scispace - formally typeset
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.

Papers
More filters
Journal ArticleDOI

Critical Decision-Speed and Information Transfer in the “Graz Brain–Computer Interface”

TL;DR: Analysis of 4 young paraplegic patients' last 2 experimental sessions showed that the trial length can be reduced to values around 2 s to obtain the highest possible information transfer.
Journal ArticleDOI

Mapping of event-related desynchronization and type of derivation

TL;DR: Single-lead EEG data referred to one ear were recorded during voluntary finger movements, and transverse bipolar, source and common average reference derivations and the laplacian operator were calculated, and ERD maps are computed.
Journal ArticleDOI

On the existence of different alpha band rhythms in the hand area of man.

TL;DR: In this paper, the authors applied dynamic cross-spectral analysis to event-related EEG data recorded during finger movement and found a superposition of Rolandic mu rhythms and bilaterally coherent alpha band rhythms in the central area.
Journal ArticleDOI

A comparison of common spatial patterns with complex band power features in a four-class BCI experiment

TL;DR: A new set of features called complex band power (CBP) features which make explicit use of phase are introduced and are shown to produce good results in the offline analysis of four-class brain-computer interface (BCI) data recordings.
Book ChapterDOI

Quantitative EEG in normals and in patients with cerebral ischemia.

TL;DR: This chapter describes the procedure that allows clear discrimination of the normals and patients with cerebral ischemia based on multiple EEG data recorded during rest and voluntary movement.