Daniel Graupe
- Biomedical Engineering top 2%
- Cognitive Neuroscience top 2%
- Cellular and Molecular Neuroscience top 2%
- Artificial Intelligence top 2%
- Signal Processing top 1%
- Co-authors
- Kate H. KohnVivek NigamHubert KordylewskiA.A. BeexDaniela TuninettiMichael A. WincekKonstantin V. SlavinIshita Basu
- Topics
- Muscle activation and electromyography studies (35 papers)EEG and Brain-Computer Interfaces (29 papers)Neuroscience and Neural Engineering (23 papers)
- Journals
- TechnometricsAmerican Journal of Respiratory and Critical Care MedicineIEEE Transactions on Automatic Control
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Daniel Graupe
117 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 168
- Biomedical Engineering 1.3k
- Cognitive Neuroscience 1.1k
- Cellular and Molecular Neuroscience 740
- Artificial Intelligence 669
- Signal Processing 489
Countries citing papers authored by Daniel Graupe
This map shows the geographic impact of Daniel Graupe'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 Daniel Graupe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Graupe more than expected).
Fields of papers citing papers by Daniel Graupe
This network shows the impact of papers produced by Daniel Graupe. 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 Daniel Graupe. The network helps show where Daniel Graupe may publish in the future.
Co-authorship network of co-authors of Daniel Graupe
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Graupe. A scholar is included among the top collaborators of Daniel Graupe 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 Daniel Graupe. Daniel Graupe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 268 | |
| 5 | 10 | |
| 6 | 3 | |
| 7 | 50 | |
| 8 | 28 | |
| 9 | Extracting fetal from maternal ECG for early diagnosis: theoretical problems and solutions - BAF and ICA | 4 |
| 10 | 280 | |
| 11 | 86 | |
| 12 | 36 | |
| 13 | 27 | |
| 14 | 67 | |
| 15 | 5 | |
| 16 | Activation of paraplegic patients by functional electrical stimulation: training and biomechanical evaluation. | 20 |
| 17 | Filtering for spread spectrum channels with frequency-hop interference | 0 |
| 18 | 1 | |
| 19 | 2 | |
| 20 | A multifunctional prosthesis control system based on time series identification of EMG signals using microprocessors. | 17 |
About Daniel Graupe
Daniel Graupe is a scholar working on Computational Mathematics, Signal Processing and Cognitive Neuroscience, having authored 127 papers that have together received 3.5k indexed citations. Recurring topics across this work include Muscle activation and electromyography studies (35 papers), EEG and Brain-Computer Interfaces (29 papers) and Neuroscience and Neural Engineering (23 papers). The work is most often cited by research in Cognitive Neuroscience (1.1k citations), Signal Processing (489 citations) and Cellular and Molecular Neuroscience (740 citations). Daniel Graupe has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Kate H. Kohn, Vivek Nigam, Hubert Kordylewski, A.A. Beex, Daniela Tuninetti, Michael A. Wincek, Konstantin V. Slavin, Ishita Basu, Aaron S. Field and Jason H. Moore. Their work appears in journals such as Technometrics, American Journal of Respiratory and Critical Care Medicine and IEEE Transactions on Automatic Control.
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.