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Transfer Learning in Motor Imagery Brain Computer Interface: A Review

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Abstract

Transfer learning, as a new machine learning methodology, may solve problems in related but different domains by using existing knowledge, and it is often applied to transfer training data from another domain for model training in the case of insufficient training data. In recent years, an increasing number of researchers who engage in brain-computer interface (BCI), have focused on using transfer learning to make most of the available electroencephalogram data from different subjects, effectively reducing the cost of expensive data acquisition and labeling as well as greatly improving the learning performance of the model. This paper surveys the development of transfer learning and reviews the transfer learning approaches in BCI. In addition, according to the “what to transfer” question in transfer learning, this review is organized into three contexts: instance-based transfer learning, parameter-based transfer learning, and feature-based transfer learning. Furthermore, the current transfer learning applications in BCI research are summarized in terms of the transfer learning methods, datasets, evaluation performance, etc. At the end of the paper, the questions to be solved in future research are put forward, laying the foundation for the popularization and in-depth research of transfer learning in BCI.

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Authors and Affiliations

  1. Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Mingai Li  (李明爱) & Dongqin Xu  (许冬芹)

  2. Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, 100124, China

    Mingai Li  (李明爱)

  3. Engineering Research Center of Digital Community, Ministry of Education, Beijing, 100124, China

    Mingai Li  (李明爱)

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  1. Mingai Li  (李明爱)
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Correspondence to Mingai Li  (李明爱).

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Foundation item: the National Natural Science Foundation of China (Nos. 11832003 and 81471770), and the Natural Science Foundation of Beijing (No. 4182009)

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Li, M., Xu, D. Transfer Learning in Motor Imagery Brain Computer Interface: A Review. J. Shanghai Jiaotong Univ. (Sci.) 29, 37–59 (2024). https://doi.org/10.1007/s12204-022-2488-4

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