Subject-oriented training for motor imagery brain-computer interfaces

Successful operation of motor imagery (MI)-based brain-computer interfaces (BCI) requires mutual adaptation between the human subject and the BCI. Traditional training methods, as well as more recent ones based on co-adaptation, have mainly focused on the machine-learning aspects of BCI training. This work presents a novel co-adaptive training protocol shifting the focus on subject-related performances and the optimal accommodation of the interactions between the two learning agents of the BCI loop. Preliminary results with 8 able-bodied individuals demonstrate that the proposed method has been able to bring 3 naive users into control of a MI BCI within a few runs and to improve the BCI performances of 3 experienced BCI users by an average of 0.36 bits/sec.


Published in:
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 1259-1262
Presented at:
36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year:
2014
Publisher:
New York, IEEE
Laboratories:




 Record created 2015-05-29, last modified 2018-03-18


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