Beate Meffert

607 citations
47 papers · 436 · h-index 9

Impact in

    • EEG and Brain-Computer Interfaces
    • Neural dynamics and brain function
    • Functional Brain Connectivity Studies
    • Blind Source Separation Techniques

Papers in

Beate Meffert

39 papers receiving 410 citations

Peers

Beate Meffert
Comparison fields: 5 of 98
  • Cognitive Neuroscience 223
  • Signal Processing 97
  • Human-Computer Interaction 30
  • Computer Vision and Pattern Recognition 61
  • Experimental and Cognitive Psychology 34
Replace Maxime Bérar with:
Maxime Bérar France
Shubham J. Dodia India
Padmavati Khandnor India
Antonello Florio Italy
Pavel Sovka Czechia
Hubert J. Banville France
Muhammad Zeeshan Baig United Arab Emirates
Tian-jian Luo China
Radu Ranta France
Valérie Louis-Dorr France
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Citations per field
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Citations per year

Countries citing papers authored by Beate Meffert

Since Specialization
Citations

This map shows the geographic impact of Beate Meffert'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 Beate Meffert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beate Meffert more than expected).

Fields of papers citing papers by Beate Meffert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Beate Meffert. 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 Beate Meffert. The network helps show where Beate Meffert may publish in the future.

Co-authors

The 23 scholars most cited alongside Beate Meffert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Beate Meffert Line = papers co-authored together Beate Meffert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017118
2 2015105
3 201936
4 200521
5 200916
6 202015
7 200415
8 200914
9 200812
10 20206
11 20185
12 19725
13 20005
14 20075
15 20014
16 19874
17 20094
18 19943
19 20013
20 20203

About Beate Meffert

Beate Meffert is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience, Instrumentation, Signal Processing and Control and Systems Engineering, having authored 47 papers that have together received 436 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (6 papers), Human-Automation Interaction and Safety (4 papers), Advanced Control Systems Optimization (4 papers), Advanced Data Compression Techniques (3 papers), Blind Source Separation Techniques (3 papers), Image and Signal Denoising Methods (3 papers), Advanced Optical Sensing Technologies (3 papers) and Network Time Synchronization Technologies (2 papers). The work is most often cited by research in Cognitive Neuroscience (223 citations), Signal Processing (97 citations), Human-Computer Interaction (30 citations), Computer Vision and Pattern Recognition (61 citations) and Experimental and Cognitive Psychology (34 citations). Beate Meffert has collaborated with scholars based in Germany, Egypt and United States. Frequent co-authors include Thea Radüntz, Mohammed A.‐M. Salem, H Meffert, Frank Winkler, Nivin A. Ghamry, Norbert Fürstenau, Thomas Kemp, Henning F. Harmuth, Thorsten Mühlhausen and Gabriela Riemekasten. Their work appears in journals such as Apidologie, IEEE Transactions on Human-Machine Systems, Computers in Biology and Medicine, JMIR mhealth and uhealth and Journal of Neural Engineering.

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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