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- W2023180492 abstract "Brain-Computer Interfaces (BCI) that rely upon epidural electrocorticographic signals may become a promising tool for neurorehabilitation of patients with severe hemiparatic syndromes due to cerebrovascular, traumatic or tumor-related brain damage. Here, we show in a patient-based feasibility study that online classification of arm movement intention is possible. The intention to move or to rest can be identified with high accuracy (~90 %), which is sufficient for BCI-guided neurorehabilitation. The observed spatial distribution of relevant features on the motor cortex indicates that cortical reorganization has been induced by the brain lesion. Low- and high-frequency components of the electrocorticographic power spectrum provide complementary information towards classification of arm movement intention." @default.
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- W2023180492 date "2010-08-01" @default.
- W2023180492 modified "2023-09-27" @default.
- W2023180492 title "Epidural ECoG Online Decoding of Arm Movement Intention in Hemiparesis" @default.
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- W2023180492 doi "https://doi.org/10.1109/wbd.2010.17" @default.
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