Jun‐Uk Chu

30 papers receiving 1.2k citations

Peers

Jun‐Uk Chu
Comparison fields: 5 of 126
  • Human-Computer Interaction 200
  • Cognitive Neuroscience 515
  • Cellular and Molecular Neuroscience 343
  • Biomedical Engineering 809
  • Rehabilitation 42
Replace Emanuele Gruppioni with:
Emanuele Gruppioni Italy
Changcheng Wu China
Dapeng Yang China
Marco Maggiali Italy
Reza Fazel-Rezai United States
Hong Zeng China
Xiangyu Liu China
Brock A. Wester United States
Matthew S. Johannes United States
Jun Xie China
Jun‐Uk Chu relative to Emanuele Gruppioni Italy Emanuele Gruppioni's profile →
Citations per field
00.5×2.9×
Emanuele Gruppioni · 1×
Citations per year

Countries citing papers authored by Jun‐Uk Chu

Since Specialization
Citations

This map shows the geographic impact of Jun‐Uk Chu'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 Jun‐Uk Chu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun‐Uk Chu more than expected).

Fields of papers citing papers by Jun‐Uk Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun‐Uk Chu. 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 Jun‐Uk Chu. The network helps show where Jun‐Uk Chu may publish in the future.

Co-authors

The 25 scholars most cited alongside Jun‐Uk Chu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun‐Uk Chu Line = papers co-authored together Jun‐Uk Chu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006272
2 2017266
3 2007226
4 2012137
5 2006119
6 200831
7 200524
8 200923
9 201823
10 200423
11 201222
12 200616
13 201216
14 201616
15 201614
16 20089
17 20158
18 20078
19
A Real-Time Pattern Recognition for Multifunction Myoelectric Hand Control
20057
20 20174

About Jun‐Uk Chu

Jun‐Uk Chu is a scholar working on Cognitive Neuroscience, Biomedical Engineering, Cellular and Molecular Neuroscience, Control and Systems Engineering and Human-Computer Interaction, having authored 31 papers that have together received 1.3k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (18 papers), Muscle activation and electromyography studies (16 papers), Neuroscience and Neural Engineering (12 papers), Gaze Tracking and Assistive Technology (4 papers), Robotics and Automated Systems (3 papers), Hand Gesture Recognition Systems (3 papers), Robotic Path Planning Algorithms (2 papers) and Conducting polymers and applications (2 papers). The work is most often cited by research in Human-Computer Interaction (200 citations), Cognitive Neuroscience (515 citations), Cellular and Molecular Neuroscience (343 citations), Biomedical Engineering (809 citations) and Rehabilitation (42 citations). Jun‐Uk Chu has collaborated with scholars based in South Korea, Singapore and Japan. Frequent co-authors include Mu-Seong Mun, Inhyuk Moon, Yun-Jung Lee, Inchan Youn, Hyungmin Kim, Ahnsei Shon, Myung-Joon Lee, Kuiwon Choi, Ick Chan Kwon and Kwangmeyung Kim. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, International Journal of Precision Engineering and Manufacturing, Journal of Microelectromechanical Systems, IEEE/ASME Transactions on Mechatronics and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

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.

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