M. Pregenzer

2.1k total citations · 1 hit paper
17 papers, 1.6k citations indexed

About

M. Pregenzer is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Cellular and Molecular Neuroscience. According to data from OpenAlex, M. Pregenzer has authored 17 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cognitive Neuroscience, 9 papers in Artificial Intelligence and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in M. Pregenzer's work include EEG and Brain-Computer Interfaces (14 papers), Neural Networks and Applications (9 papers) and Neural dynamics and brain function (6 papers). M. Pregenzer is often cited by papers focused on EEG and Brain-Computer Interfaces (14 papers), Neural Networks and Applications (9 papers) and Neural dynamics and brain function (6 papers). M. Pregenzer collaborates with scholars based in Austria and Germany. M. Pregenzer's co-authors include G. Pfurtscheller, Doris Flotzinger, Ch. Neuper, Christa Neuper, Alois Schlögl, Herbert Ramoser, C. Guger, B. Obermaier, G. Pfurtscheller and J. Kalcher and has published in prestigious journals such as Electroencephalography and Clinical Neurophysiology, Neurocomputing and Neuroscience Letters.

In The Last Decade

M. Pregenzer

16 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

EEG-based discrimination between imagination of right and left hand movement

1997 673 citations G. Pfurtscheller, Ch. Neuper et al. Electroencephalography and Clinical Neurophysiology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
M. Pregenzer Austria	12	1.5k	752	354	312	251	17	1.6k
Claudia Keinrath Austria	12	1.6k 1.1×	657 0.9×	304 0.9×	281 0.9×	360 1.4×	22	1.7k
B. Obermaier Austria	8	1.1k 0.8×	613 0.8×	254 0.7×	273 0.9×	232 0.9×	10	1.2k
B. Graimann Austria	15	2.0k 1.4×	1.1k 1.5×	361 1.0×	384 1.2×	304 1.2×	19	2.2k
Stephan Waldert Germany	11	1.6k 1.1×	790 1.1×	323 0.9×	379 1.2×	241 1.0×	14	1.7k
Laurent Bougrain France	13	1.6k 1.1×	630 0.8×	293 0.8×	381 1.2×	292 1.2×	40	1.8k
J. Mouriño Spain	11	1.1k 0.7×	611 0.8×	173 0.5×	246 0.8×	298 1.2×	33	1.3k
Luis F. Nicolás-Alonso Spain	8	1.6k 1.1×	869 1.2×	296 0.8×	397 1.3×	375 1.5×	9	1.7k
Mahnaz Arvaneh United Kingdom	18	1.1k 0.7×	421 0.6×	305 0.9×	251 0.8×	191 0.8×	60	1.3k
S.G. Mason Canada	13	1.1k 0.7×	717 1.0×	133 0.4×	316 1.0×	237 0.9×	26	1.2k
Claudia Sannelli Germany	15	1.7k 1.2×	801 1.1×	181 0.5×	377 1.2×	206 0.8×	24	1.8k

Countries citing papers authored by M. Pregenzer

Since Specialization

Citations

This map shows the geographic impact of M. Pregenzer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by M. Pregenzer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Pregenzer more than expected).

Fields of papers citing papers by M. Pregenzer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Pregenzer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by M. Pregenzer. The network helps show where M. Pregenzer may publish in the future.

Co-authorship network of co-authors of M. Pregenzer

This figure shows the co-authorship network connecting the top 25 collaborators of M. Pregenzer. A scholar is included among the top collaborators of M. Pregenzer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with M. Pregenzer. M. Pregenzer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Pregenzer, M., Doris Flotzinger, & G. Pfurtscheller. (2002). Distinction Sensitive Learning Vector Quantisation-a new noise-insensitive classification method. 5. 2890–2894. 8 indexed citations

Pfurtscheller, G., Christa Neuper, C. Guger, et al.. (2000). Current trends in Graz brain-computer interface (BCI) research. IEEE Transactions on Rehabilitation Engineering. 8(2). 216–219. 367 indexed citations

Pregenzer, M. & G. Pfurtscheller. (1999). Frequency component selection for an EEG-based brain to computer interface. IEEE Transactions on Rehabilitation Engineering. 7(4). 413–419. 118 indexed citations

Schlögl, Alois, P. Anderer, Stephen Roberts, M. Pregenzer, & Gert Pfurtscheller. (1999). Artefact detection in sleep EEG by the use of Kalman filtering. 1648–1649. 19 indexed citations

Pregenzer, M., et al.. (1999). A non parametric method for calculating a posteriori probabilities of sleep spindles in EEG data. 484–485. 1 indexed citations

Schlögl, Alois, et al.. (1998). Feature extraction for on-line EEG classification using principal components and linear discriminants. Medical & Biological Engineering & Computing. 36(3). 309–314. 36 indexed citations

Pfurtscheller, G., Ch. Neuper, Doris Flotzinger, & M. Pregenzer. (1997). EEG-based discrimination between imagination of right and left hand movement. Electroencephalography and Clinical Neurophysiology. 103(6). 642–651. 673 indexed citations breakdown →

Pfurtscheller, Gert, M. Pregenzer, & Doris Flotzinger. (1997). Classification of single EEG trials using machine learning methods and neural networks. 221–235.

Pfurtscheller, G., Doris Flotzinger, M. Pregenzer, Jonathan R. Wolpaw, & Dennis J. McFarland. (1996). EEG-based brain computer interface (BCI). Search for optimal electrode positions and frequency components.. PubMed. 21(3). 111–21. 45 indexed citations

10.

Pfurtscheller, G., et al.. (1996). On-line EEG classification during externally-paced hand movements using a neural network-based classifier. Electroencephalography and Clinical Neurophysiology. 99(5). 416–425. 86 indexed citations

11.

Schlögl, Alois, et al.. (1996). Classification of Single trial EEG: A comparison of different parameters.. 266–268. 3 indexed citations

12.

Pregenzer, M., et al.. (1996). Automated feature selection with a distinction sensitive learning vector quantizer. Neurocomputing. 11(1). 19–29. 64 indexed citations

13.

Pregenzer, M., Gert Pfurtscheller, & Colin Andrew. (1995). Improvement of EEG classification with a subject-specific feature selection.. The European Symposium on Artificial Neural Networks. 2 indexed citations

14.

Pregenzer, M.. (1995). Distinction Sensitive Learning Vector Quantization (DSLVQ) - application as a classifier based feature selection method for a brain computer interface. 1995. 433–436. 16 indexed citations

15.

Pfurtscheller, G., M. Pregenzer, & Christa Neuper. (1994). Visualization of sensorimotor areas involved in preparation for hand movement based on classification of μ and central β rhythms in single EEG trials in man. Neuroscience Letters. 181(1-2). 43–46. 95 indexed citations

16.

Pregenzer, M., G. Pfurtscheller, & Doris Flotzinger. (1994). Selection of electrode positions for an EEG-based Brain Computer Interface (BCI). Auswahl von Elektrodenpositionen für ein auf EEG-Ableitungen basierendes Brain Computer Interface (BCI). Biomedizinische Technik/Biomedical Engineering. 39(10). 264–269. 15 indexed citations

17.

Flotzinger, Doris, M. Pregenzer, & G. Pfurtscheller. (1994). Feature selection with distinction sensitive learning vector quantisation and genetic algorithms. 3448–3451 vol.6. 24 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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