Lanlan Chen
Impact in
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- Emotion and Mood Recognition
- Sleep and Work-Related Fatigue
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
Papers in
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- Sleep and Work-Related Fatigue 6
- Emotion and Mood Recognition 2
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- Heart Rate Variability and Autonomic Control 5
- Co-authors
- Junzhong Zou (4 shared papers)Jian Zhang (2 shared papers)Yu Zhao (2 shared papers)Pengfei Ye (1 shared paper)Wei Chen (1 shared paper)Dongdong Li (1 shared paper)Zhenzhen Song (1 shared paper)Ao Zhang (1 shared paper)
In The Last Decade
Lanlan Chen
14 papers receiving 638 citations
Peers
Comparison fields: 5 of 79
- Experimental and Cognitive Psychology 364
- Cognitive Neuroscience 372
- Human-Computer Interaction 61
- Cardiology and Cardiovascular Medicine 178
- Signal Processing 79
Countries citing papers authored by Lanlan Chen
This map shows the geographic impact of Lanlan Chen'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 Lanlan Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lanlan Chen more than expected).
Fields of papers citing papers by Lanlan Chen
This network shows the impact of papers produced by Lanlan Chen. 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 Lanlan Chen. The network helps show where Lanlan Chen may publish in the future.
Co-authors
The 23 scholars most cited alongside Lanlan Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 193 | |
| 2 | 2015 | 147 | |
| 3 | 2020 | 139 | |
| 4 | 2013 | 70 | |
| 5 | 2019 | 64 | |
| 6 | 2021 | 10 | |
| 7 | 2010 | 9 | |
| 8 | 2010 | 6 | |
| 9 | 2024 | 4 | |
| 10 | 2024 | 4 | |
| 11 | 2012 | 4 | |
| 12 | 2024 | 2 | |
| 13 | Recurrence quantification analysis of EEGs for mental fatigue evaluation | 2012 | 2 |
| 14 | 2009 | 1 |
About Lanlan Chen
Lanlan Chen is a scholar working on Experimental and Cognitive Psychology, Cardiology and Cardiovascular Medicine, Cognitive Neuroscience, Biomedical Engineering and Social Psychology, having authored 14 papers that have together received 655 indexed citations. Recurring topics across this work include Sleep and Work-Related Fatigue (6 papers), Heart Rate Variability and Autonomic Control (5 papers), EEG and Brain-Computer Interfaces (5 papers), Non-Invasive Vital Sign Monitoring (3 papers), Blind Source Separation Techniques (2 papers), Emotion and Mood Recognition (2 papers), Color perception and design (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (364 citations), Cognitive Neuroscience (372 citations), Human-Computer Interaction (61 citations), Cardiology and Cardiovascular Medicine (178 citations) and Signal Processing (79 citations). Lanlan Chen has collaborated with scholars based in China and Japan. Frequent co-authors include Junzhong Zou, Jian Zhang, Yu Zhao, Pengfei Ye, Wei Chen, Dongdong Li, Zhenzhen Song, Ao Zhang, Junzhong Zou and Jian Zhang. Their work appears in journals such as Expert Systems with Applications, Biomedical Signal Processing and Control, IEEE Transactions on Intelligent Transportation Systems, Journal of Applied Electrochemistry and Frontiers in Psychology.
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.