Gert Pfurtscheller

TL;DR: Using autoregressive modeling of EEG time series and artificial neural nets, a classifier is developed that can tell which movement is performed from a segment of the EEG signal from a single trial, suitable for a so-called 'Brain-Computer Interface', a system that allows one to control a computer, or another device, with ones brain waves.

TL;DR: Two feature selection methods, a distinction-sensitive learning vector quantizer (DSLVQ) and a genetic algorithm (GA) approach, are applied to multichannel electroencephalogram (EEG) patterns, showing the importance of methods automatically selecting the most distinctive out of a number of available features.

TL;DR: The desynchronization and resynchronization of alpha oscillations was studied in 10 normal subjects after visual stimulation of both eyes under two experimental conditions, "eyes opened" and "eyes closed".

TL;DR: Viewing a moving hand results in a stronger desynchronization of the central beta rhythm than viewing a moving cube, which provides further evidence for some extent of motor processing related to visual presentation of objects and implies a greater involvement of motor areas in the brain with the observation of action of different body parts.

TL;DR: Alternative methods for using an individual's previous performance to select the intercept for subsequent trials are compared and the moving average method, using the five most recent pairs of top and bottom trials, appears to be the method of choice.