Subject-to-subject adaptation to reduce calibration time in motor imagery-based brain-computer interface

@article{Arvaneh2014SubjecttosubjectAT,
  title={Subject-to-subject adaptation to reduce calibration time in motor imagery-based brain-computer interface},
  author={Mahnaz Arvaneh and Ian H. Robertson and Tom{\'a}s Ward},
  journal={2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  year={2014},
  pages={6501-6504}
}
In order to enhance the usability of a motor imagery-based brain-computer interface (BCI), it is highly desirable to reduce the calibration time. Due to inter-subject variability, typically a new subject has to undergo a 20-30 minutes calibration session to collect sufficient data for training a BCI model based on his/her brain patterns. This paper proposes a new subject-to-subject adaptation algorithm to reliably reduce the calibration time of a new subject to only 3-4 minutes. To reduce the… CONTINUE READING
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