Yongtian He

2.7k total citations · 1 hit paper
16 papers, 1.8k citations indexed

About

Yongtian He is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Yongtian He has authored 16 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cognitive Neuroscience, 9 papers in Biomedical Engineering and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Yongtian He's work include EEG and Brain-Computer Interfaces (12 papers), Muscle activation and electromyography studies (7 papers) and Neuroscience and Neural Engineering (4 papers). Yongtian He is often cited by papers focused on EEG and Brain-Computer Interfaces (12 papers), Muscle activation and electromyography studies (7 papers) and Neuroscience and Neural Engineering (4 papers). Yongtian He collaborates with scholars based in United States, Spain and Bangladesh. Yongtian He's co-authors include José L. Contreras-Vidal, Alexander Craik, Trieu Phat Luu, Sho Nakagome, David Eguren, Kevin Nathan, José M. Azorín, Robert G. Grossman, Samuel M. Brown and José L. Pons and has published in prestigious journals such as Scientific Reports, Frontiers in Human Neuroscience and Scientific Data.

In The Last Decade

Yongtian He

16 papers receiving 1.7k citations

Hit Papers

Deep learning for electroencephalogram (EEG) classificati... 2019 2026 2021 2023 2019 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Deep learning for electroencephalogram (EEG) classification tasks: a review
    2019 980 citations Alexander Craik, Yongtian He et al. Journal of Neural Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yongtian He United States 12 1.3k 545 379 243 203 16 1.8k
Aleksandra Vučković United Kingdom 23 1.1k 0.8× 404 0.7× 425 1.1× 97 0.4× 114 0.6× 95 1.6k
Teodoro Solis‐Escalante Netherlands 22 1.9k 1.5× 803 1.5× 763 2.0× 389 1.6× 234 1.2× 42 2.4k
Hongzhi Qi China 26 1.7k 1.3× 331 0.6× 696 1.8× 63 0.3× 271 1.3× 124 2.0k
Fiorenzo Artoni Switzerland 22 1.2k 0.9× 756 1.4× 530 1.4× 106 0.4× 102 0.5× 52 1.7k
Selina C. Wriessnegger Austria 22 1.4k 1.1× 359 0.7× 466 1.2× 54 0.2× 200 1.0× 64 1.7k
Han-Jeong Hwang South Korea 16 849 0.7× 282 0.5× 329 0.9× 122 0.5× 160 0.8× 36 1.1k
Mads Jochumsen Denmark 21 1.2k 0.9× 695 1.3× 547 1.4× 193 0.8× 306 1.5× 85 1.6k
Iñaki Iturrate Switzerland 24 1.9k 1.5× 430 0.8× 840 2.2× 179 0.7× 455 2.2× 46 2.2k
Moritz Grosse‐Wentrup Germany 21 2.0k 1.6× 265 0.5× 836 2.2× 97 0.4× 317 1.6× 78 2.3k
R. Leeb Switzerland 20 2.2k 1.7× 340 0.6× 896 2.4× 112 0.5× 519 2.6× 27 2.4k

Countries citing papers authored by Yongtian He

Since Specialization
Citations

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

Fields of papers citing papers by Yongtian He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yongtian He

This figure shows the co-authorship network connecting the top 25 collaborators of Yongtian He. A scholar is included among the top collaborators of Yongtian He 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 Yongtian He. Yongtian He is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Paek, Andrew, Justin Brantley, Kevin Nathan, et al.. (2021). A Roadmap Towards Standards for Neurally Controlled End Effectors. IEEE Open Journal of Engineering in Medicine and Biology. 2. 84–90. 6 indexed citations
2.
Nakagome, Sho, et al.. (2020). An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding. Scientific Reports. 10(1). 4372–4372. 62 indexed citations
3.
Craik, Alexander, Yongtian He, & José L. Contreras-Vidal. (2019). Deep learning for electroencephalogram (EEG) classification tasks: a review. Journal of Neural Engineering. 16(3). 31001–31001. 980 indexed citations breakdown →
4.
He, Yongtian, David Eguren, José M. Azorín, et al.. (2018). Brain–machine interfaces for controlling lower-limb powered robotic systems. Journal of Neural Engineering. 15(2). 21004–21004. 166 indexed citations
5.
He, Yongtian, Trieu Phat Luu, Kevin Nathan, Sho Nakagome, & José L. Contreras-Vidal. (2018). A mobile brain-body imaging dataset recorded during treadmill walking with a brain-computer interface. Scientific Data. 5(1). 180074–180074. 31 indexed citations
6.
He, Yongtian, David Eguren, Trieu Phat Luu, & José L. Contreras-Vidal. (2017). Risk management and regulations for lower limb medical exoskeletons: a review. Medical Devices Evidence and Research. Volume 10. 89–107. 110 indexed citations
7.
Luu, Trieu Phat, Sho Nakagome, Yongtian He, & José L. Contreras-Vidal. (2017). Real-time EEG-based brain-computer interface to a virtual avatar enhances cortical involvement in human treadmill walking. Scientific Reports. 7(1). 8895–8895. 68 indexed citations
8.
Luu, Trieu Phat, Yongtian He, Sho Nakagome, & José L. Contreras-Vidal. (2017). EEG-based brain-computer interface to a virtual walking avatar engages cortical adaptation. 3054–3057. 11 indexed citations
9.
Luu, Trieu Phat, Yongtian He, Sho Nakagome, et al.. (2017). Multi-Trial Gait Adaptation of Healthy Individuals during Visual Kinematic Perturbations. Frontiers in Human Neuroscience. 11. 320–320. 10 indexed citations
10.
He, Yongtian, David Eguren, Trieu Phat Luu, & José L. Contreras-Vidal. (2017). Risk and adverse events related to lower-limb exoskeletons. 6 indexed citations
11.
Contreras-Vidal, José L., Nikunj Bhagat, Justin Brantley, et al.. (2016). Powered exoskeletons for bipedal locomotion after spinal cord injury. Journal of Neural Engineering. 13(3). 31001–31001. 142 indexed citations
12.
Luu, Trieu Phat, et al.. (2016). Unscented Kalman filter for neural decoding of human treadmill walking from non-invasive electroencephalography. PubMed. 2016. 1548–1551. 19 indexed citations
13.
Luu, Trieu Phat, Yongtian He, Samuel M. Brown, Sho Nakagome, & José L. Contreras-Vidal. (2016). Gait adaptation to visual kinematic perturbations using a real-time closed-loop brain–computer interface to a virtual reality avatar. Journal of Neural Engineering. 13(3). 36006–36006. 83 indexed citations
14.
Luu, Trieu Phat, Yongtian He, Samuel M. Brown, Sho Nakagome, & José L. Contreras-Vidal. (2015). A closed-loop brain computer interface to a virtual reality avatar: Gait adaptation to visual kinematic perturbations. PubMed. 2015. 30–37. 29 indexed citations
15.
He, Yongtian & José L. Contreras-Vidal. (2015). Classification of finger vibrotactile input using scalp EEG. PubMed. 2015. 4717–4720. 2 indexed citations
16.
He, Yongtian, Kevin Nathan, Anusha Venkatakrishnan, et al.. (2014). An integrated neuro-robotic interface for stroke rehabilitation using the NASA X1 powered lower limb exoskeleton. PubMed. 2014. 3985–3988. 50 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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