Hsien–Tsai Wu
- Cardiology and Cardiovascular Medicine top 5%
- Biomedical Engineering top 10%
- Signal Processing top 2%
- Computational Mechanics top 10%
- Aerospace Engineering top 10%
- Topics
- Heart Rate Variability and Autonomic Control (45 papers)Non-Invasive Vital Sign Monitoring (45 papers)Cardiovascular Health and Disease Prevention (30 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsIEEE Transactions on Signal Processing
- Partner nations
- TaiwanChinaUnited States
In The Last Decade
Hsien–Tsai Wu
87 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 124
- Cardiology and Cardiovascular Medicine 489
- Biomedical Engineering 407
- Signal Processing 309
- Computational Mechanics 145
- Aerospace Engineering 110
Countries citing papers authored by Hsien–Tsai Wu
This map shows the geographic impact of Hsien–Tsai Wu'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 Hsien–Tsai Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hsien–Tsai Wu more than expected).
Fields of papers citing papers by Hsien–Tsai Wu
This network shows the impact of papers produced by Hsien–Tsai Wu. 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 Hsien–Tsai Wu. The network helps show where Hsien–Tsai Wu may publish in the future.
Co-authorship network of co-authors of Hsien–Tsai Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Hsien–Tsai Wu. A scholar is included among the top collaborators of Hsien–Tsai Wu 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 Hsien–Tsai Wu. Hsien–Tsai Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 14 | |
| 4 | 1 | |
| 5 | 9 | |
| 6 | 34 | |
| 7 | 12 | |
| 8 | 26 | |
| 9 | 14 | |
| 10 | 7 | |
| 11 | 29 | |
| 12 | 7 | |
| 13 | 13 | |
| 14 | 4 | |
| 15 | 24 | |
| 16 | 2 | |
| 17 | 15 | |
| 18 | 40 | |
| 19 | 35 | |
| 20 | Using artificial neural network for providing hourly load update and next day load profile | 2 |
About Hsien–Tsai Wu
Hsien–Tsai Wu is a scholar working on Cardiology and Cardiovascular Medicine, Biomedical Engineering and Complementary and alternative medicine, having authored 91 papers that have together received 1.2k indexed citations. Recurring topics across this work include Heart Rate Variability and Autonomic Control (45 papers), Non-Invasive Vital Sign Monitoring (45 papers) and Cardiovascular Health and Disease Prevention (30 papers). The work is most often cited by research in Signal Processing (309 citations), Cardiology and Cardiovascular Medicine (489 citations) and Biomedical Engineering (407 citations). Hsien–Tsai Wu has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Jar‐Ferr Yang, Fu‐Kun Chen, Cheuk‐Kwan Sun, S.M. Kuo, An‐Bang Liu, Po‐Chun Hsu, Haicheng Wei, Na Ta, I‐Ting Tsai and Mao‐Chang Su. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Signal Processing.
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.