Neurorehabilitation Using Concurrent LFP and EEG Features: A Case Study

Author(s)3: Yi Sun, Yu Qi, Yueming Wang, Cuntai Guan, Yu Sun
Design a Novel BCI for Neurorehabilitation Using Concurrent LFP and EEG Features: A Case Study IEEE Transactions on Biomedical Engineering (TBME)
This work introduced for the first time a novel BCI that incorporate both intracortical LFP and scalp EEG (named, LFP-EEG-BCI) for motor intention decoding during neurorehabilitation. Concurrent intracortical and scalp signals were collected from a paraplegic patient undergoing motor imagery (MI) neurorehabilitation training. A common spatial filter approach was adopted for feature extraction and a decision fusion strategy was further introduced to obtain the decoding results. Transfer learning approach was also utilized to reduce the calibration. The proposed novel LFP-EEG-BCI may lead to new directions for developing practical neurorehabilitation systems in clinical applications. read more

Align and Pool for EEG Headset Domain Adaptation (ALPHA) to Facilitate Dry Electrode Based SSVEP-BCI

Author(s)3: Bingchuan Liu, Xiaogang Chen, Xiang Li, Yijun Wang, Xiaorong Gao, Shangkai Gao
Align and Pool for EEG Headset Domain Adaptation (ALPHA) to Facilitate Dry Electrode Based SSVEP-BCI 170 177 IEEE Transactions on Biomedical Engineering (TBME)
This study leverages transfer learning to improve the performance for steady-state visual evoked potential based brain-computer interface (SSVEP-BCI) implemented by dry electrodes. We utilize auxiliary individual electroencephalogram (EEG) recorded from wet electrode for cross-device transfer learning via the proposed framework named ALign and Pool for EEG Headset domain Adaptation (ALPHA), which aligns the SSVEP features by domain adaptation. ALPHA significantly outperformed the competing methods in two transfer directions, and boosted the dry-electrode systems using wet-electrode EEG. The cross-device transfer learning by ALPHA could increase the utility and potentially promote the use of dry electrode based SSVEP-BCIs in practical applications. read more

Transferring Subspaces Between Subjects in Brain-Computer Interfacing

Transferring Subspaces Between Subjects in Brain-Computer Interfacing 150 150 IEEE Transactions on Biomedical Engineering (TBME)

Wojciech Samek, Frank C. Meinecke, Klaus-Robert Müller Volume: 60, Issue:8, Page(s): 2289-2298 Compensating changes between a subjects’ training and testing session in Brain Computer Interfacing (BCI) is challenging but of…

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