Kan Luo

520 citations
38 papers · 395 · h-index 10

Impact in

Papers in

Kan Luo

35 papers receiving 387 citations

Peers

Kan Luo
Comparison fields: 5 of 73
  • Cardiology and Cardiovascular Medicine 216
  • Cognitive Neuroscience 137
  • Bioengineering 26
  • Signal Processing 46
  • Biomedical Engineering 153
Replace R. N. Ponnalagu with:
R. N. Ponnalagu India
Chih‐Hung Chen Canada
Venkata Rajesh Pamula United States
Boo-Ho Yang United States
Hamidreza Rezaee-Dehsorkh Iran
Amar Rouane France
Dongyi Chen China
Hyung-Ro Yoon South Korea
Jia Wen China
Nassim Ravanshad Iran
Kan Luo relative to R. N. Ponnalagu India R. N. Ponnalagu's profile →
Citations per field
00.5×10×14×
R. N. Ponnalagu · 1×
Citations per year

Countries citing papers authored by Kan Luo

Since Specialization
Citations

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

Fields of papers citing papers by Kan Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Kan Luo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kan Luo Line = papers co-authored together Kan Luo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017101
2 201861
3 201439
4 200020
5 201918
6 201713
7 200113
8 201413
9 201613
10 201710
11 20009
12 20249
13 20188
14 20127
15 20006
16 20186
17 20245
18 20165
19 20244
20 20134

About Kan Luo

Kan Luo is a scholar working on Biomedical Engineering, Cardiology and Cardiovascular Medicine, Signal Processing, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 38 papers that have together received 395 indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (12 papers), Non-Invasive Vital Sign Monitoring (9 papers), Music and Audio Processing (4 papers), EEG and Brain-Computer Interfaces (4 papers), Neural Networks and Applications (4 papers), Innovative Microfluidic and Catalytic Techniques Innovation (3 papers), Emotion and Mood Recognition (3 papers) and Wireless Body Area Networks (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (216 citations), Cognitive Neuroscience (137 citations), Bioengineering (26 citations), Signal Processing (46 citations) and Biomedical Engineering (153 citations). Kan Luo has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Jianqing Li, A. Cuschieri, Zhigang Wang, Chengyu Liu, Jianfeng Wu, Li Zhang, Caiyun Ma, Kemin Wang, Shoushui Wei and Xiaoyan Xu. Their work appears in journals such as Sensors and Actuators B Chemical, Biomedical Signal Processing and Control, Electronics, Analytica Chimica Acta and HardwareX.

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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