Ignas Martišius
Impact in
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
- Human-Computer Interaction top 5%
- Gaze Tracking and Assistive Technology
Papers in
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- EEG and Brain-Computer Interfaces 8
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- Blind Source Separation Techniques 6
- Digital Filter Design and Implementation 1
- Video Coding and Compression Technologies 1
- Co-authors
- Robertas Damaševičius (10 shared papers)Rytis Maskeliūnas (1 shared paper)Vacius Jusas (8 shared papers)Marcin Woźniak (2 shared papers)
In The Last Decade
Ignas Martišius
12 papers receiving 323 citations
Peers
Comparison fields: 5 of 55
- Cognitive Neuroscience 265
- Human-Computer Interaction 59
- Signal Processing 73
- Cellular and Molecular Neuroscience 81
- Cardiology and Cardiovascular Medicine 45
Countries citing papers authored by Ignas Martišius
This map shows the geographic impact of Ignas Martišius'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 Ignas Martišius with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ignas Martišius more than expected).
Fields of papers citing papers by Ignas Martišius
This network shows the impact of papers produced by Ignas Martišius. 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 Ignas Martišius. The network helps show where Ignas Martišius may publish in the future.
Co-authors
The 4 scholars most cited alongside Ignas Martišius, 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 | 2016 | 145 | |
| 2 | 2016 | 87 | |
| 3 | 2012 | 31 | |
| 4 | 2014 | 26 | |
| 5 | 2015 | 10 | |
| 6 | 2012 | 9 | |
| 7 | 2011 | 8 | |
| 8 | 2015 | 6 | |
| 9 | 2014 | 6 | |
| 10 | 2013 | 6 | |
| 11 | Real-Time Training of Voted Perceptron for Classification of EEG Data | 2013 | 4 |
| 12 | Data acquisition and signal processing methods for brain – computer interfaces | 2016 | 2 |
About Ignas Martišius
Ignas Martišius is a scholar working on Cognitive Neuroscience, Signal Processing, Biomedical Engineering, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 12 papers that have together received 340 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (8 papers), Blind Source Separation Techniques (6 papers), Neuroscience and Neural Engineering (2 papers), Neural Networks and Applications (2 papers), Advanced Memory and Neural Computing (2 papers), Muscle activation and electromyography studies (2 papers), Digital Filter Design and Implementation (1 paper) and Video Coding and Compression Technologies (1 paper). The work is most often cited by research in Cognitive Neuroscience (265 citations), Human-Computer Interaction (59 citations), Signal Processing (73 citations), Cellular and Molecular Neuroscience (81 citations) and Cardiology and Cardiovascular Medicine (45 citations). Ignas Martišius has collaborated with scholars based in Lithuania, Spain and Poland. Frequent co-authors include Robertas Damaševičius, Rytis Maskeliūnas, Vacius Jusas and Marcin Woźniak. Their work appears in journals such as Computational Intelligence and Neuroscience, PeerJ, Elektronika ir Elektrotechnika, Computer Science and Information Systems and Information Technology And Control.
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.