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Decoding finger movements from ECoG signals using switching linear models
[article]
2011
arXiv
pre-print
One of the major challenges of ECoG-based Brain-Machine Interfaces is the movement prediction of a human subject. Several methods exist to predict an arm 2-D trajectory. The fourth BCI Competition gives a dataset in which the aim is to predict individual finger movements (5-D trajectory). The difficulty lies in the fact that there is no simple relation between ECoG signals and finger movement. We propose in this paper to decode finger flexions using switching models. This method permits to
arXiv:1106.3395v1
fatcat:aw3dnz4nmzaa3jf732mk2jdd3a