Data-Driven Transducer Design and Identification for Internally-Paced Motor Brain Computer Interfaces: A Review

@article{Schaeffer2018DataDrivenTD,
  title={Data-Driven Transducer Design and Identification for Internally-Paced Motor Brain Computer Interfaces: A Review},
  author={Marie-Caroline Schaeffer and Tetiana I. Aksenova},
  journal={Frontiers in Neuroscience},
  year={2018},
  volume={12}
}
Brain-Computer Interfaces (BCIs) are systems that establish a direct communication pathway between the users' brain activity and external effectors. They offer the potential to improve the quality of life of motor-impaired patients. Motor BCIs aim to permit severely motor-impaired users to regain limb mobility by controlling orthoses or prostheses. In particular, motor BCI systems benefit patients if the decoded actions reflect the users' intentions with an accuracy that enables them to… 

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