J. Kalcher et al., GRAZ BRAIN-COMPUTER INTERFACE-II - TOWARDS COMMUNICATION BETWEEN HUMANS AND COMPUTERS BASED ON ONLINE CLASSIFICATION OF 3 DIFFERENT EEG PATTERNS, Medical & biological engineering & computing, 34(5), 1996, pp. 382-388
The paper describes work on the brain-computer interface (BCI). The BC
I is designed to help patients with severe motor impairment (e.g. amyo
tropic lateral sclerosis) to communicate with their environment throug
h wilful modification of their EEG. To establish such a communication
channel, two major prerequisites have to be fulfilled: features that r
eliably describe several distinctive brain states have to be available
, and these features must be classified on-line, i.e. on a single-tria
l basis. The prototype Graz BCI II, which is based on the distinction
of three different types of EEG pattern, is described, and results of
online and offline classification performance of four subjects are rep
orted. The online results suggest that, in the best case, a classifica
tion accuracy of about 60% is reached after only three training sessio
ns. The offline results show how selection of specific frequency bands
influences the classification performance in single-trial data.