G
Gert Pfurtscheller
Researcher at Graz University of Technology
Publications - 510
Citations - 68013
Gert Pfurtscheller is an academic researcher from Graz University of Technology. The author has contributed to research in topics: Electroencephalography & Brain–computer interface. The author has an hindex of 117, co-authored 507 publications receiving 62873 citations. Previous affiliations of Gert Pfurtscheller include University of Graz.
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Journal ArticleDOI
Prediction of the side of hand movements from single-trial multi-channel EEG data using neural networks.
TL;DR: Event-related desynchronization (ERD) was quantified in the 8-10 Hz and 10-12 Hz bands in single-trial data and used as training input for a neural network comprised of a learning vector quantizer (LVQ).
Journal ArticleDOI
Analysis of sensorimotor rhythms for the implementation of a brain switch for healthy subjects
TL;DR: The methods described in this work are suitable for operating a brain–computer interface (BCI) as an attractive control alternative for healthy users and a step forward towards an easy- to-set-up and easy-to-use asynchronous BCI system forhealthy users.
Journal ArticleDOI
Comparison of DFT and lock-in amplifier features and search for optimal electrode positions in SSVEP-based BCI.
TL;DR: This study investigated how the classification accuracy of a 4-class BCI system can be improved by localizing individual electroencephalogram (EEG) recording positions and found that the use of three SSVEP-harmonics recorded from individual channels yielded significantly higher classification accuracy.
Book ChapterDOI
Event-related synchronization and desynchronization of alpha and beta waves in a cognitive task
TL;DR: Together with the discovery of alpha waves in human scalp electroencephalograms by Berger (1930), blocking was reported in response to a light stimulation and reports of an enhancement of alpha band activity as a response to visual stimulation and tactile stimulation.
Journal ArticleDOI
Self-initiation of EEG-based brain-computer communication using the heart rate response.
TL;DR: This work analyzes whether the respiratory heart rate response, induced by brisk inspiration, can be used as an additional communication channel for self-initiation in brain-computer interface users.