Michael D. Paskett
Impact in
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- Stroke Rehabilitation and Recovery
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- EEG and Brain-Computer Interfaces
- Motor Control and Adaptation
Papers in
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- Muscle activation and electromyography studies 6
- Advanced Sensor and Energy Harvesting Materials 2
- Prosthetics and Rehabilitation Robotics 1
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- EEG and Brain-Computer Interfaces 2
- Motor Control and Adaptation 1
- Co-authors
- Jacob A. George (5 shared papers)Gregory A. Clark (6 shared papers)Tyler S. Davis (4 shared papers)Mark R. Brinton (4 shared papers)Christopher C. Duncan (2 shared papers)David T. Kluger (1 shared paper)Masaru Teramoto (1 shared paper)
- Journals
- Journal of NeuroEngineering and Rehabilitation (1 paper)IEEE Transactions on Neural Systems and Rehabilitation Engineering (1 paper)Scientific Reports (1 paper)Frontiers in Robotics and AI (1 paper)2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (1 paper)
- Partner nations
- United States
In The Last Decade
Michael D. Paskett
6 papers receiving 68 citations
Peers
Comparison fields: 5 of 18
- Rehabilitation 13
- Cognitive Neuroscience 27
- Biomedical Engineering 56
- Cellular and Molecular Neuroscience 22
- Human-Computer Interaction 2
Countries citing papers authored by Michael D. Paskett
This map shows the geographic impact of Michael D. Paskett'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 Michael D. Paskett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael D. Paskett more than expected).
Fields of papers citing papers by Michael D. Paskett
This network shows the impact of papers produced by Michael D. Paskett. 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 Michael D. Paskett. The network helps show where Michael D. Paskett may publish in the future.
Co-authors
The 7 scholars most cited alongside Michael D. Paskett, 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 | 2021 | 23 | |
| 2 | 2019 | 19 | |
| 3 | 2020 | 17 | |
| 4 | 2024 | 4 | |
| 5 | 2021 | 3 | |
| 6 | 2020 | 3 |
About Michael D. Paskett
Michael D. Paskett is a scholar working on Biomedical Engineering, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Rehabilitation and Infectious Diseases, having authored 6 papers that have together received 69 indexed citations. Recurring topics across this work include Muscle activation and electromyography studies (6 papers), Neuroscience and Neural Engineering (2 papers), EEG and Brain-Computer Interfaces (2 papers), Stroke Rehabilitation and Recovery (2 papers), Advanced Sensor and Energy Harvesting Materials (2 papers), Prosthetics and Rehabilitation Robotics (1 paper) and Motor Control and Adaptation (1 paper). The work is most often cited by research in Rehabilitation (13 citations), Cognitive Neuroscience (27 citations), Biomedical Engineering (56 citations), Cellular and Molecular Neuroscience (22 citations) and Human-Computer Interaction (2 citations). Michael D. Paskett has collaborated with scholars based in United States. Frequent co-authors include Jacob A. George, Gregory A. Clark, Tyler S. Davis, Mark R. Brinton, Christopher C. Duncan, David T. Kluger and Masaru Teramoto. Their work appears in journals such as Journal of NeuroEngineering and Rehabilitation, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Scientific Reports, Frontiers in Robotics and AI and 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).
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.