Christian Mühl
- Cognitive Neuroscience top 0.5%
- Experimental and Cognitive Psychology top 0.2%
- Human-Computer Interaction top 0.5%
- Cardiology and Cardiovascular Medicine top 5%
- Signal Processing top 1%
- Co-authors
- Ioannis PatrasSander KoelstraAnton NijholtAmirmehdi YazdaniTouradj EbrahimiJong‐Seok LeeThierry PunMohammad Soleymani
- Topics
- EEG and Brain-Computer Interfaces (12 papers)Neural and Behavioral Psychology Studies (9 papers)Neural dynamics and brain function (6 papers)
- Partner nations
- United StatesNetherlandsGermany
In The Last Decade
Christian Mühl
20 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 99
- Cognitive Neuroscience 2.9k
- Experimental and Cognitive Psychology 2.6k
- Human-Computer Interaction 550
- Cardiology and Cardiovascular Medicine 530
- Signal Processing 478
Countries citing papers authored by Christian Mühl
This map shows the geographic impact of Christian Mühl'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 Christian Mühl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christian Mühl more than expected).
Fields of papers citing papers by Christian Mühl
This network shows the impact of papers produced by Christian Mühl. 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 Christian Mühl. The network helps show where Christian Mühl may publish in the future.
Co-authorship network of co-authors of Christian Mühl
This figure shows the co-authorship network connecting the top 25 collaborators of Christian Mühl. A scholar is included among the top collaborators of Christian Mühl 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 Christian Mühl. Christian Mühl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 28 | |
| 5 | 19 | |
| 6 | 43 | |
| 7 | EEG-based workload estimation across affective contexts | 1 |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 203 | |
| 11 | 53 | |
| 12 | 1 | |
| 13 | 96 | |
| 14 | DEAP: A Database for Emotion Analysis ;Using Physiological Signalsbreakdown → | 3233 |
| 15 | Modality-specific Affective Responses and their Implications for Affective BCI | 21 |
| 16 | 48 | |
| 17 | Bacteria Hunt: A multimodal, multiparadigm BCI game | 26 |
| 18 | 47 | |
| 19 | 3 | |
| 20 | 37 |
About Christian Mühl
Christian Mühl is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Social Psychology, having authored 20 papers that have together received 3.9k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (12 papers), Neural and Behavioral Psychology Studies (9 papers) and Neural dynamics and brain function (6 papers). The work is most often cited by research in Experimental and Cognitive Psychology (2.6k citations), Cognitive Neuroscience (2.9k citations) and Human-Computer Interaction (550 citations). Christian Mühl has collaborated with scholars based in United States, Netherlands and Germany. Frequent co-authors include Ioannis Patras, Sander Koelstra, Anton Nijholt, Amirmehdi Yazdani, Touradj Ebrahimi, Jong‐Seok Lee, Thierry Pun, Mohammad Soleymani, Fabien Lotte and Florian Larrue. Their work appears in journals such as Journal of Applied Physiology, Frontiers in Physiology and Frontiers in Human Neuroscience.
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.