Shivnarayan Patidar
- Cognitive Neuroscience top 5%
- Cardiology and Cardiovascular Medicine top 5%
- Signal Processing top 2%
- Pulmonary and Respiratory Medicine top 10%
- Biomedical Engineering
- Co-authors
- Ram Bilas PachoriU. Rajendra AcharyaTrilochan PanigrahiAbhay UpadhyayAshish SharmaSoumya JanaRu‐San TanVaneet Aggarwal
- Topics
- ECG Monitoring and Analysis (16 papers)Phonocardiography and Auscultation Techniques (10 papers)EEG and Brain-Computer Interfaces (8 papers)
- Partner nations
- IndiaSingaporeUnited States
In The Last Decade
Shivnarayan Patidar
27 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 83
- Cognitive Neuroscience 656
- Cardiology and Cardiovascular Medicine 503
- Signal Processing 405
- Pulmonary and Respiratory Medicine 204
- Biomedical Engineering 195
Countries citing papers authored by Shivnarayan Patidar
This map shows the geographic impact of Shivnarayan Patidar'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 Shivnarayan Patidar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shivnarayan Patidar more than expected).
Fields of papers citing papers by Shivnarayan Patidar
This network shows the impact of papers produced by Shivnarayan Patidar. 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 Shivnarayan Patidar. The network helps show where Shivnarayan Patidar may publish in the future.
Co-authorship network of co-authors of Shivnarayan Patidar
This figure shows the co-authorship network connecting the top 25 collaborators of Shivnarayan Patidar. A scholar is included among the top collaborators of Shivnarayan Patidar 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 Shivnarayan Patidar. Shivnarayan Patidar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 19 | |
| 5 | 13 | |
| 6 | 23 | |
| 7 | 35 | |
| 8 | 2 | |
| 9 | 5 | |
| 10 | 70 | |
| 11 | 7 | |
| 12 | 11 | |
| 13 | 97 | |
| 14 | 4 | |
| 15 | 145 | |
| 16 | 76 | |
| 17 | 3 | |
| 18 | 84 | |
| 19 | 217 | |
| 20 | 9 |
About Shivnarayan Patidar
Shivnarayan Patidar is a scholar working on Computational Mathematics, Cardiology and Cardiovascular Medicine and Signal Processing, having authored 28 papers that have together received 1.1k indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (16 papers), Phonocardiography and Auscultation Techniques (10 papers) and EEG and Brain-Computer Interfaces (8 papers). The work is most often cited by research in Signal Processing (405 citations), Cognitive Neuroscience (656 citations) and Cardiology and Cardiovascular Medicine (503 citations). Shivnarayan Patidar has collaborated with scholars based in India, Singapore and United States. Frequent co-authors include Ram Bilas Pachori, U. Rajendra Acharya, Trilochan Panigrahi, Abhay Upadhyay, Ashish Sharma, Soumya Jana, Ru‐San Tan, Vaneet Aggarwal, T. Veerakumar and M. H. Vasantha. Their work appears in journals such as Critical Care Medicine, Expert Systems with Applications and Applied Soft Computing.
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.