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Abstract:
On-line classification of slow cortical potentials (SCP) of the EEG allows the characterization
of two to four different brain states which can be used for computer based selection
of letters or words. 7 completely paralyzed, artificially respirated and fed lockedin
patients suffering from amyotrophic lateral sclerosis were trained to produce negative
and positive SCP at the Vertex-electrode. After successful training selection of letters or
words was possible with a maximum speed of one letter or word per minute. Patients
whose training was initiated late at a completely locked-in-state were only able to answer
yes-no questions with their SCP. New classification algorithms, in particular support
vector machines, allow better classifications. First attempts to build a 150 channel
MEG/EEG brain-computer-interface (BCI) for the locked-in and otherwise paralyzed
patients are reported.
Critical for successful application, however, is the selection of simple behavioral paradigms
allowing patients with cognitive disorders and higher animals to produce classifiable
brain states. The operant regulation with feedback seems to be an easy to apply
and psychologically most adapted paradigm for BCI.
