Muye Pang

756 total citations
64 papers, 560 citations indexed

About

Muye Pang is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Rehabilitation. According to data from OpenAlex, Muye Pang has authored 64 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Biomedical Engineering, 23 papers in Cognitive Neuroscience and 19 papers in Rehabilitation. Recurrent topics in Muye Pang's work include Muscle activation and electromyography studies (46 papers), Prosthetics and Rehabilitation Robotics (22 papers) and Stroke Rehabilitation and Recovery (19 papers). Muye Pang is often cited by papers focused on Muscle activation and electromyography studies (46 papers), Prosthetics and Rehabilitation Robotics (22 papers) and Stroke Rehabilitation and Recovery (19 papers). Muye Pang collaborates with scholars based in China, Japan and United Kingdom. Muye Pang's co-authors include Shuxiang Guo, Kui Xiang, Songyuan Zhang, Hidenori Ishihara, Hideyuki Hirata, Zhibin Song, Baofeng Gao, Qiang Huang, Zhanxia Zhu and Fang Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Muye Pang

59 papers receiving 551 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Muye Pang China 12 394 172 168 73 60 64 560
Khairul Anam Indonesia 10 369 0.9× 155 0.9× 151 0.9× 42 0.6× 107 1.8× 68 637
Weiqun Wang China 17 422 1.1× 234 1.4× 259 1.5× 81 1.1× 132 2.2× 67 826
Guozheng Xu China 12 246 0.6× 127 0.7× 211 1.3× 65 0.9× 20 0.3× 41 438
Kuankuan Zhao China 7 312 0.8× 94 0.5× 144 0.9× 95 1.3× 22 0.4× 8 471
Qichuan Ding China 10 382 1.0× 205 1.2× 90 0.5× 46 0.6× 42 0.7× 32 504
Michele Folgheraiter Kazakhstan 14 360 0.9× 220 1.3× 126 0.8× 86 1.2× 73 1.2× 49 551
Clemente Lauretti Italy 13 272 0.7× 111 0.6× 136 0.8× 128 1.8× 33 0.6× 29 431
Francisco J. Badesa Spain 16 409 1.0× 219 1.3× 391 2.3× 71 1.0× 17 0.3× 46 716
Giuseppe Averta Italy 13 250 0.6× 183 1.1× 61 0.4× 197 2.7× 50 0.8× 45 468
Chi Zhu Japan 15 531 1.3× 180 1.0× 105 0.6× 154 2.1× 27 0.5× 82 725

Countries citing papers authored by Muye Pang

Since Specialization
Citations

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

Fields of papers citing papers by Muye Pang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muye Pang

This figure shows the co-authorship network connecting the top 25 collaborators of Muye Pang. A scholar is included among the top collaborators of Muye Pang 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 Muye Pang. Muye Pang 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.
Pang, Muye, et al.. (2025). Influence factors on airborne pollen dispersal in a tropical island over China: morphology and meteorology. Atmospheric Environment X. 26. 100323–100323.
2.
Luo, Jing, Chao Zeng, Yiming Jiang, et al.. (2024). Robotics Perception and Control: Key Technologies and Applications. Micromachines. 15(4). 531–531. 11 indexed citations
5.
Li, Ruiqing, et al.. (2023). A membership-function–based broad learning system for human–robot interaction force estimation under drawing task. Medical & Biological Engineering & Computing. 61(8). 1975–1992. 4 indexed citations
7.
Ding, Ying, et al.. (2023). Muscle Synergy Structure Consistency During Lifting Motion with Exoskeleton. 46–49. 1 indexed citations
8.
Liu, Changcheng, et al.. (2023). An Improved Combined Framework of Force Measurement With Friction Model for Harmonic Gear. IEEE Sensors Journal. 23(9). 9943–9951. 5 indexed citations
9.
Zhu, Guorong, et al.. (2022). Research on the Influence of Slot-Pole Combination on the Performance of Quadruped Robot Joint Motor. 2022 IEEE 5th International Electrical and Energy Conference (CIEEC). 1762–1767. 1 indexed citations
10.
Peng, Yaling, et al.. (2022). Cost Function Determination for Human Lifting Motion via the Bilevel Optimization Technology. Frontiers in Bioengineering and Biotechnology. 10. 883633–883633. 2 indexed citations
11.
Wang, Jinfeng, et al.. (2021). Effect of Muscle Fatigue on Surface Electromyography-Based Hand Grasp Force Estimation. Applied Bionics and Biomechanics. 2021. 1–12. 21 indexed citations
12.
Xiang, Kui, et al.. (2020). Design of Muscle Reflex Control for Upright Standing Push-Recovery Based on a Series Elastic Robot Ankle Joint. Frontiers in Neurorobotics. 14. 20–20. 1 indexed citations
13.
Jiang, Shan, et al.. (2020). Grasp Detection Based on Faster Region CNN. 323–328. 7 indexed citations
14.
Zhou, Yaqian, et al.. (2020). Evaluation of Activation Mechanism of Ankle Muscles During Upright Stance Push-recovery. 45. 483–488. 1 indexed citations
15.
Xiang, Kui, et al.. (2019). Personalised Control of Robotic Ankle Exoskeleton Through Experience-Based Adaptive Fuzzy Inference. IEEE Access. 7. 72221–72233. 29 indexed citations
16.
Xiang, Kui, et al.. (2018). An integrated particle swarm optimization approach hybridizing a new self-adaptive particle swarm optimization with a modified differential evolution. Neural Computing and Applications. 32(9). 4849–4883. 35 indexed citations
17.
Guo, Shuxiang, Muye Pang, Baofeng Gao, Hideyuki Hirata, & Hidenori Ishihara. (2015). Comparison of sEMG-Based Feature Extraction and Motion Classification Methods for Upper-Limb Movement. Sensors. 15(4). 9022–9038. 60 indexed citations
18.
Guo, Shuxiang, et al.. (2014). Study on the comparison of three different upper limb motion recognition methods. 208–212. 5 indexed citations
19.
Pang, Muye, Shuxiang Guo, & Songyuan Zhang. (2014). Interaction force transfer for characteristic evaluation of touch motion. 7. 1237–1242. 1 indexed citations
20.
Pang, Muye, Shuxiang Guo, & Zhibin Song. (2012). Study on the sEMG Driven Upper Limb Exoskeleton Rehabilitation Device in Bilateral Rehabilitation. Journal of Robotics and Mechatronics. 24(4). 585–594. 26 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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