Epidural ECoG Online Decoding of Arm Movement Intention in Hemiparesis

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...

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Bibliographic Details
Published in2010 First Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging pp. 36 - 39
Main Authors Gomez-Rodriguez, M, Grosse-Wentrup, M, Peters, J, Naros, G, Hill, J, Scholkopf, B, Gharabaghi, A
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2010
Subjects
Accuracy
Decoding
Electrodes
Lesions
Manipulators
Training
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Summary: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.
ISBN:9781424484867
1424484863
DOI:10.1109/WBD.2010.17