S. Lemm
Impact in
- Cognitive Neuroscience top 2%
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Signal Processing top 2%
- Blind Source Separation Techniques
Papers in
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- Time Series Analysis and Forecasting 3
- Blind Source Separation Techniques 2
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- EEG and Brain-Computer Interfaces 3
- Neural dynamics and brain function 2
- Co-authors
- Gabriel Curio (4 shared papers)K. Müller (4 shared papers)Benjamin Blankertz (1 shared paper)Christin Schäfer (1 shared paper)Yevhen Hlushchuk (1 shared paper)Jens Kohlmorgen (3 shared papers)Gunnar Rätsch (1 shared paper)Klaus Pawelzik (1 shared paper)
- Journals
- IEEE Transactions on Biomedical Engineering (3 papers)International Journal of Psychophysiology (1 paper)Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) (3 papers)
- Partner nations
- GermanyUnited StatesNetherlands
In The Last Decade
S. Lemm
7 papers receiving 800 citations
S. Lemm's Hit Papers
Peers
Comparison fields: 5 of 48
- Cognitive Neuroscience 762
- Signal Processing 372
- Human-Computer Interaction 131
- Cellular and Molecular Neuroscience 268
- Computational Mathematics 2
Countries citing papers authored by S. Lemm
This map shows the geographic impact of S. Lemm'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 S. Lemm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Lemm more than expected).
Fields of papers citing papers by S. Lemm
This network shows the impact of papers produced by S. Lemm. 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 S. Lemm. The network helps show where S. Lemm may publish in the future.
Co-authors
The 13 scholars most cited alongside S. Lemm, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Spatio-spectral filters for improving the classification of single trial EEG Hit paper breakdown → | 2005 | 546 |
| 2 | 2004 | 182 | |
| 3 | 2006 | 66 | |
| 4 | 2002 | 17 | |
| 5 | 2003 | 5 | |
| 6 | 2002 | 5 | |
| 7 | 2008 | 1 |
About S. Lemm
S. Lemm is a scholar working on Signal Processing, Cognitive Neuroscience, Artificial Intelligence, Statistical and Nonlinear Physics and Biomedical Engineering, having authored 7 papers that have together received 822 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (3 papers), Time Series Analysis and Forecasting (3 papers), Blind Source Separation Techniques (2 papers), Chaos control and synchronization (2 papers), Neural dynamics and brain function (2 papers), Neural Networks and Applications (2 papers), Muscle activation and electromyography studies (1 paper) and Gaussian Processes and Bayesian Inference (1 paper). The work is most often cited by research in Cognitive Neuroscience (762 citations), Signal Processing (372 citations), Human-Computer Interaction (131 citations), Cellular and Molecular Neuroscience (268 citations) and Computational Mathematics (2 citations). S. Lemm has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Gabriel Curio, K. Müller, Benjamin Blankertz, Christin Schäfer, Yevhen Hlushchuk, Jens Kohlmorgen, Gunnar Rätsch, Klaus Pawelzik, Klaus Linkenkaer‐Hansen and Vadim V. Nikulin. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, International Journal of Psychophysiology and Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft).
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.