Gert Pfurtscheller

Bio: Gert Pfurtscheller is an academic researcher from Graz University of Technology. The author has contributed to research in topics: Brain–computer interface & Electroencephalography. The author has an hindex of 117, co-authored 507 publications receiving 62873 citations. Previous affiliations of Gert Pfurtscheller include University of Graz.

Graz Brain-Computer Interface (BCI) II

Abstract: This paper describes the new setup of the Graz Brain-Computer Interface (BCI) system II, which is based on on-line classification of EEG patterns to determine which of three kinds of movement is planned by a subject. This classification can be exploited for on-line control which may constitute a great help for handicapped persons in the future.

Feature extraction for on-line EEG classification using principal components and linear discriminants

Abstract: The study focuses on the problems of dimensionality reduction by means of principal component analysis (PCA) in the context of single-trial EEG data classification (i.e. discriminating between imagined left- and right-hand movement). The principal components with the highest variance, however, do not necessarily carry the greatest information to enable a discrimination between classes. An EEG data set is presented where principal components with high variance cannot be used for discrimination. In addition, a method based on linear discriminant analysis (LDA), is introduced that detects principal components which can be used for discrimination, leading to data sets of reduced dimensionality but similar classification accuracy.

AI-based approach to automatic sleep classification

Abstract: The primary goal of this paper is to introduce the potential of artificial intelligence (AI) methods to researchers in sleep classification. AI provides learning procedures for the construction of a sleep classifier, prescribing how to combine the observed parameters and how to derive the corresponding decision thresholds. A case study reporting a successful application of an automatic induction of decision trees and of a learning vector quantizer to this domain is presented.

EEG classification by learning vector quantization.

Abstract: EEG classification using Learning Vector Quantization (LVQ) is introduced on the basis of a Brain-Computer Interface (BCI) built in Graz, where a subject controlled a cursor in one dimension on a monitor using potentials recorded from the intact scalp. The method of classification with LVQ is described in detail along with first results on a subject who participated in four on-line cursor control sessions. Using this data, extensive off-line experiments were performed to show the influence of the various parameters of the classifier and the extracted features of the EEG on the classification results.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or