Yaqi Chu

641 total citations
31 papers, 460 citations indexed

About

Yaqi Chu is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Human-Computer Interaction. According to data from OpenAlex, Yaqi Chu has authored 31 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cognitive Neuroscience, 16 papers in Biomedical Engineering and 11 papers in Human-Computer Interaction. Recurrent topics in Yaqi Chu's work include EEG and Brain-Computer Interfaces (17 papers), Muscle activation and electromyography studies (12 papers) and Neuroscience and Neural Engineering (10 papers). Yaqi Chu is often cited by papers focused on EEG and Brain-Computer Interfaces (17 papers), Muscle activation and electromyography studies (12 papers) and Neuroscience and Neural Engineering (10 papers). Yaqi Chu collaborates with scholars based in China, New Zealand and United Kingdom. Yaqi Chu's co-authors include Xingang Zhao, Jianda Han, Yiwen Zhao, Daohui Zhang, Yijun Zou, Wei Xu, Yang Su, Dezhen Xiong, Bo Zhu and Zhiqiang Zhang and has published in prestigious journals such as ACS Applied Materials & Interfaces, Frontiers in Neuroscience and IEEE Transactions on Systems Man and Cybernetics Systems.

In The Last Decade

Yaqi Chu

30 papers receiving 451 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yaqi Chu China 11 299 172 119 113 65 31 460
Weibo Yi China 15 576 1.9× 134 0.8× 104 0.9× 260 2.3× 123 1.9× 39 649
Keun-Tae Kim South Korea 11 398 1.3× 148 0.9× 158 1.3× 220 1.9× 86 1.3× 32 482
Attila Korik United Kingdom 8 281 0.9× 80 0.5× 56 0.5× 120 1.1× 33 0.5× 17 376
Alkinoos Athanasiou Greece 11 253 0.8× 79 0.5× 55 0.5× 89 0.8× 34 0.5× 35 413
Rattanaphon Chaisaen Thailand 5 272 0.9× 63 0.4× 64 0.5× 68 0.6× 67 1.0× 8 367
Natasha Padfield United Kingdom 6 412 1.4× 70 0.4× 103 0.9× 182 1.6× 101 1.6× 8 477
Yunjun Nam South Korea 9 469 1.6× 125 0.7× 183 1.5× 163 1.4× 78 1.2× 15 534
Tushar Chouhan Singapore 8 366 1.2× 106 0.6× 117 1.0× 164 1.5× 95 1.5× 11 464
Phairot Autthasan Thailand 6 313 1.0× 54 0.3× 65 0.5× 83 0.7× 75 1.2× 13 381

Countries citing papers authored by Yaqi Chu

Since Specialization
Citations

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

Fields of papers citing papers by Yaqi Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaqi Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Yaqi Chu. A scholar is included among the top collaborators of Yaqi Chu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yaqi Chu. Yaqi Chu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chu, Yaqi, et al.. (2025). AMEEGNet: attention-based multiscale EEGNet for effective motor imagery EEG decoding. Frontiers in Neurorobotics. 19. 1540033–1540033. 5 indexed citations
2.
Li, Xiaoguang, et al.. (2024). 3D convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery EEG signal. Frontiers in Neurorobotics. 18. 1485640–1485640. 2 indexed citations
3.
4.
Xiong, Dezhen, et al.. (2024). Robotic telemanipulation with EMG-driven strategy-assisted shared control method. Science China Technological Sciences. 67(12). 3812–3824. 3 indexed citations
5.
Xiong, Dezhen, Daohui Zhang, Yaqi Chu, Yiwen Zhao, & Xingang Zhao. (2024). Intuitive Human-Robot-Environment Interaction with EMG Signals: A Review. IEEE/CAA Journal of Automatica Sinica. 11(5). 1075–1091. 21 indexed citations
6.
Chen, Yong, et al.. (2022). Bacillus arachidis sp. nov., Isolated from Peanut Rhizosphere Soil. Current Microbiology. 79(8). 231–231. 4 indexed citations
7.
Zhu, Bo, et al.. (2022). SeNic: An Open Source Dataset for sEMG-Based Gesture Recognition in Non-Ideal Conditions. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 30. 1252–1260. 39 indexed citations
8.
Zhu, Bo, et al.. (2022). A Novel Limbs-Free Variable Structure Wheelchair based on Face-Computer Interface (FCI) with Shared Control. 2022 International Conference on Robotics and Automation (ICRA). 5480–5486. 2 indexed citations
9.
Xiong, Dezhen, Daohui Zhang, Xingang Zhao, Yaqi Chu, & Yiwen Zhao. (2022). Breathing Pattern Recognition By the Fusion of EMG and Acceleration Signals. 2022 IEEE International Conference on Robotics and Biomimetics (ROBIO). 877–882. 2 indexed citations
10.
Zou, Yijun, Xingang Zhao, Yaqi Chu, et al.. (2022). A supervised independent component analysis algorithm for motion imagery-based brain computer interface. Biomedical Signal Processing and Control. 75. 103576–103576. 8 indexed citations
11.
Zhu, Bo, Daohui Zhang, Yaqi Chu, et al.. (2021). Face-Computer Interface (FCI): Intent Recognition Based on Facial Electromyography (fEMG) and Online Human-Computer Interface With Audiovisual Feedback. Frontiers in Neurorobotics. 15. 692562–692562. 12 indexed citations
12.
Zhu, Bo, et al.. (2021). A Novel Limbs-free Human-Computer Interface: Face-Computer Interface (FCI) with Channels Optimization. 2021 IEEE International Conference on Robotics and Biomimetics (ROBIO). 1092–1097. 1 indexed citations
13.
Chu, Yaqi, Bo Zhu, Xingang Zhao, & Yiwen Zhao. (2021). [Convolutional neural network based on temporal-spatial feature learning for motor imagery electroencephalogram signal decoding].. PubMed. 38(1). 1–9. 10 indexed citations
14.
Xiong, Dezhen, Daohui Zhang, Xingang Zhao, Yaqi Chu, & Yiwen Zhao. (2021). Synergy-Based Neural Interface for Human Gait Tracking With Deep Learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 29. 2271–2280. 35 indexed citations
15.
Chu, Yaqi, Xingang Zhao, Yijun Zou, et al.. (2020). Decoding multiclass motor imagery EEG from the same upper limb by combining Riemannian geometry features and partial least squares regression. Journal of Neural Engineering. 17(4). 46029–46029. 68 indexed citations
16.
Zou, Yijun, Xingang Zhao, Yaqi Chu, et al.. (2018). An inter-subject model to reduce the calibration time for motion imagination-based brain-computer interface. Medical & Biological Engineering & Computing. 57(4). 939–952. 10 indexed citations
17.
Chu, Yaqi, Xingang Zhao, Yijun Zou, et al.. (2018). A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network. Frontiers in Neuroscience. 12. 680–680. 46 indexed citations
18.
Chu, Yaqi, Xingang Zhao, Yijun Zou, Wei Xu, & Yiwen Zhao. (2018). Robot-Assisted Rehabilitation System Based on SSVEP Brain-Computer Interface for Upper Extremity. 1098–1103. 9 indexed citations
19.
Chu, Yaqi, Xingang Zhao, Jianda Han, & Yang Su. (2017). Physiological Signal-Based Method for Measurement of Pain Intensity. Frontiers in Neuroscience. 11. 279–279. 67 indexed citations
20.
Chu, Yaqi, Xingang Zhao, Jianda Han, Yiwen Zhao, & Jun Yao. (2014). SSVEP based brain-computer interface controlled functional electrical stimulation system for upper extremity rehabilitation. 10 indexed citations

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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