Ping Zhou

6.8k total citations
218 papers, 5.1k citations indexed

About

Ping Zhou is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ping Zhou has authored 218 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 163 papers in Biomedical Engineering, 96 papers in Cognitive Neuroscience and 51 papers in Cellular and Molecular Neuroscience. Recurrent topics in Ping Zhou's work include Muscle activation and electromyography studies (160 papers), EEG and Brain-Computer Interfaces (74 papers) and Neuroscience and Neural Engineering (49 papers). Ping Zhou is often cited by papers focused on Muscle activation and electromyography studies (160 papers), EEG and Brain-Computer Interfaces (74 papers) and Neuroscience and Neural Engineering (49 papers). Ping Zhou collaborates with scholars based in United States, China and Hong Kong. Ping Zhou's co-authors include Xu Zhang, William Z. Rymer, Xiaoyan Li, Todd Kuiken, Maoqi Chen, Sheng Li, Guanglin Li, Xiang Chen, Zhiyuan Lu and Jie Liu and has published in prestigious journals such as The Lancet, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Ping Zhou

205 papers receiving 5.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ping Zhou United States 35 3.7k 2.3k 1.4k 1.0k 582 218 5.1k
José L. Contreras-Vidal United States 46 2.9k 0.8× 5.2k 2.2× 1.6k 1.2× 1.0k 1.0× 468 0.8× 200 7.4k
Catherine Dißelhorst-Klug Germany 29 4.6k 1.2× 1.7k 0.7× 592 0.4× 810 0.8× 426 0.7× 80 7.5k
Roger Gassert Switzerland 44 3.5k 1.0× 2.5k 1.1× 358 0.3× 2.6k 2.5× 870 1.5× 247 7.3k
Loredana Zollo Italy 34 3.0k 0.8× 1.7k 0.7× 1.0k 0.8× 987 1.0× 214 0.4× 213 4.6k
Janis J. Daly United States 29 1.1k 0.3× 1.6k 0.7× 809 0.6× 1.3k 1.3× 452 0.8× 77 3.1k
Miloš R. Popović Canada 48 3.9k 1.0× 2.0k 0.8× 1.7k 1.3× 1.8k 1.8× 637 1.1× 317 7.4k
B. Conway United Kingdom 29 2.4k 0.6× 2.7k 1.2× 1.6k 1.2× 344 0.3× 1.0k 1.8× 114 5.3k
Serge H. Roy United States 37 3.5k 0.9× 1.4k 0.6× 585 0.4× 324 0.3× 345 0.6× 77 5.4k
Alessandra Pedrocchi Italy 36 1.9k 0.5× 1.5k 0.6× 736 0.5× 1.1k 1.1× 323 0.6× 233 4.5k
Francesco Negro Italy 40 4.5k 1.2× 3.1k 1.3× 1.6k 1.2× 270 0.3× 297 0.5× 162 5.7k

Countries citing papers authored by Ping Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Ping Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ping Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Ping Zhou. A scholar is included among the top collaborators of Ping Zhou 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 Ping Zhou. Ping Zhou 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.
Zhang, Yanhui, et al.. (2025). MScanFit and StairFit Motor Unit Number Estimation of the Extensor Digitorum Brevis and Abductor Digiti Minimi Muscles. Muscle & Nerve. 71(3). 446–449. 2 indexed citations
2.
Li, Le, et al.. (2024). Clustering index analysis on EMG-Torque relation-based representation of complex neuromuscular changes after spinal cord injury. Journal of Electromyography and Kinesiology. 76. 102885–102885.
3.
Zhou, Ping. (2024). Surface EMG in China: a report on the 2023 surface EMG symposium. SHILAP Revista de lepidopterología. 5. 1353564–1353564. 2 indexed citations
4.
Zhang, Dan, et al.. (2024). Effect of surface electrode recording area on compound muscle action potential scan processing for motor unit number estimation. Frontiers in Neuroscience. 18. 1382871–1382871. 1 indexed citations
5.
Li, Xiaoyan, Maoqi Chen, Paul E. Barkhaus, et al.. (2024). F wave analysis based on the compound muscle action potential scan. Muscle & Nerve. 70(3). 395–401.
6.
Wang, Yutao, et al.. (2024). Maintenance of callus-associated endophyte balance to mitigate oxidative browning in plant tissue culture practices. Plant Cell Tissue and Organ Culture (PCTOC). 157(2).
7.
Chen, Xiaofeng, et al.. (2024). Long-term air-stable amplified spontaneous emission in quasi-2D perovskite films through ligand engineering. Journal of Materials Chemistry C. 12(22). 8119–8126. 4 indexed citations
8.
Houston, Michael, et al.. (2023). Alterations of Motor Unit Characteristics Associated With Muscle Fatigue. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 4831–4838. 3 indexed citations
9.
Chen, Maoqi & Ping Zhou. (2021). Automatic decomposition of pediatric high density surface EMG: A pilot study. SHILAP Revista de lepidopterología. 12. 100094–100094.
10.
Houston, Michael, Xiaoyan Li, Ping Zhou, et al.. (2021). Alterations in Muscle Networks in the Upper Extremity of Chronic Stroke Survivors. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 29. 1026–1034. 27 indexed citations
11.
Hu, Huijing, Wai Leung Ambrose Lo, Xiaoyun Wang, Le Li, & Ping Zhou. (2021). Interrater and Intrarater Reliability of Electrical Impedance Myography: A Comparison between Large and Small Handheld Electrode Arrays. Journal of Healthcare Engineering. 2021. 1–8. 3 indexed citations
12.
13.
Bao, Shi‐Chun, et al.. (2019). Pathway-specific modulatory effects of neuromuscular electrical stimulation during pedaling in chronic stroke survivors. Journal of NeuroEngineering and Rehabilitation. 16(1). 143–143. 16 indexed citations
14.
Chen, Yen-Ting, Shengai Li, Ping Zhou, & Sheng Li. (2019). A startling acoustic stimulation (SAS)-TMS approach to assess the reticulospinal system in healthy and stroke subjects. Journal of the Neurological Sciences. 399. 82–88. 11 indexed citations
15.
Lu, Zhiyuan, Raymond Kai‐Yu Tong, Xu Zhang, Sheng Li, & Ping Zhou. (2018). Myoelectric Pattern Recognition for Controlling a Robotic Hand: A Feasibility Study in Stroke. IEEE Transactions on Biomedical Engineering. 66(2). 365–372. 80 indexed citations
16.
17.
Chen, Yen‐Ting, Shengai Li, Ping Zhou, & Sheng Li. (2016). Different Effects of Startling Acoustic Stimuli (SAS) on TMS-Induced Responses at Rest and during Sustained Voluntary Contraction. Frontiers in Human Neuroscience. 10. 396–396. 16 indexed citations
18.
19.
Barkhaus, Paul E., et al.. (2014). Spike sorting paradigm for classification of multi-channel recorded fasciculation potentials. Computers in Biology and Medicine. 55. 26–35. 6 indexed citations
20.
Zhou, Ping, Madeleine M. Lowery, & William Z. Rymer. (2006). EXTRACTING MOTOR UNIT FIRING INFORMATION BY INDEPENDENT COMPONENT ANALYSIS OF SURFACE ELECTROMYOGRAM: A PRELIMINARY STUDY USING A SIMULATION APPROACH. 7. 19–28. 4 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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