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Multi-source domain adaptation for decoder calibration of intracortical brain-machine interface.

Wei LiShaohua JiXi ChenBo KuaiJiping HePeng ZhangQiang Li
Published in: Journal of neural engineering (2020)
(1) The idea of the multi-source domain adaptation was introduced into the iBMIs to solve the problem of time consumption in the daily decoder retraining. (2) Instead of using only single-source domain data in the previous study, our algorithm made use of multi-day historical data, resulting in better and more robust decoding performance. (3) Our algorithm could be accomplished with only a small current sample set, and it can effectively reduce the decoder calibration time, which is important for further clinical applications.
Keyphrases
  • deep learning
  • machine learning
  • electronic health record
  • big data
  • physical activity
  • white matter
  • neural network
  • resting state
  • brain injury