Philippe Ravier
Impact in
- Signal Processing top 10%
- Blind Source Separation Techniques
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces
- Motor Control and Adaptation
Papers in
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- Muscle activation and electromyography studies 18
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- Blind Source Separation Techniques 13
- Speech and Audio Processing 7
- Co-authors
- Olivier Buttelli (34 shared papers)Pierre‐Olivier Amblard (5 shared papers)Dario Farina (3 shared papers)Meryem Jabloun (20 shared papers)F. Leclerc (2 shared papers)Rachid Harba (8 shared papers)Lars Arendt‐Nielsen (1 shared paper)Pascal Madeleine (1 shared paper)
In The Last Decade
Philippe Ravier
82 papers receiving 685 citations
Peers
Comparison fields: 5 of 104
- Signal Processing 99
- Cognitive Neuroscience 166
- Computational Mathematics 5
- Biomedical Engineering 223
- Orthopedics and Sports Medicine 39
Countries citing papers authored by Philippe Ravier
This map shows the geographic impact of Philippe Ravier'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 Philippe Ravier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philippe Ravier more than expected).
Fields of papers citing papers by Philippe Ravier
This network shows the impact of papers produced by Philippe Ravier. 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 Philippe Ravier. The network helps show where Philippe Ravier may publish in the future.
Co-authors
The 25 scholars most cited alongside Philippe Ravier, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 112 | |
| 2 | 2001 | 60 | |
| 3 | 2004 | 54 | |
| 4 | 2012 | 40 | |
| 5 | 2004 | 27 | |
| 6 | 2015 | 26 | |
| 7 | 2019 | 19 | |
| 8 | 1998 | 18 | |
| 9 | 2017 | 17 | |
| 10 | 2013 | 17 | |
| 11 | 2010 | 17 | |
| 12 | 2018 | 14 | |
| 13 | 2013 | 13 | |
| 14 | 2009 | 13 | |
| 15 | 2010 | 11 | |
| 16 | 2016 | 11 | |
| 17 | 2017 | 11 | |
| 18 | 2016 | 10 | |
| 19 | 2008 | 10 | |
| 20 | 2023 | 9 |
About Philippe Ravier
Philippe Ravier is a scholar working on Biomedical Engineering, Signal Processing, Cognitive Neuroscience, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 90 papers that have together received 722 indexed citations. Recurring topics across this work include Muscle activation and electromyography studies (18 papers), Blind Source Separation Techniques (13 papers), EEG and Brain-Computer Interfaces (12 papers), ECG Monitoring and Analysis (11 papers), Smart Grid Energy Management (10 papers), Face and Expression Recognition (7 papers), Chaos control and synchronization (7 papers) and Speech and Audio Processing (7 papers). The work is most often cited by research in Signal Processing (99 citations), Cognitive Neuroscience (166 citations), Computational Mathematics (5 citations), Biomedical Engineering (223 citations) and Orthopedics and Sports Medicine (39 citations). Philippe Ravier has collaborated with scholars based in France, Algeria and Vietnam. Frequent co-authors include Olivier Buttelli, Pierre‐Olivier Amblard, Dario Farina, Meryem Jabloun, F. Leclerc, Rachid Harba, Lars Arendt‐Nielsen, Pascal Madeleine, Rachid Jennane and Antonio Dávalos. Their work appears in journals such as Biomedical Signal Processing and Control, Signal Processing, Journal of Electromyography and Kinesiology, IEEE Transactions on Instrumentation and Measurement and Pattern Recognition Letters.
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.