Subha D. Puthankattil
- Cognitive Neuroscience top 2%
- Cardiology and Cardiovascular Medicine top 5%
- Experimental and Cognitive Psychology top 5%
- Signal Processing top 5%
- Artificial Intelligence
- Co-authors
- U. Rajendra AcharyaPaul K. JosephYuki HagiwaraHojjat AdeliShu Lih OhJen Hong TanGalip AydınUlaş Baran Baloğlu
- Topics
- EEG and Brain-Computer Interfaces (29 papers)ECG Monitoring and Analysis (13 papers)Functional Brain Connectivity Studies (13 papers)
- Cited by
- Cognitive NeuroscienceCardiology and Cardiovascular MedicineExperimental and Cognitive Psychology
- Journals
- SHILAP Revista de lepidopterologíaBrain ResearchComputer Methods and Programs in Biomedicine
In The Last Decade
Subha D. Puthankattil
32 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Cognitive Neuroscience 999
- Cardiology and Cardiovascular Medicine 475
- Experimental and Cognitive Psychology 248
- Signal Processing 119
- Artificial Intelligence 89
Countries citing papers authored by Subha D. Puthankattil
This map shows the geographic impact of Subha D. Puthankattil'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 Subha D. Puthankattil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Subha D. Puthankattil more than expected).
Fields of papers citing papers by Subha D. Puthankattil
This network shows the impact of papers produced by Subha D. Puthankattil. 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 Subha D. Puthankattil. The network helps show where Subha D. Puthankattil may publish in the future.
Co-authorship network of co-authors of Subha D. Puthankattil
This figure shows the co-authorship network connecting the top 25 collaborators of Subha D. Puthankattil. A scholar is included among the top collaborators of Subha D. Puthankattil 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 Subha D. Puthankattil. Subha D. Puthankattil 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 | 3 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | 10 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 42 | |
| 11 | 24 | |
| 12 | 5 | |
| 13 | 11 | |
| 14 | 4 | |
| 15 | 195 | |
| 16 | 30 | |
| 17 | Automated EEG-based screening of depression using deep convolutional neural networkbreakdown → | 450 |
| 18 | 4 | |
| 19 | 90 | |
| 20 | 18 |
About Subha D. Puthankattil
Subha D. Puthankattil is a scholar working on Cognitive Neuroscience, Cardiology and Cardiovascular Medicine and Signal Processing, having authored 33 papers that have together received 1.2k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (29 papers), ECG Monitoring and Analysis (13 papers) and Functional Brain Connectivity Studies (13 papers). The work is most often cited by research in Cognitive Neuroscience (999 citations), Cardiology and Cardiovascular Medicine (475 citations) and Experimental and Cognitive Psychology (248 citations). Subha D. Puthankattil has collaborated with scholars based in India, Singapore and Malaysia. Frequent co-authors include U. Rajendra Acharya, Paul K. Joseph, Yuki Hagiwara, Hojjat Adeli, Shu Lih Oh, Jen Hong Tan, Galip Aydın, Ulaş Baran Baloğlu, Muhammed Talo and Betül Ay. Their work appears in journals such as SHILAP Revista de lepidopterología, Brain Research and Computer Methods and Programs in Biomedicine.
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.