A. W. Monster
Impact in
- Cognitive Neuroscience top 5%
- Motor Control and Adaptation
- EEG and Brain-Computer Interfaces
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- Neuroscience and Neural Engineering
Papers in
-
- Muscle activation and electromyography studies 8
- Advanced Sensor and Energy Harvesting Materials 2
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- Neuroscience and Neural Engineering 4
- Co-authors
- Daniel Kernell (3 shared papers)Hsiang‐Yu Chan (2 shared papers)David O’Connor (1 shared paper)Hung Tuck Chan (1 shared paper)Donna O’Connor (1 shared paper)Y. Tamai (1 shared paper)
- Journals
- Experimental Brain Research (2 papers)Brain Research (2 papers)Experimental Neurology (1 paper)IEEE Transactions on Biomedical Engineering (1 paper)Journal of Neurophysiology (1 paper)
- Partner nations
- United StatesNetherlands
In The Last Decade
A. W. Monster
11 papers receiving 765 citations
Peers
Comparison fields: 5 of 72
- Cognitive Neuroscience 373
- Cellular and Molecular Neuroscience 291
- Neurology 122
- Orthopedics and Sports Medicine 122
- Biomedical Engineering 605
Countries citing papers authored by A. W. Monster
This map shows the geographic impact of A. W. Monster'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 A. W. Monster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. W. Monster more than expected).
Fields of papers citing papers by A. W. Monster
This network shows the impact of papers produced by A. W. Monster. 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 A. W. Monster. The network helps show where A. W. Monster may publish in the future.
Co-authors
The 6 scholars most cited alongside A. W. Monster, 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 | 1977 | 260 | |
| 2 | 1982 | 156 | |
| 3 | 1982 | 143 | |
| 4 | 1978 | 104 | |
| 5 | 1978 | 40 | |
| 6 | 1981 | 32 | |
| 7 | 1980 | 26 | |
| 8 | 1979 | 17 | |
| 9 | 1980 | 15 | |
| 10 | Dantrolene sodium: its effect on extrafusal muscle fibers. | 1974 | 11 |
| 11 | Two ranges in the firing rate response of volitionally activated low-threshold EDC motor units. | 1978 | 2 |
About A. W. Monster
A. W. Monster is a scholar working on Biomedical Engineering, Cellular and Molecular Neuroscience, Cognitive Neuroscience, Orthopedics and Sports Medicine and Computer Networks and Communications, having authored 11 papers that have together received 806 indexed citations. Recurring topics across this work include Muscle activation and electromyography studies (8 papers), Neuroscience and Neural Engineering (4 papers), Motor Control and Adaptation (4 papers), Sports Performance and Training (3 papers), Advanced Sensor and Energy Harvesting Materials (2 papers), Ocular Surface and Contact Lens (1 paper), Glaucoma and retinal disorders (1 paper) and Pain Mechanisms and Treatments (1 paper). The work is most often cited by research in Cognitive Neuroscience (373 citations), Cellular and Molecular Neuroscience (291 citations), Neurology (122 citations), Orthopedics and Sports Medicine (122 citations) and Biomedical Engineering (605 citations). A. W. Monster has collaborated with scholars based in United States and Netherlands. Frequent co-authors include Daniel Kernell, Hsiang‐Yu Chan, David O’Connor, Hung Tuck Chan, Donna O’Connor and Y. Tamai. Their work appears in journals such as Experimental Brain Research, Brain Research, Experimental Neurology, IEEE Transactions on Biomedical Engineering and Journal of Neurophysiology.
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.