Kai Gui
Impact in
- Rehabilitation top 2%
- Stroke Rehabilitation and Recovery
- Human-Computer Interaction top 5%
- Gaze Tracking and Assistive Technology
Papers in
-
- Muscle activation and electromyography studies 10
- Prosthetics and Rehabilitation Robotics 5
-
- EEG and Brain-Computer Interfaces 6
- Motor Control and Adaptation 2
- Co-authors
- Dingguo Zhang (13 shared papers)Honghai Liu (6 shared papers)U-Xuan Tan (2 shared papers)Xu Yang (1 shared paper)Xinjun Sheng (1 shared paper)Xiaokang Shu (1 shared paper)Kairu Li (1 shared paper)Yu Zhou (1 shared paper)
- Journals
- Robotics and Autonomous Systems (1 paper)Journal of Electromyography and Kinesiology (1 paper)IEEE Transactions on Neural Systems and Rehabilitation Engineering (1 paper)IEEE Sensors Journal (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)
- Partner nations
- ChinaUnited KingdomSingapore
In The Last Decade
Kai Gui
13 papers receiving 465 citations
Peers
Comparison fields: 5 of 49
- Rehabilitation 192
- Human-Computer Interaction 62
- Cognitive Neuroscience 173
- Biomedical Engineering 349
- Cellular and Molecular Neuroscience 77
Countries citing papers authored by Kai Gui
This map shows the geographic impact of Kai Gui'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 Kai Gui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Gui more than expected).
Fields of papers citing papers by Kai Gui
This network shows the impact of papers produced by Kai Gui. 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 Kai Gui. The network helps show where Kai Gui may publish in the future.
Co-authors
The 21 scholars most cited alongside Kai Gui, 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 | 2019 | 129 | |
| 2 | 2017 | 83 | |
| 3 | 2019 | 74 | |
| 4 | 2018 | 58 | |
| 5 | 2020 | 44 | |
| 6 | 2017 | 27 | |
| 7 | 2017 | 20 | |
| 8 | 2016 | 15 | |
| 9 | 2015 | 9 | |
| 10 | 2014 | 5 | |
| 11 | 2016 | 4 | |
| 12 | 2019 | 4 | |
| 13 | 2020 | 3 | |
| 14 | 2024 | 0 | |
| 15 | 2025 | 0 |
About Kai Gui
Kai Gui is a scholar working on Biomedical Engineering, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Rehabilitation and Human-Computer Interaction, having authored 15 papers that have together received 475 indexed citations. Recurring topics across this work include Muscle activation and electromyography studies (10 papers), EEG and Brain-Computer Interfaces (6 papers), Neuroscience and Neural Engineering (5 papers), Prosthetics and Rehabilitation Robotics (5 papers), Stroke Rehabilitation and Recovery (5 papers), Gaze Tracking and Assistive Technology (2 papers), Motor Control and Adaptation (2 papers) and Balance, Gait, and Falls Prevention (1 paper). The work is most often cited by research in Rehabilitation (192 citations), Human-Computer Interaction (62 citations), Cognitive Neuroscience (173 citations), Biomedical Engineering (349 citations) and Cellular and Molecular Neuroscience (77 citations). Kai Gui has collaborated with scholars based in China, United Kingdom and Singapore. Frequent co-authors include Dingguo Zhang, Honghai Liu, U-Xuan Tan, Xu Yang, Xinjun Sheng, Xiaokang Shu, Kairu Li, Yu Zhou, Yinfeng Fang and Yong Ren. Their work appears in journals such as Robotics and Autonomous Systems, Journal of Electromyography and Kinesiology, IEEE Transactions on Neural Systems and Rehabilitation Engineering, IEEE Sensors Journal and IEEE Journal of Biomedical and Health Informatics.
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.